diff --git a/_data/navigation.yml b/_data/navigation.yml index 58f2105..78db1b7 100644 --- a/_data/navigation.yml +++ b/_data/navigation.yml @@ -4,6 +4,8 @@ main: url: /about/ - title: "Standards" url: /standards/ + - title: "Commitee" + url: /committee/ - title: "News" url: /post/ # - title: "Sample Posts" diff --git a/committee.md b/committee.md index 6e11af6..e5a19f7 100644 --- a/committee.md +++ b/committee.md @@ -8,9 +8,6 @@ header: overlay_filter: 0.8 --- - -# MISP Standard Committee Charter - # MISP Standard Committee Charter ## Introduction diff --git a/rfc/misp-standard-taxonomy-format.html b/rfc/misp-standard-taxonomy-format.html index a0b20b8..08a73a6 100644 --- a/rfc/misp-standard-taxonomy-format.html +++ b/rfc/misp-standard-taxonomy-format.html @@ -8,31 +8,26 @@ - + @@ -44,7 +39,7 @@ cyber security events, threats, suspicious events, or indicators. this can be consolidated so that style settings occur only in one place, but for now the contents of this file consists first of the initial CSS work as provided to the RFC Formatter (xml2rfc) work, followed by itemized and - commented changes found necssary during the development of the v3 + commented changes found necessary during the development of the v3 formatters. */ @@ -54,9 +49,14 @@ cyber security events, threats, suspicious events, or indicators. @import url('https://fonts.googleapis.com/css?family=Noto+Serif'); /* Serif (print) */ @import url('https://fonts.googleapis.com/css?family=Roboto+Mono'); /* Monospace */ +:root { + --font-sans: 'Noto Sans', Arial, Helvetica, sans-serif; + --font-serif: 'Noto Serif', 'Times', 'Times New Roman', serif; + --font-mono: 'Roboto Mono', Courier, 'Courier New', monospace; +} + @viewport { zoom: 1.0; - width: extend-to-zoom; } @-ms-viewport { width: extend-to-zoom; @@ -71,9 +71,10 @@ body { color: #222; background-color: #fff; font-size: 14px; - font-family: 'Noto Sans', Arial, Helvetica, sans-serif; + font-family: var(--font-sans); line-height: 1.6; scroll-behavior: smooth; + overflow-wrap: break-word; } .ears { display: none; @@ -160,6 +161,15 @@ div { svg { display: block; } +svg[font-family~="serif" i], svg [font-family~="serif" i] { + font-family: var(--font-serif); +} +svg[font-family~="sans-serif" i], svg [font-family~="sans-serif" i] { + font-family: var(--font-sans); +} +svg[font-family~="monospace" i], svg [font-family~="monospace" i] { + font-family: var(--font-mono); +} .alignCenter.art-text { background-color: #f9f9f9; border: 1px solid #eee; @@ -174,11 +184,8 @@ svg { margin: 1em 0; } .alignCenter > *:first-child { - border: none; - /* this isn't optimal, but it's an existence proof. PrinceXML doesn't - support flexbox yet. - */ display: table; + border: none; margin: 0 auto; } @@ -256,9 +263,9 @@ a.selfRef:hover { } */ /* Figures */ -tt, code, pre, code { +tt, code, pre { background-color: #f9f9f9; - font-family: 'Roboto Mono', monospace; + font-family: var(--font-mono); } pre { border: 1px solid #eee; @@ -298,11 +305,17 @@ blockquote { border-radius: 3px; margin: 1em 0; } +blockquote > *:last-child { + margin-bottom: 0; +} cite { display: block; text-align: right; font-style: italic; } +.xref { + overflow-wrap: normal; +} /* tables */ table { @@ -447,6 +460,10 @@ nav.toc li { margin-bottom: 1.25em; } +.refSubseries { + margin-bottom: 1.25em; +} + .references .ascii { margin-bottom: 0.25em; } @@ -495,7 +512,7 @@ address.vcard .nameRole { margin-left: 0; } address.vcard .label { - font-family: "Noto Sans",Arial,Helvetica,sans-serif; + font-family: var(--font-sans); margin: 0.5em 0; } address.vcard .type { @@ -635,7 +652,6 @@ hr.addr { /* pagination */ @media print { body { - width: 100%; } p { @@ -658,6 +674,9 @@ hr.addr { figure { overflow: scroll; } + .breakable pre { + break-inside: auto; + } h1, h2, h3, h4, h5, h6 { page-break-after: avoid; } @@ -725,7 +744,7 @@ hr.addr { size: A4; margin-bottom: 45mm; padding-top: 20px; - /* The follwing is commented out here, but set appropriately by in code, as + /* The following is commented out here, but set appropriately by in code, as the content depends on the document */ /* @top-left { @@ -825,12 +844,12 @@ section { } /* prevent monospace from becoming overly large */ -tt, code, pre, code { +tt, code, pre { font-size: 95%; } /* Fix the height/width aspect for ascii art*/ -pre.sourcecode, +.sourcecode pre, .art-text pre { line-height: 1.12; } @@ -866,7 +885,7 @@ table th.text-right { text-align: right; } -/* Make the alternative author contact informatio look less like just another +/* Make the alternative author contact information look less like just another author, and group it closer with the primary author contact information */ .alternative-contact { margin: 0.5em 0 0.25em 0; @@ -1048,6 +1067,7 @@ aside > p { /* Sourcecode margin in print, when there's no pilcrow */ @media print { .artwork, + .artwork > pre, .sourcecode { margin-bottom: 1em; } @@ -1062,13 +1082,16 @@ ol.type-A { list-style-type: upper-alpha; } ol.type-i { list-style-type: lower-roman; } ol.type-I { list-style-type: lower-roman; } /* Apply the print table and row borders in general, on request from the RPC, -and increase the contrast between border and odd row background sligthtly */ +and increase the contrast between border and odd row background slightly */ table { border: 1px solid #ddd; } td { border-top: 1px solid #ddd; } +tr { + break-inside: avoid; +} tr:nth-child(2n+1) > td { background-color: #f8f8f8; } @@ -1119,7 +1142,7 @@ span.break, dd.break { break-before: auto; } } -/* Text in compact lists should not get extra bottim margin space, +/* Text in compact lists should not get extra bottom margin space, since that would makes the list not compact */ ul.compact p, .ulCompact p, ol.compact p, .olCompact p { @@ -1144,7 +1167,7 @@ p tt, p code, li tt, li code { pre { margin-top: 0.5px; } -/* Tweak the comact list text */ +/* Tweak the compact list text */ ul.compact, .ulCompact, ol.compact, .olCompact, dl.compact, .dlCompact { @@ -1162,7 +1185,7 @@ dd > div.artwork:first-child, dd > aside:first-child, dd > figure:first-child, dd > ol:first-child, -dd > div:first-child > pre.sourcecode, +dd > div.sourcecode:first-child, dd > table:first-child, dd > ul:first-child { clear: left; @@ -1176,24 +1199,24 @@ li > p { margin-bottom: 0.5em } /* Don't let p margin spill out from inside list items */ -li > p:last-of-type { +li > p:last-of-type:only-child { margin-bottom: 0; } - + - + - +
Internet-Draft MISP taxonomy formatDecember 2023December 2024
Dulaunoy & IklodyExpires 26 June 2024Expires 3 July 2025 [Page]
@@ -1206,12 +1229,12 @@ li > p:last-of-type {
draft-08
Published:
- +
Intended Status:
Informational
Expires:
-
+
Authors:
@@ -1228,10 +1251,7 @@ li > p:last-of-type {

MISP taxonomy format

Abstract

-

This document describes the MISP taxonomy format which describes a simple JSON format to -represent machine tags (also called triple tags) vocabularies. A public directory of common vocabularies -called MISP taxonomies is available and relies on the MISP taxonomy format. MISP taxonomies are used to classify -cyber security events, threats, suspicious events, or indicators.

+

This document outlines the MISP taxonomy format, a straightforward JSON structure designed to represent machine tags (also known as triple tags) vocabularies. A public directory, referred to as MISP taxonomies, is available and leverages this format. These taxonomies are used to classify cybersecurity events, threats, suspicious activities, and indicators.

@@ -1252,7 +1272,7 @@ cyber security events, threats, suspicious events, or indicators.

- This Internet-Draft will expire on 26 June 2024.

+ This Internet-Draft will expire on 3 July 2025.

The MISP taxonomy format describes how to define a machine tag namespace in a parseable format. The objective is to provide a simple format @@ -1401,7 +1423,7 @@ to describe machine tag (aka triple tag) vocabularies. 2.1. Overview -

The MISP taxonomy format uses the JSON [RFC8259] format. Each namespace is represented as a JSON object with meta information including the following fields: namespace, description, version, type.

+

The MISP taxonomy format uses the JSON [RFC8259] format. Each namespace is represented as a JSON object with meta information including the following fields: namespace, description, version, type.

namespace defines the overall namespace of the machine tag. The namespace is represented as a string and MUST be present. The description is represented as a string and MUST be present. A version is represented as a unsigned integer MUST be present. A type defines where a specific taxonomy is applicable and a type can be applicable at event, user or org level. The type is represented as an array containing one or more type and SHOULD be present. If a type is not mentioned, by default, the taxonomy is applicable at event level only. An exclusive boolean property MAY be present and defines at namespace level if the predicates are mutually exclusive.

predicates defines all the predicates available in the namespace defined. predicates is represented as an array of JSON objects. predicates MUST be present and MUST at least content one element.

values defines all the values for each predicate in the namespace defined. values SHOULD be present.

@@ -1451,6 +1473,7 @@ to describe machine tag (aka triple tag) vocabularies.
@@ -1508,6 +1531,7 @@ among taxonomies.

} ] } + @@ -1521,7 +1545,7 @@ among taxonomies.

3. Directory

-

The MISP taxonomies directory is publicly available [MISP-T] in a git repository. The repository +

The MISP taxonomies directory is publicly available [MISP-T] in a git repository. The repository contains a directory per namespace then a file machinetag.json which contains the taxonomy as described in the format above. In the root of the repository, a MANIFEST.json exists containing a list of all the taxonomies.

@@ -1554,6 +1578,7 @@ A taxonomies array describes the taxonomy available with the description, name a "version": 2 }] } + @@ -1647,6 +1672,7 @@ A taxonomies array describes the taxonomy available with the description, name a } ] } + @@ -1780,618 +1806,173 @@ A taxonomies array describes the taxonomy available with the description, name a ] } + -
+

-4.3. Available taxonomies in the public directory +4.3. Available taxonomies in the public repository

-

The public directory of MISP taxonomies [MISP-T] contains a variety of taxonomy in various fields such as:

-
-
CERT-XLM:
-
CERT-XLM Security Incident Classification. -
-
-
DFRLab-dichotomies-of-disinformation:
-
DFRLab Dichotomies of Disinformation. -
-
-
DML:
-
The Detection Maturity Level (DML) model is a capability maturity model for referencing ones maturity in detecting cyber attacks. It's designed for organizations who perform intel-driven detection and response and who put an emphasis on having a mature detection program. -
-
-
GrayZone:
-
Gray Zone of Active defense includes all elements which lay between reactive defense elements and offensive operations. It does fill the gray spot between them. Taxo may be used for active defense planning or modeling. -
-
-
PAP:
-
The Permissible Actions Protocol - or short: PAP - was designed to indicate how the received information can be used. -
-
-
access-method:
-
The access method used to remotely access a system. -
-
-
accessnow:
-
Access Now classification to classify an issue (such as security, human rights, youth rights). -
-
-
action-taken:
-
Action taken in the case of a security incident (CSIRT perspective). -
-
-
admiralty-scale:
-
The Admiralty Scale or Ranking (also called the NATO System) is used to rank the reliability of a source and the credibility of an information. Reference based on FM 2-22.3 (FM 34-52) HUMAN INTELLIGENCE COLLECTOR OPERATIONS and NATO documents. -
-
-
adversary:
-
An overview and description of the adversary infrastructure -
-
-
ais-marking:
-
The AIS Marking Schema implementation is maintained by the National Cybersecurity and Communication Integration Center (NCCIC) of the U.S. Department of Homeland Security (DHS) -
-
-
analyst-assessment:
-
A series of assessment predicates describing the analyst capabilities to perform analysis. These assessment can be assigned by the analyst him/herself or by another party evaluating the analyst. -
-
-
approved-category-of-action:
-
A pre-approved category of action for indicators being shared with partners (MIMIC). -
-
-
artificial-satellites:
-
This taxonomy was designed to describe artificial satellites -
-
-
aviation:
-
A taxonomy describing security threats or incidents against the aviation sector. -
-
-
binary-class:
-
Custom taxonomy for types of binary file. -
-
-
cccs:
-
Internal taxonomy for CCCS. -
-
-
circl:
-
CIRCL Taxonomy - Schemes of Classification in Incident Response and Detection. -
-
-
cnsd:
-
La presente taxonomia es la primera versión disponible para el Centro Nacional de Seguridad Digital del Perú. -
-
-
coa:
-
Course of action taken within organization to discover, detect, deny, disrupt, degrade, deceive and/or destroy an attack. -
-
-
collaborative-intelligence:
-
Collaborative intelligence support language is a common language to support analysts to perform their analysis to get crowdsourced support when using threat intelligence sharing platform like MISP. The objective of this language is to advance collaborative analysis and to share earlier than later. -
-
-
common-taxonomy:
-
Common Taxonomy for Law enforcement and CSIRTs -
-
-
copine-scale:
-
The COPINE Scale is a rating system created in Ireland and used in the United Kingdom to categorise the severity of images of child sex abuse. The scale was developed by staff at the COPINE (Combating Paedophile Information Networks in Europe) project. The COPINE Project was founded in 1997, and is based in the Department of Applied Psychology, University College Cork, Ireland. -
-
-
course-of-action:
-
A Course Of Action analysis considers six potential courses of action for the development of a cyber security capability. -
-
-
crowdsec:
-
Crowdsec IP address classifications and behaviors taxonomy. -
-
-
cryptocurrency-threat:
-
Threats targetting cryptocurrency, based on CipherTrace report. -
-
-
csirt-americas:
-
Taxonomía CSIRT Américas. -
-
-
csirt_case_classification:
-
It is critical that the CSIRT provide consistent and timely response to the customer, and that sensitive information is handled appropriately. This document provides the guidelines needed for CSIRT Incident Managers (IM) to classify the case category, criticality level, and sensitivity level for each CSIRT case. This information will be entered into the Incident Tracking System (ITS) when a case is created. Consistent case classification is required for the CSIRT to provide accurate reporting to management on a regular basis. In addition, the classifications will provide CSIRT IM's with proper case handling procedures and will form the basis of SLA's between the CSIRT and other Company departments. -
-
-
cssa:
-
The CSSA agreed sharing taxonomy. -
-
-
cti:
-
Cyber Threat Intelligence cycle to control workflow state of your process. -
-
-
current-event:
-
Current events - Schemes of Classification in Incident Response and Detection -
-
-
cyber-threat-framework:
-
Cyber Threat Framework was developed by the US Government to enable consistent characterization and categorization of cyber threat events, and to identify trends or changes in the activities of cyber adversaries. https://www.dni.gov/index.php/cyber-threat-framework -
-
-
cycat:
-
Taxonomy used by CyCAT, the Universal Cybersecurity Resource Catalogue, to categorize the namespaces it supports and uses. -
-
-
cytomic-orion:
-
Taxonomy to describe desired actions for Cytomic Orion -
-
-
dark-web:
-
Criminal motivation and content detection the dark web: A categorisation model for law enforcement. ref: Janis Dalins, Campbell Wilson, Mark Carman. Taxonomy updated by MISP Project and extended by the JRC (Joint Research Centre) of the European Commission. -
-
-
data-classification:
-
Data classification for data potentially at risk of exfiltration based on table 2.1 of Solving Cyber Risk book. -
-
-
dcso-sharing:
-
Taxonomy defined in the DCSO MISP Event Guide. It provides guidance for the creation and consumption of MISP events in a way that minimises the extra effort for the sending party, while enhancing the usefulness for receiving parties. -
-
-
ddos:
-
Distributed Denial of Service - or short: DDoS - taxonomy supports the description of Denial of Service attacks and especially the types they belong too. -
-
-
de-vs:
-
German (DE) Government classification markings (VS). -
-
-
death-possibilities:
-
Taxonomy of Death Possibilities -
-
-
deception:
-
Deception is an important component of information operations, valuable for both offense and defense. -
-
-
dga:
-
A taxonomy to describe domain-generation algorithms often called DGA. Ref: A Comprehensive Measurement Study of Domain Generating Malware Daniel Plohmann and others. -
-
-
dhs-ciip-sectors:
-
DHS critical sectors as in https://www.dhs.gov/critical-infrastructure-sectors -
-
-
diamond-model:
-
The Diamond Model for Intrusion Analysis establishes the basic atomic element of any intrusion activity, the event, composed of four core features: adversary, infrastructure, capability, and victim. -
-
-
diamond-model-for-influence-operations:
-
The diamond model for influence operations analysis is a framework that leads analysts and researchers toward a comprehensive understanding of a malign influence campaign by addressing the socio-political, technical, and psychological aspects of the campaign. The diamond model for influence operations analysis consists of 5 components: 4 corners and a core element. The 4 corners are divided into 2 axes: influencer and audience on the socio-political axis, capabilities and infrastructure on the technical axis. Narrative makes up the core of the diamond. -
-
-
dni-ism:
-
A subset of Information Security Marking Metadata ISM as required by Executive Order (EO) 13526. As described by DNI.gov as Data Encoding Specifications for Information Security Marking Metadata in Controlled Vocabulary Enumeration Values for ISM -
-
-
domain-abuse:
-
Domain Name Abuse - taxonomy to tag domain names used for cybercrime. -
-
-
doping-substances:
-
This taxonomy aims to list doping substances -
-
-
drugs:
-
A taxonomy based on the superclass and class of drugs. Based on https://www.drugbank.ca/releases/latest -
-
-
economical-impact:
-
Economical impact is a taxonomy to describe the financial impact as positive or negative gain to the tagged information (e.g. data exfiltration loss, a positive gain for an adversary). -
-
-
ecsirt:
-
Incident Classification by the ecsirt.net version mkVI of 31 March 2015 enriched with IntelMQ taxonomy-type mapping. -
-
-
enisa:
-
The present threat taxonomy is an initial version that has been developed on the basis of available ENISA material. This material has been used as an ENISA-internal structuring aid for information collection and threat consolidation purposes. It emerged in the time period 2012-2015. -
-
-
estimative-language:
-
Estimative language to describe quality and credibility of underlying sources, data, and methodologies based Intelligence Community Directive 203 (ICD 203) and JP 2-0, Joint Intelligence -
-
-
eu-marketop-and-publicadmin:
-
Market operators and public administrations that must comply to some notifications requirements under EU NIS directive -
-
-
eu-nis-sector-and-subsectors:
-
Sectors, subsectors, and digital services as identified by the NIS Directive -
-
-
euci:
-
EU classified information (EUCI) means any information or material designated by a EU security classification, the unauthorised disclosure of which could cause varying degrees of prejudice to the interests of the European Union or of one or more of the Member States. -
-
-
europol-event:
-
This taxonomy was designed to describe the type of events -
-
-
europol-incident:
-
This taxonomy was designed to describe the type of incidents by class. -
-
-
event-assessment:
-
A series of assessment predicates describing the event assessment performed to make judgement(s) under a certain level of uncertainty. -
-
-
event-classification:
-
Classification of events as seen in tools such as RT/IR, MISP and other -
-
-
exercise:
-
Exercise is a taxonomy to describe if the information is part of one or more cyber or crisis exercise. -
-
-
extended-event:
-
Reasons why an event has been extended. This taxonomy must be used on the extended event. The competitive analysis aspect is from Psychology of Intelligence Analysis by Richard J. Heuer, Jr. ref:http://www.foo.be/docs/intelligence/PsychofIntelNew.pdf -
-
-
failure-mode-in-machine-learning:
-
The purpose of this taxonomy is to jointly tabulate both the of these failure modes in a single place. Intentional failures wherein the failure is caused by an active adversary attempting to subvert the system to attain her goals - either to misclassify the result, infer private training data, or to steal the underlying algorithm. Unintentional failures wherein the failure is because an ML system produces a formally correct but completely unsafe outcome. -
-
-
false-positive:
-
This taxonomy aims to ballpark the expected amount of false positives. -
-
-
file-type:
-
List of known file types. -
-
-
financial:
-
Financial taxonomy to describe financial services, infrastructure and financial scope. -
-
-
flesch-reading-ease:
-
Flesch Reading Ease is a revised system for determining the comprehension difficulty of written material. The scoring of the flesh score can have a maximum of 121.22 and there is no limit on how low a score can be (negative score are valid). -
-
-
fpf:
-
The Future of Privacy Forum (FPF) visual guide to practical de-identification taxonomy is used to evaluate the degree of identifiability of personal data and the types of pseudonymous data, de-identified data and anonymous data. The work of FPF is licensed under a creative commons attribution 4.0 international license. -
-
-
fr-classif:
-
French gov information classification system -
-
-
gdpr:
-
Taxonomy related to the REGULATION (EU) 2016/679 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation) -
-
-
gea-nz-activities:
-
Information needed to track or monitor moments, periods or events that occur over time. This type of information is focused on occurrences that must be tracked for business reasons or represent a specific point in the evolution of 'The Business'. -
-
-
gea-nz-entities:
-
Information relating to instances of entities or things. -
-
-
gea-nz-motivators:
-
Information relating to authority or governance. -
-
-
gsma-attack-category:
-
Taxonomy used by GSMA for their information sharing program with telco describing the attack categories -
-
-
gsma-fraud:
-
Taxonomy used by GSMA for their information sharing program with telco describing the various aspects of fraud -
-
-
gsma-network-technology:
-
Taxonomy used by GSMA for their information sharing program with telco describing the types of infrastructure. WiP -
-
-
honeypot-basic:
-
Updated (CIRCL, Seamus Dowling and EURECOM) from Christian Seifert, Ian Welch, Peter Komisarczuk, 'Taxonomy of Honeypots', Technical Report CS-TR-06/12, VICTORIA UNIVERSITY OF WELLINGTON, School of Mathematical and Computing Sciences, June 2006, http://www.mcs.vuw.ac.nz/comp/Publications/archive/CS-TR-06/CS-TR-06-12.pdf -
-
-
ics:
-
FIRST.ORG CTI SIG - MISP Proposal for ICS/OT Threat Attribution (IOC) Project -
-
-
iep:
-
Forum of Incident Response and Security Teams (FIRST) Information Exchange Policy (IEP) framework -
-
-
iep2-policy:
-
Forum of Incident Response and Security Teams (FIRST) Information Exchange Policy (IEP) v2.0 Policy -
-
-
iep2-reference:
-
Forum of Incident Response and Security Teams (FIRST) Information Exchange Policy (IEP) v2.0 Reference -
-
-
ifx-vetting:
-
The IFX taxonomy is used to categorise information (MISP events and attributes) to aid in the intelligence vetting process -
-
-
incident-disposition:
-
How an incident is classified in its process to be resolved. The taxonomy is inspired from NASA Incident Response and Management Handbook. https://www.nasa.gov/pdf/589502main_ITS-HBK-2810.09-02%20%5bNASA%20Information%20Security%20Incident%20Management%5d.pdf#page=9 -
-
-
infoleak:
-
A taxonomy describing information leaks and especially information classified as being potentially leaked. The taxonomy is based on the work by CIRCL on the AIL framework. The taxonomy aim is to be used at large to improve classification of leaked information. -
-
-
information-origin:
-
Taxonomy for tagging information by its origin: human-generated or AI-generated. -
-
-
information-security-data-source:
-
Taxonomy to classify the information security data sources. -
-
-
information-security-indicators:
-
A full set of operational indicators for organizations to use to benchmark their security posture. -
-
-
interactive-cyber-training-audience:
-
Describes the target of cyber training and education. -
-
-
interactive-cyber-training-technical-setup:
-
The technical setup consists of environment structure, deployment, and orchestration. -
-
-
interactive-cyber-training-training-environment:
-
The training environment details the environment around the training, consisting of training type and scenario. -
-
-
interactive-cyber-training-training-setup:
-
The training setup further describes the training itself with the scoring, roles, the training mode as well as the customization level. -
-
-
interception-method:
-
The interception method used to intercept traffic. -
-
-
ioc:
-
An IOC classification to facilitate automation of malicious and non malicious artifacts -
-
-
iot:
-
Internet of Things taxonomy, based on IOT UK report https://iotuk.org.uk/wp-content/uploads/2017/01/IOT-Taxonomy-Report.pdf -
-
-
kill-chain:
-
The Cyber Kill Chain, a phase-based model developed by Lockheed Martin, aims to help categorise and identify the stage of an attack. -
-
-
maec-delivery-vectors:
-
Vectors used to deliver malware based on MAEC 5.0 -
-
-
maec-malware-behavior:
-
Malware behaviours based on MAEC 5.0 -
-
-
maec-malware-capabilities:
-
Malware Capabilities based on MAEC 5.0 -
-
-
maec-malware-obfuscation-methods:
-
Obfuscation methods used by malware based on MAEC 5.0 -
-
-
malware_classification:
-
Classification based on different categories. Based on https://www.sans.org/reading-room/whitepapers/incident/malware-101-viruses-32848 -
-
-
misinformation-website-label:
-
classification for the identification of type of misinformation among websites. Source:False, Misleading, Clickbait-y, and/or Satirical News Sources by Melissa Zimdars 2019 -
-
-
misp:
-
MISP taxonomy to infer with MISP behavior or operation. -
-
-
misp-workflow:
-
MISP workflow taxonomy to support result of workflow execution. -
-
-
monarc-threat:
-
MONARC Threats Taxonomy -
-
-
ms-caro-malware:
-
Malware Type and Platform classification based on Microsoft's implementation of the Computer Antivirus Research Organization (CARO) Naming Scheme and Malware Terminology. Based on https://www.microsoft.com/en-us/security/portal/mmpc/shared/malwarenaming.aspx, https://www.microsoft.com/security/portal/mmpc/shared/glossary.aspx, https://www.microsoft.com/security/portal/mmpc/shared/objectivecriteria.aspx, and http://www.caro.org/definitions/index.html. Malware families are extracted from Microsoft SIRs since 2008 based on https://www.microsoft.com/security/sir/archive/default.aspx and https://www.microsoft.com/en-us/security/portal/threat/threats.aspx. Note that SIRs do NOT include all Microsoft malware families. -
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ms-caro-malware-full:
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Malware Type and Platform classification based on Microsoft's implementation of the Computer Antivirus Research Organization (CARO) Naming Scheme and Malware Terminology. Based on https://www.microsoft.com/en-us/security/portal/mmpc/shared/malwarenaming.aspx, https://www.microsoft.com/security/portal/mmpc/shared/glossary.aspx, https://www.microsoft.com/security/portal/mmpc/shared/objectivecriteria.aspx, and http://www.caro.org/definitions/index.html. Malware families are extracted from Microsoft SIRs since 2008 based on https://www.microsoft.com/security/sir/archive/default.aspx and https://www.microsoft.com/en-us/security/portal/threat/threats.aspx. Note that SIRs do NOT include all Microsoft malware families. -
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mwdb:
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Malware Database (mwdb) Taxonomy - Tags used across the platform -
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nato:
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NATO classification markings. -
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-
nis:
-
The taxonomy is meant for large scale cybersecurity incidents, as mentioned in the Commission Recommendation of 13 September 2017, also known as the blueprint. It has two core parts: The nature of the incident, i.e. the underlying cause, that triggered the incident, and the impact of the incident, i.e. the impact on services, in which sector(s) of economy and society. -
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nis2:
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The taxonomy is meant for large scale cybersecurity incidents, as mentioned in the Commission Recommendation of 13 May 2022, also known as the provisional agreement. It has two core parts: The nature of the incident, i.e. the underlying cause, that triggered the incident, and the impact of the incident, i.e. the impact on services, in which sector(s) of economy and society. -
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-
open_threat:
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Open Threat Taxonomy v1.1 base on James Tarala of SANS http://www.auditscripts.com/resources/open_threat_taxonomy_v1.1a.pdf, https://files.sans.org/summit/Threat_Hunting_Incident_Response_Summit_2016/PDFs/Using-Open-Tools-to-Convert-Threat-Intelligence-into-Practical-Defenses-James-Tarala-SANS-Institute.pdf, https://www.youtube.com/watch?v=5rdGOOFC_yE, and https://www.rsaconference.com/writable/presentations/file_upload/str-r04_using-an-open-source-threat-model-for-prioritized-defense-final.pdf -
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osint:
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Open Source Intelligence - Classification (MISP taxonomies) -
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pandemic:
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Pandemic -
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passivetotal:
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Tags from RiskIQ's PassiveTotal service -
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pentest:
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Penetration test (pentest) classification. -
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phishing:
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Taxonomy to classify phishing attacks including techniques, collection mechanisms and analysis status. -
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poison-taxonomy:
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Non-exhaustive taxonomy of natural poison -
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political-spectrum:
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A political spectrum is a system to characterize and classify different political positions in relation to one another. -
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priority-level:
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After an incident is scored, it is assigned a priority level. The six levels listed below are aligned with NCCIC, DHS, and the CISS to help provide a common lexicon when discussing incidents. This priority assignment drives NCCIC urgency, pre-approved incident response offerings, reporting requirements, and recommendations for leadership escalation. Generally, incident priority distribution should follow a similar pattern to the graph below. Based on https://www.us-cert.gov/NCCIC-Cyber-Incident-Scoring-System. -
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pyoti:
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PyOTI automated enrichment schemes for point in time classification of indicators. -
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ransomware:
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Ransomware is used to define ransomware types and the elements that compose them. -
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ransomware-roles:
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The seven roles seen in most ransomware incidents. -
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retention:
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Add a retenion time to events to automatically remove the IDS-flag on ip-dst or ip-src attributes. We calculate the time elapsed based on the date of the event. Supported time units are: d(ays), w(eeks), m(onths), y(ears). The numerical_value is just for sorting in the web-interface and is not used for calculations. -
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rsit:
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Reference Security Incident Classification Taxonomy -
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rt_event_status:
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Status of events used in Request Tracker. -
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-
runtime-packer:
-
Runtime or software packer used to combine compressed or encrypted data with the decompression or decryption code. This code can add additional obfuscations mechanisms including polymorphic-packer or other obfuscation techniques. This taxonomy lists all the known or official packer used for legitimate use or for packing malicious binaries. -
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scrippsco2-fgc:
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Flags describing the sample -
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scrippsco2-fgi:
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Flags describing the sample for isotopic data (C14, O18) -
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scrippsco2-sampling-stations:
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Sampling stations of the Scripps CO2 Program -
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sentinel-threattype:
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Sentinel indicator threat types. -
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smart-airports-threats:
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Threat taxonomy in the scope of securing smart airports by ENISA. https://www.enisa.europa.eu/publications/securing-smart-airports -
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social-engineering-attack-vectors:
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Attack vectors used in social engineering as described in 'A Taxonomy of Social Engineering Defense Mechanisms' by Dalal Alharthi and others. -
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srbcert:
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SRB-CERT Taxonomy - Schemes of Classification in Incident Response and Detection -
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state-responsibility:
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A spectrum of state responsibility to more directly tie the goals of attribution to the needs of policymakers. -
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stealth_malware:
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Classification based on malware stealth techniques. Described in https://vxheaven.org/lib/pdf/Introducing%20Stealth%20Malware%20Taxonomy.pdf -
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stix-ttp:
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TTPs are representations of the behavior or modus operandi of cyber adversaries. -
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targeted-threat-index:
-
The Targeted Threat Index is a metric for assigning an overall threat ranking score to email messages that deliver malware to a victim's computer. The TTI metric was first introduced at SecTor 2013 by Seth Hardy as part of the talk "RATastrophe: Monitoring a Malware Menagerie" along with Katie Kleemola and Greg Wiseman. -
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thales_group:
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Thales Group Taxonomy - was designed with the aim of enabling desired sharing and preventing unwanted sharing between Thales Group security communities. -
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-
threatmatch:
-
The ThreatMatch Sectors, Incident types, Malware types and Alert types are applicable for any ThreatMatch instances and should be used for all CIISI and TIBER Projects. -
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-
threats-to-dns:
-
An overview of some of the known attacks related to DNS as described by Torabi, S., Boukhtouta, A., Assi, C., & Debbabi, M. (2018) in Detecting Internet Abuse by Analyzing Passive DNS Traffic: A Survey of Implemented Systems. IEEE Communications Surveys & Tutorials, 1-1. doi:10.1109/comst.2018.2849614 -
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-
tlp:
-
The Traffic Light Protocol (TLP) (v2.0) was created to facilitate greater sharing of potentially sensitive information and more effective collaboration. Information sharing happens from an information source, towards one or more recipients. TLP is a set of four standard labels (a fifth label is included in amber to limit the diffusion) used to indicate the sharing boundaries to be applied by the recipients. Only labels listed in this standard are considered valid by FIRST. This taxonomy includes additional labels for backward compatibility which are no more validated by FIRST SIG. -
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tor:
-
Taxonomy to describe Tor network infrastructure -
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-
trust:
-
The Indicator of Trust provides insight about data on what can be trusted and known as a good actor. Similar to a whitelist but on steroids, reusing features one would use with Indicators of Compromise, but to filter out what is known to be good. -
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type:
-
Taxonomy to describe different types of intelligence gathering discipline which can be described the origin of intelligence. -
-
-
unified-kill-chain:
-
The Unified Kill Chain is a refinement to the Kill Chain. -
-
-
use-case-applicability:
-
The Use Case Applicability categories reflect standard resolution categories, to clearly display alerting rule configuration problems. -
-
-
veris:
-
Vocabulary for Event Recording and Incident Sharing (VERIS) -
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-
vmray:
-
VMRay taxonomies to map VMRay Thread Identifier scores and artifacts. -
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-
vocabulaire-des-probabilites-estimatives:
-
Ce vocabulaire attribue des valeurs en pourcentage à certains énoncés de probabilité -
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-
workflow:
-
Workflow support language is a common language to support intelligence analysts to perform their analysis on data and information. -
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-
+

The public directory of MISP taxonomies [MISP-T] contains more than 150 taxonomies spanning various fields, including:

+

CERT-XLM : CERT-XLM Security Incident Classification.

+

DFRLab-dichotomies-of-disinformation : DFRLab Dichotomies of Disinformation.

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DML : The Detection Maturity Level (DML) model is a capability maturity model for referencing ones maturity in detecting cyber attacks. It's designed for organizations who perform intel-driven detection and response and who put an emphasis on having a mature detection program.

+

GrayZone : Gray Zone of Active defense includes all elements which lay between reactive defense elements and offensive operations. It does fill the gray spot between them. Taxo may be used for active defense planning or modeling.

+

PAP : The Permissible Actions Protocol - or short: PAP - was designed to indicate how the received information can be used.

+

access-method : The access method used to remotely access a system.

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accessnow : Access Now classification to classify an issue (such as security, human rights, youth rights).

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acs-marking : The Access Control Specification (ACS) marking type defines the object types required to implement automated access control systems based on the relevant policies governing sharing between participants.

+

action-taken : Action taken in the case of a security incident (CSIRT perspective).

+

admiralty-scale : The Admiralty Scale or Ranking (also called the NATO System) is used to rank the reliability of a source and the credibility of an information. Reference based on FM 2-22.3 (FM 34-52) HUMAN INTELLIGENCE COLLECTOR OPERATIONS and NATO documents.

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adversary : An overview and description of the adversary infrastructure

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ais-marking : The AIS Marking Schema implementation is maintained by the National Cybersecurity and Communication Integration Center (NCCIC) of the U.S. Department of Homeland Security (DHS)

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analyst-assessment : A series of assessment predicates describing the analyst capabilities to perform analysis. These assessment can be assigned by the analyst him/herself or by another party evaluating the analyst.

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approved-category-of-action : A pre-approved category of action for indicators being shared with partners (MIMIC).

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artificial-satellites : This taxonomy was designed to describe artificial satellites

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aviation : A taxonomy describing security threats or incidents against the aviation sector.

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binary-class : Custom taxonomy for types of binary file.

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cccs : Internal taxonomy for CCCS.

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circl : CIRCL Taxonomy - Schemes of Classification in Incident Response and Detection.

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cnsd : La presente taxonomia es la primera versión disponible para el Centro Nacional de Seguridad Digital del Perú.

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coa : Course of action taken within organization to discover, detect, deny, disrupt, degrade, deceive and/or destroy an attack.

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collaborative-intelligence : Collaborative intelligence support language is a common language to support analysts to perform their analysis to get crowdsourced support when using threat intelligence sharing platform like MISP. The objective of this language is to advance collaborative analysis and to share earlier than later.

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common-taxonomy : Common Taxonomy for Law enforcement and CSIRTs

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copine-scale : The COPINE Scale is a rating system created in Ireland and used in the United Kingdom to categorise the severity of images of child sex abuse. The scale was developed by staff at the COPINE (Combating Paedophile Information Networks in Europe) project. The COPINE Project was founded in 1997, and is based in the Department of Applied Psychology, University College Cork, Ireland.

+

course-of-action : A Course Of Action analysis considers six potential courses of action for the development of a cyber security capability.

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crowdsec : Crowdsec IP address classifications and behaviors taxonomy.

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cryptocurrency-threat : Threats targetting cryptocurrency, based on CipherTrace report.

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csirt-americas : Taxonomía CSIRT Américas.

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csirt_case_classification : It is critical that the CSIRT provide consistent and timely response to the customer, and that sensitive information is handled appropriately. This document provides the guidelines needed for CSIRT Incident Managers (IM) to classify the case category, criticality level, and sensitivity level for each CSIRT case. This information will be entered into the Incident Tracking System (ITS) when a case is created. Consistent case classification is required for the CSIRT to provide accurate reporting to management on a regular basis. In addition, the classifications will provide CSIRT IM’s with proper case handling procedures and will form the basis of SLA’s between the CSIRT and other Company departments.

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cssa : The CSSA agreed sharing taxonomy.

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cti : Cyber Threat Intelligence cycle to control workflow state of your process.

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current-event : Current events - Schemes of Classification in Incident Response and Detection

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cyber-threat-framework : Cyber Threat Framework was developed by the US Government to enable consistent characterization and categorization of cyber threat events, and to identify trends or changes in the activities of cyber adversaries. https://www.dni.gov/index.php/cyber-threat-framework

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cycat : Taxonomy used by CyCAT, the Universal Cybersecurity Resource Catalogue, to categorize the namespaces it supports and uses.

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cytomic-orion : Taxonomy to describe desired actions for Cytomic Orion

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dark-web : Criminal motivation and content detection the dark web: A categorisation model for law enforcement. ref: Janis Dalins, Campbell Wilson, Mark Carman. Taxonomy updated by MISP Project and extended by the JRC (Joint Research Centre) of the European Commission.

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data-classification : Data classification for data potentially at risk of exfiltration based on table 2.1 of Solving Cyber Risk book.

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dcso-sharing : Taxonomy defined in the DCSO MISP Event Guide. It provides guidance for the creation and consumption of MISP events in a way that minimises the extra effort for the sending party, while enhancing the usefulness for receiving parties.

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ddos : Distributed Denial of Service - or short: DDoS - taxonomy supports the description of Denial of Service attacks and especially the types they belong too.

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de-vs : German (DE) Government classification markings (VS).

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death-possibilities : Taxonomy of Death Possibilities

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deception : Deception is an important component of information operations, valuable for both offense and defense.

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detection-engineering : Taxonomy related to detection engineering techniques

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dga : A taxonomy to describe domain-generation algorithms often called DGA. Ref: A Comprehensive Measurement Study of Domain Generating Malware Daniel Plohmann and others.

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dhs-ciip-sectors : DHS critical sectors as in https://www.dhs.gov/critical-infrastructure-sectors

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diamond-model : The Diamond Model for Intrusion Analysis establishes the basic atomic element of any intrusion activity, the event, composed of four core features: adversary, infrastructure, capability, and victim.

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diamond-model-for-influence-operations : The diamond model for influence operations analysis is a framework that leads analysts and researchers toward a comprehensive understanding of a malign influence campaign by addressing the socio-political, technical, and psychological aspects of the campaign. The diamond model for influence operations analysis consists of 5 components: 4 corners and a core element. The 4 corners are divided into 2 axes: influencer and audience on the socio-political axis, capabilities and infrastructure on the technical axis. Narrative makes up the core of the diamond.

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dni-ism : A subset of Information Security Marking Metadata ISM as required by Executive Order (EO) 13526. As described by DNI.gov as Data Encoding Specifications for Information Security Marking Metadata in Controlled Vocabulary Enumeration Values for ISM

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domain-abuse : Domain Name Abuse - taxonomy to tag domain names used for cybercrime.

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doping-substances : This taxonomy aims to list doping substances

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drugs : A taxonomy based on the superclass and class of drugs. Based on https://www.drugbank.ca/releases/latest

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economical-impact : Economical impact is a taxonomy to describe the financial impact as positive or negative gain to the tagged information (e.g. data exfiltration loss, a positive gain for an adversary).

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ecsirt : Incident Classification by the ecsirt.net version mkVI of 31 March 2015 enriched with IntelMQ taxonomy-type mapping.

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enisa : The present threat taxonomy is an initial version that has been developed on the basis of available ENISA material. This material has been used as an ENISA-internal structuring aid for information collection and threat consolidation purposes. It emerged in the time period 2012-2015.

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estimative-language : Estimative language to describe quality and credibility of underlying sources, data, and methodologies based Intelligence Community Directive 203 (ICD 203) and JP 2-0, Joint Intelligence

+

eu-marketop-and-publicadmin : Market operators and public administrations that must comply to some notifications requirements under EU NIS directive

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eu-nis-sector-and-subsectors : Sectors, subsectors, and digital services as identified by the NIS Directive

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euci : EU classified information (EUCI) means any information or material designated by a EU security classification, the unauthorised disclosure of which could cause varying degrees of prejudice to the interests of the European Union or of one or more of the Member States.

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europol-event : This taxonomy was designed to describe the type of events

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europol-incident : This taxonomy was designed to describe the type of incidents by class.

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event-assessment : A series of assessment predicates describing the event assessment performed to make judgement(s) under a certain level of uncertainty.

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event-classification : Classification of events as seen in tools such as RT/IR, MISP and other

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exercise : Exercise is a taxonomy to describe if the information is part of one or more cyber or crisis exercise.

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extended-event : Reasons why an event has been extended. This taxonomy must be used on the extended event. The competitive analysis aspect is from Psychology of Intelligence Analysis by Richard J. Heuer, Jr. ref:http://www.foo.be/docs/intelligence/PsychofIntelNew.pdf

+

failure-mode-in-machine-learning : The purpose of this taxonomy is to jointly tabulate both the of these failure modes in a single place. Intentional failures wherein the failure is caused by an active adversary attempting to subvert the system to attain her goals – either to misclassify the result, infer private training data, or to steal the underlying algorithm. Unintentional failures wherein the failure is because an ML system produces a formally correct but completely unsafe outcome.

+

false-positive : This taxonomy aims to ballpark the expected amount of false positives.

+

file-type : List of known file types.

+

financial : Financial taxonomy to describe financial services, infrastructure and financial scope.

+

flesch-reading-ease : Flesch Reading Ease is a revised system for determining the comprehension difficulty of written material. The scoring of the flesh score can have a maximum of 121.22 and there is no limit on how low a score can be (negative score are valid).

+

fpf : The Future of Privacy Forum (FPF) visual guide to practical de-identification taxonomy is used to evaluate the degree of identifiability of personal data and the types of pseudonymous data, de-identified data and anonymous data. The work of FPF is licensed under a creative commons attribution 4.0 international license.

+

fr-classif : French gov information classification system

+

gdpr : Taxonomy related to the REGULATION (EU) 2016/679 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation)

+

gea-nz-activities : Information needed to track or monitor moments, periods or events that occur over time. This type of information is focused on occurrences that must be tracked for business reasons or represent a specific point in the evolution of ‘The Business’.

+

gea-nz-entities : Information relating to instances of entities or things.

+

gea-nz-motivators : Information relating to authority or governance.

+

gsma-attack-category : Taxonomy used by GSMA for their information sharing program with telco describing the attack categories

+

gsma-fraud : Taxonomy used by GSMA for their information sharing program with telco describing the various aspects of fraud

+

gsma-network-technology : Taxonomy used by GSMA for their information sharing program with telco describing the types of infrastructure. WiP

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honeypot-basic : Updated (CIRCL, Seamus Dowling and EURECOM) from Christian Seifert, Ian Welch, Peter Komisarczuk, ‘Taxonomy of Honeypots’, Technical Report CS-TR-06/12, VICTORIA UNIVERSITY OF WELLINGTON, School of Mathematical and Computing Sciences, June 2006, http://www.mcs.vuw.ac.nz/comp/Publications/archive/CS-TR-06/CS-TR-06-12.pdf

+

ics : FIRST.ORG CTI SIG - MISP Proposal for ICS/OT Threat Attribution (IOC) Project

+

iep : Forum of Incident Response and Security Teams (FIRST) Information Exchange Policy (IEP) framework

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iep2-policy : Forum of Incident Response and Security Teams (FIRST) Information Exchange Policy (IEP) v2.0 Policy

+

iep2-reference : Forum of Incident Response and Security Teams (FIRST) Information Exchange Policy (IEP) v2.0 Reference

+

ifx-vetting : The IFX taxonomy is used to categorise information (MISP events and attributes) to aid in the intelligence vetting process

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incident-disposition : How an incident is classified in its process to be resolved. The taxonomy is inspired from NASA Incident Response and Management Handbook. https://www.nasa.gov/pdf/589502main_ITS-HBK-2810.09-02%20%5bNASA%20Information%20Security%20Incident%20Management%5d.pdf#page=9

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infoleak : A taxonomy describing information leaks and especially information classified as being potentially leaked. The taxonomy is based on the work by CIRCL on the AIL framework. The taxonomy aim is to be used at large to improve classification of leaked information.

+

information-origin : Taxonomy for tagging information by its origin: human-generated or AI-generated.

+

information-security-data-source : Taxonomy to classify the information security data sources.

+

information-security-indicators : A full set of operational indicators for organizations to use to benchmark their security posture.

+

interactive-cyber-training-audience : Describes the target of cyber training and education.

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interactive-cyber-training-technical-setup : The technical setup consists of environment structure, deployment, and orchestration.

+

interactive-cyber-training-training-environment : The training environment details the environment around the training, consisting of training type and scenario.

+

interactive-cyber-training-training-setup : The training setup further describes the training itself with the scoring, roles, the training mode as well as the customization level.

+

interception-method : The interception method used to intercept traffic.

+

ioc : An IOC classification to facilitate automation of malicious and non malicious artifacts

+

iot : Internet of Things taxonomy, based on IOT UK report https://iotuk.org.uk/wp-content/uploads/2017/01/IOT-Taxonomy-Report.pdf

+

kill-chain : The Cyber Kill Chain, a phase-based model developed by Lockheed Martin, aims to help categorise and identify the stage of an attack.

+

maec-delivery-vectors : Vectors used to deliver malware based on MAEC 5.0

+

maec-malware-behavior : Malware behaviours based on MAEC 5.0

+

maec-malware-capabilities : Malware Capabilities based on MAEC 5.0

+

maec-malware-obfuscation-methods : Obfuscation methods used by malware based on MAEC 5.0

+

malware_classification : Classification based on different categories. Based on https://www.sans.org/reading-room/whitepapers/incident/malware-101-viruses-32848

+

misinformation-website-label : classification for the identification of type of misinformation among websites. Source:False, Misleading, Clickbait-y, and/or Satirical News Sources by Melissa Zimdars 2019

+

misp : MISP taxonomy to infer with MISP behavior or operation.

+

misp-workflow : MISP workflow taxonomy to support result of workflow execution.

+

monarc-threat : MONARC Threats Taxonomy

+

ms-caro-malware : Malware Type and Platform classification based on Microsoft's implementation of the Computer Antivirus Research Organization (CARO) Naming Scheme and Malware Terminology. Based on https://www.microsoft.com/en-us/security/portal/mmpc/shared/malwarenaming.aspx, https://www.microsoft.com/security/portal/mmpc/shared/glossary.aspx, https://www.microsoft.com/security/portal/mmpc/shared/objectivecriteria.aspx, and http://www.caro.org/definitions/index.html. Malware families are extracted from Microsoft SIRs since 2008 based on https://www.microsoft.com/security/sir/archive/default.aspx and https://www.microsoft.com/en-us/security/portal/threat/threats.aspx. Note that SIRs do NOT include all Microsoft malware families.

+

ms-caro-malware-full : Malware Type and Platform classification based on Microsoft's implementation of the Computer Antivirus Research Organization (CARO) Naming Scheme and Malware Terminology. Based on https://www.microsoft.com/en-us/security/portal/mmpc/shared/malwarenaming.aspx, https://www.microsoft.com/security/portal/mmpc/shared/glossary.aspx, https://www.microsoft.com/security/portal/mmpc/shared/objectivecriteria.aspx, and http://www.caro.org/definitions/index.html. Malware families are extracted from Microsoft SIRs since 2008 based on https://www.microsoft.com/security/sir/archive/default.aspx and https://www.microsoft.com/en-us/security/portal/threat/threats.aspx. Note that SIRs do NOT include all Microsoft malware families.

+

mwdb : Malware Database (mwdb) Taxonomy - Tags used across the platform

+

nato : NATO classification markings.

+

nis : The taxonomy is meant for large scale cybersecurity incidents, as mentioned in the Commission Recommendation of 13 September 2017, also known as the blueprint. It has two core parts: The nature of the incident, i.e. the underlying cause, that triggered the incident, and the impact of the incident, i.e. the impact on services, in which sector(s) of economy and society.

+

nis2 : The taxonomy is meant for large scale cybersecurity incidents, as mentioned in the Commission Recommendation of 13 May 2022, also known as the provisional agreement. It has two core parts: The nature of the incident, i.e. the underlying cause, that triggered the incident, and the impact of the incident, i.e. the impact on services, in which sector(s) of economy and society.

+

open_threat : Open Threat Taxonomy v1.1 base on James Tarala of SANS http://www.auditscripts.com/resources/open_threat_taxonomy_v1.1a.pdf, https://files.sans.org/summit/Threat_Hunting_Incident_Response_Summit_2016/PDFs/Using-Open-Tools-to-Convert-Threat-Intelligence-into-Practical-Defenses-James-Tarala-SANS-Institute.pdf, https://www.youtube.com/watch?v=5rdGOOFC_yE, and https://www.rsaconference.com/writable/presentations/file_upload/str-r04_using-an-open-source-threat-model-for-prioritized-defense-final.pdf

+

organizational-cyber-harm : A taxonomy to classify organizational cyber harms based on categories like physical, economic, psychological, reputational, and social/societal impacts.

+

osint : Open Source Intelligence - Classification (MISP taxonomies)

+

pandemic : Pandemic

+

passivetotal : Tags from RiskIQ's PassiveTotal service

+

pentest : Penetration test (pentest) classification.

+

pfc : Le Protocole des feux de circulation (PFC) est basé sur le standard « Traffic Light Protocol (TLP) » conçu par le FIRST. Il a pour objectif d’informer sur les limites autorisées pour la diffusion des informations. Il est classé selon des codes de couleurs.

+

phishing : Taxonomy to classify phishing attacks including techniques, collection mechanisms and analysis status.

+

poison-taxonomy : Non-exhaustive taxonomy of natural poison

+

political-spectrum : A political spectrum is a system to characterize and classify different political positions in relation to one another.

+

priority-level : After an incident is scored, it is assigned a priority level. The six levels listed below are aligned with NCCIC, DHS, and the CISS to help provide a common lexicon when discussing incidents. This priority assignment drives NCCIC urgency, pre-approved incident response offerings, reporting requirements, and recommendations for leadership escalation. Generally, incident priority distribution should follow a similar pattern to the graph below. Based on https://www.cisa.gov/news-events/news/cisa-national-cyber-incident-scoring-system-nciss.

+

pyoti : PyOTI automated enrichment schemes for point in time classification of indicators.

+

ransomware : Ransomware is used to define ransomware types and the elements that compose them.

+

ransomware-roles : The seven roles seen in most ransomware incidents.

+

retention : Add a retenion time to events to automatically remove the IDS-flag on ip-dst or ip-src attributes. We calculate the time elapsed based on the date of the event. Supported time units are: d(ays), w(eeks), m(onths), y(ears). The numerical_value is just for sorting in the web-interface and is not used for calculations.

+

rsit : Reference Security Incident Classification Taxonomy

+

rt_event_status : Status of events used in Request Tracker.

+

runtime-packer : Runtime or software packer used to combine compressed or encrypted data with the decompression or decryption code. This code can add additional obfuscations mechanisms including polymorphic-packer or other obfuscation techniques. This taxonomy lists all the known or official packer used for legitimate use or for packing malicious binaries.

+

scrippsco2-fgc : Flags describing the sample

+

scrippsco2-fgi : Flags describing the sample for isotopic data (C14, O18)

+

scrippsco2-sampling-stations : Sampling stations of the Scripps CO2 Program

+

sentinel-threattype : Sentinel indicator threat types.

+

smart-airports-threats : Threat taxonomy in the scope of securing smart airports by ENISA. https://www.enisa.europa.eu/publications/securing-smart-airports

+

social-engineering-attack-vectors : Attack vectors used in social engineering as described in 'A Taxonomy of Social Engineering Defense Mechanisms' by Dalal Alharthi and others.

+

srbcert : SRB-CERT Taxonomy - Schemes of Classification in Incident Response and Detection

+

state-responsibility : A spectrum of state responsibility to more directly tie the goals of attribution to the needs of policymakers.

+

stealth_malware : Classification based on malware stealth techniques. Described in https://vxheaven.org/lib/pdf/Introducing%20Stealth%20Malware%20Taxonomy.pdf

+

stix-ttp : TTPs are representations of the behavior or modus operandi of cyber adversaries.

+

targeted-threat-index : The Targeted Threat Index is a metric for assigning an overall threat ranking score to email messages that deliver malware to a victim’s computer. The TTI metric was first introduced at SecTor 2013 by Seth Hardy as part of the talk “RATastrophe: Monitoring a Malware Menagerie” along with Katie Kleemola and Greg Wiseman.

+

thales_group : Thales Group Taxonomy - was designed with the aim of enabling desired sharing and preventing unwanted sharing between Thales Group security communities.

+

threatmatch : The ThreatMatch Sectors, Incident types, Malware types and Alert types are applicable for any ThreatMatch instances and should be used for all CIISI and TIBER Projects.

+

threats-to-dns : An overview of some of the known attacks related to DNS as described by Torabi, S., Boukhtouta, A., Assi, C., & Debbabi, M. (2018) in Detecting Internet Abuse by Analyzing Passive DNS Traffic: A Survey of Implemented Systems. IEEE Communications Surveys & Tutorials, 1–1. doi:10.1109/comst.2018.2849614

+

tlp : The Traffic Light Protocol (TLP) (v2.0) was created to facilitate greater sharing of potentially sensitive information and more effective collaboration. Information sharing happens from an information source, towards one or more recipients. TLP is a set of four standard labels (a fifth label is included in amber to limit the diffusion) used to indicate the sharing boundaries to be applied by the recipients. Only labels listed in this standard are considered valid by FIRST. This taxonomy includes additional labels for backward compatibility which are no more validated by FIRST SIG.

+

tor : Taxonomy to describe Tor network infrastructure

+

trust : The Indicator of Trust provides insight about data on what can be trusted and known as a good actor. Similar to a whitelist but on steroids, reusing features one would use with Indicators of Compromise, but to filter out what is known to be good.

+

type : Taxonomy to describe different types of intelligence gathering discipline which can be described the origin of intelligence.

+

unified-kill-chain : The Unified Kill Chain is a refinement to the Kill Chain.

+

unified-ransomware-kill-chain : The Unified Ransomware Kill Chain, a intelligence driven model developed by Oleg Skulkin, aims to track every single phase of a ransomware attack.

+

use-case-applicability : The Use Case Applicability categories reflect standard resolution categories, to clearly display alerting rule configuration problems.

+

veris : Vocabulary for Event Recording and Incident Sharing (VERIS)

+

vmray : VMRay taxonomies to map VMRay Thread Identifier scores and artifacts.

+

vocabulaire-des-probabilites-estimatives : Ce vocabulaire attribue des valeurs en pourcentage à certains énoncés de probabilité

+

vulnerability : A taxonomy for describing vulnerabilities (software, hardware, or social) on different scales or with additional available information.

+

workflow : Workflow support language is a common language to support intelligence analysts to perform their analysis on data and information.

@@ -2401,7 +1982,7 @@ A taxonomies array describes the taxonomy available with the description, name a

5. JSON Schema

-

The JSON Schema [JSON-SCHEMA] below defines the structure of the MISP taxonomy document +

The JSON Schema [JSON-SCHEMA] below defines the structure of the MISP taxonomy document as literally described before. The JSON Schema is used validating a MISP taxonomy. The validation is a MUST if the taxonomy is included in the MISP taxonomies directory.

@@ -2541,6 +2122,7 @@ is a MUST if the taxonomy is included in the MISP taxonomies directory. "predicates" ] } +
@@ -2555,43 +2137,48 @@ of open standards in threat intelligence sharing. -

-7. Normative References +

+7. References

+
+

+7.1. Normative References +

[RFC2119]
-
+
Bradner, S., "Key words for use in RFCs to Indicate Requirement Levels", BCP 14, RFC 2119, DOI 10.17487/RFC2119, , <https://www.rfc-editor.org/info/rfc2119>.
[RFC8259]
-
+
Bray, T., Ed., "The JavaScript Object Notation (JSON) Data Interchange Format", STD 90, RFC 8259, DOI 10.17487/RFC8259, , <https://www.rfc-editor.org/info/rfc8259>.
-
-

-8. Informative References -

+
+

+7.2. Informative References +

[JSON-SCHEMA]
-
+
Wright, A., "JSON Schema: A Media Type for Describing JSON Documents", , <https://tools.ietf.org/html/draft-wright-json-schema>.
[MISP-P]
-
-Community, M., "MISP Project - Malware Information Sharing Platform and Threat Sharing", <https://github.com/MISP>.
+
+Community, M., "MISP Project - Open Source Threat Intelligence Platform and Open Standards For Threat Information Sharing", <https://github.com/MISP>.
[MISP-T]
-
+
Community, M., "MISP Taxonomies - shared and common vocabularies of tags", <https://github.com/MISP/misp-taxonomies>.
[machine-tags]
-
+
Cope, A. S., "Machine tags", , <https://www.flickr.com/groups/51035612836@N01/discuss/72157594497877875/>.
+

diff --git a/rfc/misp-standard-taxonomy-format.txt b/rfc/misp-standard-taxonomy-format.txt index cfb1c97..c306b4f 100644 --- a/rfc/misp-standard-taxonomy-format.txt +++ b/rfc/misp-standard-taxonomy-format.txt @@ -5,7 +5,7 @@ Network Working Group A. Dulaunoy Internet-Draft A. Iklody Intended status: Informational CIRCL -Expires: 26 June 2024 24 December 2023 +Expires: 3 July 2025 30 December 2024 MISP taxonomy format @@ -13,12 +13,12 @@ Expires: 26 June 2024 24 December 2023 Abstract - This document describes the MISP taxonomy format which describes a - simple JSON format to represent machine tags (also called triple - tags) vocabularies. A public directory of common vocabularies called - MISP taxonomies is available and relies on the MISP taxonomy format. - MISP taxonomies are used to classify cyber security events, threats, - suspicious events, or indicators. + This document outlines the MISP taxonomy format, a straightforward + JSON structure designed to represent machine tags (also known as + triple tags) vocabularies. A public directory, referred to as MISP + taxonomies, is available and leverages this format. These taxonomies + are used to classify cybersecurity events, threats, suspicious + activities, and indicators. Status of This Memo @@ -35,11 +35,11 @@ Status of This Memo time. It is inappropriate to use Internet-Drafts as reference material or to cite them other than as "work in progress." - This Internet-Draft will expire on 26 June 2024. + This Internet-Draft will expire on 3 July 2025. Copyright Notice - Copyright (c) 2023 IETF Trust and the persons identified as the + Copyright (c) 2024 IETF Trust and the persons identified as the document authors. All rights reserved. This document is subject to BCP 78 and the IETF Trust's Legal @@ -53,9 +53,9 @@ Copyright Notice -Dulaunoy & Iklody Expires 26 June 2024 [Page 1] +Dulaunoy & Iklody Expires 3 July 2025 [Page 1] -Internet-Draft MISP taxonomy format December 2023 +Internet-Draft MISP taxonomy format December 2024 Table of Contents @@ -75,24 +75,26 @@ Table of Contents 4. Sample Taxonomy in MISP taxonomy format . . . . . . . . . . . 7 4.1. Admiralty Scale Taxonomy . . . . . . . . . . . . . . . . 7 4.2. Open Source Intelligence - Classification . . . . . . . . 9 - 4.3. Available taxonomies in the public directory . . . . . . 11 - 5. JSON Schema . . . . . . . . . . . . . . . . . . . . . . . . . 22 - 6. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 25 - 7. Normative References . . . . . . . . . . . . . . . . . . . . 25 - 8. Informative References . . . . . . . . . . . . . . . . . . . 25 - Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 26 + 4.3. Available taxonomies in the public repository . . . . . . 11 + 5. JSON Schema . . . . . . . . . . . . . . . . . . . . . . . . . 26 + 6. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 29 + 7. References . . . . . . . . . . . . . . . . . . . . . . . . . 29 + 7.1. Normative References . . . . . . . . . . . . . . . . . . 29 + 7.2. Informative References . . . . . . . . . . . . . . . . . 29 + Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 29 1. Introduction - Sharing threat information became a fundamental requirements on the - Internet, security and intelligence community at large. Threat + Sharing threat information has become a fundamental requirement in + the Internet security and intelligence community at large. This information can include indicators of compromise, malicious file - indicators, financial fraud indicators or even detailed information - about a threat actor. While sharing such indicators or information, - classification plays an important role to ensure adequate - distribution, understanding, validation or action of the shared - information. MISP taxonomies is a public repository of known - vocabularies that can be used in threat information sharing. + indicators, financial fraud indicators, or even detailed information + about a threat actor. Classification plays a crucial role while + sharing such indicators or information, ensuring adequate + distribution, understanding, validation, or action regarding the + shared information. The MISP taxonomies are a public repository of + known vocabularies that can be utilized in threat information + sharing. Machine tags were introduced in 2007 [machine-tags] to allow users to be more precise when tagging their pictures with geolocation. So a @@ -100,20 +102,24 @@ Table of Contents information to users and machines. Machine tags are also known as triple tags due to their format. + + + + + + + +Dulaunoy & Iklody Expires 3 July 2025 [Page 2] + +Internet-Draft MISP taxonomy format December 2024 + + In the MISP taxonomy context, machine tags help analysts to classify their cybersecurity events, indicators or threats. MISP taxonomies can be used for classification, filtering, triggering actions or visualisation depending on their use in threat intelligence platforms such as MISP [MISP-P]. - - - -Dulaunoy & Iklody Expires 26 June 2024 [Page 2] - -Internet-Draft MISP taxonomy format December 2023 - - 1.1. Conventions and Terminology The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", @@ -155,6 +161,15 @@ Internet-Draft MISP taxonomy format December 2023 event level only. An exclusive boolean property MAY be present and defines at namespace level if the predicates are mutually exclusive. + + + + +Dulaunoy & Iklody Expires 3 July 2025 [Page 3] + +Internet-Draft MISP taxonomy format December 2024 + + predicates defines all the predicates available in the namespace defined. predicates is represented as an array of JSON objects. predicates MUST be present and MUST at least content one element. @@ -162,14 +177,6 @@ Internet-Draft MISP taxonomy format December 2023 values defines all the values for each predicate in the namespace defined. values SHOULD be present. - - - -Dulaunoy & Iklody Expires 26 June 2024 [Page 3] - -Internet-Draft MISP taxonomy format December 2023 - - 2.2. predicates The predicates array contains one or more JSON objects which lists @@ -214,16 +221,9 @@ Internet-Draft MISP taxonomy format December 2023 - - - - - - - -Dulaunoy & Iklody Expires 26 June 2024 [Page 4] +Dulaunoy & Iklody Expires 3 July 2025 [Page 4] -Internet-Draft MISP taxonomy format December 2023 +Internet-Draft MISP taxonomy format December 2024 "predicates": [ @@ -277,9 +277,9 @@ Internet-Draft MISP taxonomy format December 2023 -Dulaunoy & Iklody Expires 26 June 2024 [Page 5] +Dulaunoy & Iklody Expires 3 July 2025 [Page 5] -Internet-Draft MISP taxonomy format December 2023 +Internet-Draft MISP taxonomy format December 2024 { @@ -333,9 +333,9 @@ Internet-Draft MISP taxonomy format December 2023 -Dulaunoy & Iklody Expires 26 June 2024 [Page 6] +Dulaunoy & Iklody Expires 3 July 2025 [Page 6] -Internet-Draft MISP taxonomy format December 2023 +Internet-Draft MISP taxonomy format December 2024 3.1. Sample Manifest @@ -389,9 +389,9 @@ Internet-Draft MISP taxonomy format December 2023 -Dulaunoy & Iklody Expires 26 June 2024 [Page 7] +Dulaunoy & Iklody Expires 3 July 2025 [Page 7] -Internet-Draft MISP taxonomy format December 2023 +Internet-Draft MISP taxonomy format December 2024 "value": "a", @@ -445,9 +445,9 @@ Internet-Draft MISP taxonomy format December 2023 -Dulaunoy & Iklody Expires 26 June 2024 [Page 8] +Dulaunoy & Iklody Expires 3 July 2025 [Page 8] -Internet-Draft MISP taxonomy format December 2023 +Internet-Draft MISP taxonomy format December 2024 { @@ -501,9 +501,9 @@ Internet-Draft MISP taxonomy format December 2023 -Dulaunoy & Iklody Expires 26 June 2024 [Page 9] +Dulaunoy & Iklody Expires 3 July 2025 [Page 9] -Internet-Draft MISP taxonomy format December 2023 +Internet-Draft MISP taxonomy format December 2024 "predicate": "source-type" @@ -557,9 +557,9 @@ Internet-Draft MISP taxonomy format December 2023 -Dulaunoy & Iklody Expires 26 June 2024 [Page 10] +Dulaunoy & Iklody Expires 3 July 2025 [Page 10] -Internet-Draft MISP taxonomy format December 2023 +Internet-Draft MISP taxonomy format December 2024 "description": "30% Probably not" @@ -600,599 +600,807 @@ Internet-Draft MISP taxonomy format December 2023 ] } -4.3. Available taxonomies in the public directory +4.3. Available taxonomies in the public repository - The public directory of MISP taxonomies [MISP-T] contains a variety - of taxonomy in various fields such as: + The public directory of MISP taxonomies [MISP-T] contains more than + 150 taxonomies spanning various fields, including: - CERT-XLM: CERT-XLM Security Incident Classification. - DFRLab-dichotomies-of-disinformation: DFRLab Dichotomies of - Disinformation. - DML: The Detection Maturity Level (DML) model is a capability + *CERT-XLM* : CERT-XLM Security Incident Classification. + + *DFRLab-dichotomies-of-disinformation* : DFRLab Dichotomies of + Disinformation. -Dulaunoy & Iklody Expires 26 June 2024 [Page 11] +Dulaunoy & Iklody Expires 3 July 2025 [Page 11] -Internet-Draft MISP taxonomy format December 2023 +Internet-Draft MISP taxonomy format December 2024 - maturity model for referencing ones maturity in detecting cyber - attacks. It's designed for organizations who perform intel-driven - detection and response and who put an emphasis on having a mature - detection program. - GrayZone: Gray Zone of Active defense includes all elements which - lay between reactive defense elements and offensive operations. - It does fill the gray spot between them. Taxo may be used for - active defense planning or modeling. - PAP: The Permissible Actions Protocol - or short: PAP - was designed - to indicate how the received information can be used. - access-method: The access method used to remotely access a system. - accessnow: Access Now classification to classify an issue (such as - security, human rights, youth rights). - action-taken: Action taken in the case of a security incident (CSIRT - perspective). - admiralty-scale: The Admiralty Scale or Ranking (also called the - NATO System) is used to rank the reliability of a source and the - credibility of an information. Reference based on FM 2-22.3 (FM - 34-52) HUMAN INTELLIGENCE COLLECTOR OPERATIONS and NATO documents. - adversary: An overview and description of the adversary - infrastructure - ais-marking: The AIS Marking Schema implementation is maintained by - the National Cybersecurity and Communication Integration Center - (NCCIC) of the U.S. Department of Homeland Security (DHS) - analyst-assessment: A series of assessment predicates describing the - analyst capabilities to perform analysis. These assessment can be - assigned by the analyst him/herself or by another party evaluating - the analyst. - approved-category-of-action: A pre-approved category of action for - indicators being shared with partners (MIMIC). - artificial-satellites: This taxonomy was designed to describe - artificial satellites - aviation: A taxonomy describing security threats or incidents - against the aviation sector. - binary-class: Custom taxonomy for types of binary file. - cccs: Internal taxonomy for CCCS. - circl: CIRCL Taxonomy - Schemes of Classification in Incident - Response and Detection. - cnsd: La presente taxonomia es la primera versión disponible - para el Centro Nacional de Seguridad Digital del Perú. - coa: Course of action taken within organization to discover, detect, - deny, disrupt, degrade, deceive and/or destroy an attack. - collaborative-intelligence: Collaborative intelligence support - language is a common language to support analysts to perform their - analysis to get crowdsourced support when using threat - intelligence sharing platform like MISP. The objective of this - language is to advance collaborative analysis and to share earlier - than later. + *DML* : The Detection Maturity Level (DML) model is a capability + maturity model for referencing ones maturity in detecting cyber + attacks. It's designed for organizations who perform intel-driven + detection and response and who put an emphasis on having a mature + detection program. + + *GrayZone* : Gray Zone of Active defense includes all elements which + lay between reactive defense elements and offensive operations. It + does fill the gray spot between them. Taxo may be used for active + defense planning or modeling. + + *PAP* : The Permissible Actions Protocol - or short: PAP - was + designed to indicate how the received information can be used. + + *access-method* : The access method used to remotely access a system. + + *accessnow* : Access Now classification to classify an issue (such as + security, human rights, youth rights). + + *acs-marking* : The Access Control Specification (ACS) marking type + defines the object types required to implement automated access + control systems based on the relevant policies governing sharing + between participants. + + *action-taken* : Action taken in the case of a security incident + (CSIRT perspective). + + *admiralty-scale* : The Admiralty Scale or Ranking (also called the + NATO System) is used to rank the reliability of a source and the + credibility of an information. Reference based on FM 2-22.3 (FM + 34-52) HUMAN INTELLIGENCE COLLECTOR OPERATIONS and NATO documents. + + *adversary* : An overview and description of the adversary + infrastructure + + *ais-marking* : The AIS Marking Schema implementation is maintained + by the National Cybersecurity and Communication Integration Center + (NCCIC) of the U.S. Department of Homeland Security (DHS) + + *analyst-assessment* : A series of assessment predicates describing + the analyst capabilities to perform analysis. These assessment can + be assigned by the analyst him/herself or by another party evaluating + the analyst. + + *approved-category-of-action* : A pre-approved category of action for + indicators being shared with partners (MIMIC). -Dulaunoy & Iklody Expires 26 June 2024 [Page 12] + + +Dulaunoy & Iklody Expires 3 July 2025 [Page 12] -Internet-Draft MISP taxonomy format December 2023 +Internet-Draft MISP taxonomy format December 2024 - common-taxonomy: Common Taxonomy for Law enforcement and CSIRTs - copine-scale: The COPINE Scale is a rating system created in Ireland - and used in the United Kingdom to categorise the severity of - images of child sex abuse. The scale was developed by staff at - the COPINE (Combating Paedophile Information Networks in Europe) - project. The COPINE Project was founded in 1997, and is based in - the Department of Applied Psychology, University College Cork, - Ireland. - course-of-action: A Course Of Action analysis considers six - potential courses of action for the development of a cyber - security capability. - crowdsec: Crowdsec IP address classifications and behaviors - taxonomy. - cryptocurrency-threat: Threats targetting cryptocurrency, based on - CipherTrace report. - csirt-americas: Taxonomía CSIRT Américas. - csirt_case_classification: It is critical that the CSIRT provide - consistent and timely response to the customer, and that sensitive - information is handled appropriately. This document provides the - guidelines needed for CSIRT Incident Managers (IM) to classify the - case category, criticality level, and sensitivity level for each - CSIRT case. This information will be entered into the Incident - Tracking System (ITS) when a case is created. Consistent case - classification is required for the CSIRT to provide accurate - reporting to management on a regular basis. In addition, the - classifications will provide CSIRT IM's with proper case handling - procedures and will form the basis of SLA's between the CSIRT and - other Company departments. - cssa: The CSSA agreed sharing taxonomy. - cti: Cyber Threat Intelligence cycle to control workflow state of - your process. - current-event: Current events - Schemes of Classification in - Incident Response and Detection - cyber-threat-framework: Cyber Threat Framework was developed by the - US Government to enable consistent characterization and - categorization of cyber threat events, and to identify trends or - changes in the activities of cyber adversaries. - https://www.dni.gov/index.php/cyber-threat-framework - (https://www.dni.gov/index.php/cyber-threat-framework) - cycat: Taxonomy used by CyCAT, the Universal Cybersecurity Resource - Catalogue, to categorize the namespaces it supports and uses. - cytomic-orion: Taxonomy to describe desired actions for Cytomic - Orion - dark-web: Criminal motivation and content detection the dark web: A - categorisation model for law enforcement. ref: Janis Dalins, - Campbell Wilson, Mark Carman. Taxonomy updated by MISP Project - and extended by the JRC (Joint Research Centre) of the European - Commission. + *artificial-satellites* : This taxonomy was designed to describe + artificial satellites + + *aviation* : A taxonomy describing security threats or incidents + against the aviation sector. + + *binary-class* : Custom taxonomy for types of binary file. + + *cccs* : Internal taxonomy for CCCS. + + *circl* : CIRCL Taxonomy - Schemes of Classification in Incident + Response and Detection. + + *cnsd* : La presente taxonomia es la primera versión disponible para + el Centro Nacional de Seguridad Digital del Perú. + + *coa* : Course of action taken within organization to discover, + detect, deny, disrupt, degrade, deceive and/or destroy an attack. + + *collaborative-intelligence* : Collaborative intelligence support + language is a common language to support analysts to perform their + analysis to get crowdsourced support when using threat intelligence + sharing platform like MISP. The objective of this language is to + advance collaborative analysis and to share earlier than later. + + *common-taxonomy* : Common Taxonomy for Law enforcement and CSIRTs + + *copine-scale* : The COPINE Scale is a rating system created in + Ireland and used in the United Kingdom to categorise the severity of + images of child sex abuse. The scale was developed by staff at the + COPINE (Combating Paedophile Information Networks in Europe) project. + The COPINE Project was founded in 1997, and is based in the + Department of Applied Psychology, University College Cork, Ireland. + + *course-of-action* : A Course Of Action analysis considers six + potential courses of action for the development of a cyber security + capability. + + *crowdsec* : Crowdsec IP address classifications and behaviors + taxonomy. + + *cryptocurrency-threat* : Threats targetting cryptocurrency, based on + CipherTrace report. + + *csirt-americas* : Taxonomía CSIRT Américas. -Dulaunoy & Iklody Expires 26 June 2024 [Page 13] + + + +Dulaunoy & Iklody Expires 3 July 2025 [Page 13] -Internet-Draft MISP taxonomy format December 2023 +Internet-Draft MISP taxonomy format December 2024 - data-classification: Data classification for data potentially at - risk of exfiltration based on table 2.1 of Solving Cyber Risk - book. - dcso-sharing: Taxonomy defined in the DCSO MISP Event Guide. It - provides guidance for the creation and consumption of MISP events - in a way that minimises the extra effort for the sending party, - while enhancing the usefulness for receiving parties. - ddos: Distributed Denial of Service - or short: DDoS - taxonomy - supports the description of Denial of Service attacks and - especially the types they belong too. - de-vs: German (DE) Government classification markings (VS). - death-possibilities: Taxonomy of Death Possibilities - deception: Deception is an important component of information - operations, valuable for both offense and defense. - dga: A taxonomy to describe domain-generation algorithms often - called DGA. Ref: A Comprehensive Measurement Study of Domain - Generating Malware Daniel Plohmann and others. - dhs-ciip-sectors: DHS critical sectors as in https://www.dhs.gov/ - critical-infrastructure-sectors (https://www.dhs.gov/critical- - infrastructure-sectors) - diamond-model: The Diamond Model for Intrusion Analysis establishes - the basic atomic element of any intrusion activity, the event, - composed of four core features: adversary, infrastructure, - capability, and victim. - diamond-model-for-influence-operations: The diamond model for - influence operations analysis is a framework that leads analysts - and researchers toward a comprehensive understanding of a malign - influence campaign by addressing the socio-political, technical, - and psychological aspects of the campaign. The diamond model for - influence operations analysis consists of 5 components: 4 corners - and a core element. The 4 corners are divided into 2 axes: - influencer and audience on the socio-political axis, capabilities - and infrastructure on the technical axis. Narrative makes up the - core of the diamond. - dni-ism: A subset of Information Security Marking Metadata ISM as - required by Executive Order (EO) 13526. As described by DNI.gov - as Data Encoding Specifications for Information Security Marking - Metadata in Controlled Vocabulary Enumeration Values for ISM - domain-abuse: Domain Name Abuse - taxonomy to tag domain names used - for cybercrime. - doping-substances: This taxonomy aims to list doping substances - drugs: A taxonomy based on the superclass and class of drugs. Based - on https://www.drugbank.ca/releases/latest - (https://www.drugbank.ca/releases/latest) - economical-impact: Economical impact is a taxonomy to describe the - financial impact as positive or negative gain to the tagged - information (e.g. data exfiltration loss, a positive gain for an - adversary). + *csirt_case_classification* : It is critical that the CSIRT provide + consistent and timely response to the customer, and that sensitive + information is handled appropriately. This document provides the + guidelines needed for CSIRT Incident Managers (IM) to classify the + case category, criticality level, and sensitivity level for each + CSIRT case. This information will be entered into the Incident + Tracking System (ITS) when a case is created. Consistent case + classification is required for the CSIRT to provide accurate + reporting to management on a regular basis. In addition, the + classifications will provide CSIRT IM’s with proper case handling + procedures and will form the basis of SLA’s between the CSIRT and + other Company departments. + + *cssa* : The CSSA agreed sharing taxonomy. + + *cti* : Cyber Threat Intelligence cycle to control workflow state of + your process. + + *current-event* : Current events - Schemes of Classification in + Incident Response and Detection + + *cyber-threat-framework* : Cyber Threat Framework was developed by + the US Government to enable consistent characterization and + categorization of cyber threat events, and to identify trends or + changes in the activities of cyber adversaries. + https://www.dni.gov/index.php/cyber-threat-framework + (https://www.dni.gov/index.php/cyber-threat-framework) + + *cycat* : Taxonomy used by CyCAT, the Universal Cybersecurity + Resource Catalogue, to categorize the namespaces it supports and + uses. + + *cytomic-orion* : Taxonomy to describe desired actions for Cytomic + Orion + + *dark-web* : Criminal motivation and content detection the dark web: + A categorisation model for law enforcement. ref: Janis Dalins, + Campbell Wilson, Mark Carman. Taxonomy updated by MISP Project and + extended by the JRC (Joint Research Centre) of the European + Commission. + + *data-classification* : Data classification for data potentially at + risk of exfiltration based on table 2.1 of Solving Cyber Risk book. + + *dcso-sharing* : Taxonomy defined in the DCSO MISP Event Guide. It + provides guidance for the creation and consumption of MISP events in + a way that minimises the extra effort for the sending party, while + enhancing the usefulness for receiving parties. -Dulaunoy & Iklody Expires 26 June 2024 [Page 14] +Dulaunoy & Iklody Expires 3 July 2025 [Page 14] -Internet-Draft MISP taxonomy format December 2023 +Internet-Draft MISP taxonomy format December 2024 - ecsirt: Incident Classification by the ecsirt.net version mkVI of 31 - March 2015 enriched with IntelMQ taxonomy-type mapping. - enisa: The present threat taxonomy is an initial version that has - been developed on the basis of available ENISA material. This - material has been used as an ENISA-internal structuring aid for - information collection and threat consolidation purposes. It - emerged in the time period 2012-2015. - estimative-language: Estimative language to describe quality and - credibility of underlying sources, data, and methodologies based - Intelligence Community Directive 203 (ICD 203) and JP 2-0, Joint - Intelligence - eu-marketop-and-publicadmin: Market operators and public - administrations that must comply to some notifications - requirements under EU NIS directive - eu-nis-sector-and-subsectors: Sectors, subsectors, and digital - services as identified by the NIS Directive - euci: EU classified information (EUCI) means any information or - material designated by a EU security classification, the - unauthorised disclosure of which could cause varying degrees of - prejudice to the interests of the European Union or of one or more - of the Member States. - europol-event: This taxonomy was designed to describe the type of - events - europol-incident: This taxonomy was designed to describe the type of - incidents by class. - event-assessment: A series of assessment predicates describing the - event assessment performed to make judgement(s) under a certain - level of uncertainty. - event-classification: Classification of events as seen in tools such - as RT/IR, MISP and other - exercise: Exercise is a taxonomy to describe if the information is - part of one or more cyber or crisis exercise. - extended-event: Reasons why an event has been extended. This - taxonomy must be used on the extended event. The competitive - analysis aspect is from Psychology of Intelligence Analysis by - Richard J. Heuer, Jr. ref:http://www.foo.be/docs/intelligence/ - PsychofIntelNew.pdf (http://www.foo.be/docs/intelligence/ - PsychofIntelNew.pdf) - failure-mode-in-machine-learning: The purpose of this taxonomy is to - jointly tabulate both the of these failure modes in a single - place. Intentional failures wherein the failure is caused by an - active adversary attempting to subvert the system to attain her - goals - either to misclassify the result, infer private training - data, or to steal the underlying algorithm. Unintentional - failures wherein the failure is because an ML system produces a - formally correct but completely unsafe outcome. - false-positive: This taxonomy aims to ballpark the expected amount - of false positives. + *ddos* : Distributed Denial of Service - or short: DDoS - taxonomy + supports the description of Denial of Service attacks and especially + the types they belong too. + + *de-vs* : German (DE) Government classification markings (VS). + + *death-possibilities* : Taxonomy of Death Possibilities + + *deception* : Deception is an important component of information + operations, valuable for both offense and defense. + + *detection-engineering* : Taxonomy related to detection engineering + techniques + + *dga* : A taxonomy to describe domain-generation algorithms often + called DGA. Ref: A Comprehensive Measurement Study of Domain + Generating Malware Daniel Plohmann and others. + + *dhs-ciip-sectors* : DHS critical sectors as in https://www.dhs.gov/ + critical-infrastructure-sectors (https://www.dhs.gov/critical- + infrastructure-sectors) + + *diamond-model* : The Diamond Model for Intrusion Analysis + establishes the basic atomic element of any intrusion activity, the + event, composed of four core features: adversary, infrastructure, + capability, and victim. + + *diamond-model-for-influence-operations* : The diamond model for + influence operations analysis is a framework that leads analysts and + researchers toward a comprehensive understanding of a malign + influence campaign by addressing the socio-political, technical, and + psychological aspects of the campaign. The diamond model for + influence operations analysis consists of 5 components: 4 corners and + a core element. The 4 corners are divided into 2 axes: influencer + and audience on the socio-political axis, capabilities and + infrastructure on the technical axis. Narrative makes up the core of + the diamond. + + *dni-ism* : A subset of Information Security Marking Metadata ISM as + required by Executive Order (EO) 13526. As described by DNI.gov as + Data Encoding Specifications for Information Security Marking + Metadata in Controlled Vocabulary Enumeration Values for ISM + + *domain-abuse* : Domain Name Abuse - taxonomy to tag domain names + used for cybercrime. + + *doping-substances* : This taxonomy aims to list doping substances -Dulaunoy & Iklody Expires 26 June 2024 [Page 15] + +Dulaunoy & Iklody Expires 3 July 2025 [Page 15] -Internet-Draft MISP taxonomy format December 2023 +Internet-Draft MISP taxonomy format December 2024 - file-type: List of known file types. - financial: Financial taxonomy to describe financial services, - infrastructure and financial scope. - flesch-reading-ease: Flesch Reading Ease is a revised system for - determining the comprehension difficulty of written material. The - scoring of the flesh score can have a maximum of 121.22 and there - is no limit on how low a score can be (negative score are valid). - fpf: The Future of Privacy Forum (FPF) visual guide to practical de- - identification (https://fpf.org/2016/04/25/a-visual-guide-to- - practical-data-de-identification/) taxonomy is used to evaluate - the degree of identifiability of personal data and the types of - pseudonymous data, de-identified data and anonymous data. The - work of FPF is licensed under a creative commons attribution 4.0 - international license. - fr-classif: French gov information classification system - gdpr: Taxonomy related to the REGULATION (EU) 2016/679 OF THE - EUROPEAN PARLIAMENT AND OF THE COUNCIL on the protection of - natural persons with regard to the processing of personal data and - on the free movement of such data, and repealing Directive 95/46/ - EC (General Data Protection Regulation) - gea-nz-activities: Information needed to track or monitor moments, - periods or events that occur over time. This type of information - is focused on occurrences that must be tracked for business - reasons or represent a specific point in the evolution of 'The - Business'. - gea-nz-entities: Information relating to instances of entities or - things. - gea-nz-motivators: Information relating to authority or governance. - gsma-attack-category: Taxonomy used by GSMA for their information - sharing program with telco describing the attack categories - gsma-fraud: Taxonomy used by GSMA for their information sharing - program with telco describing the various aspects of fraud - gsma-network-technology: Taxonomy used by GSMA for their information - sharing program with telco describing the types of infrastructure. - WiP - honeypot-basic: Updated (CIRCL, Seamus Dowling and EURECOM) from - Christian Seifert, Ian Welch, Peter Komisarczuk, 'Taxonomy of - Honeypots', Technical Report CS-TR-06/12, VICTORIA UNIVERSITY OF - WELLINGTON, School of Mathematical and Computing Sciences, June - 2006, http://www.mcs.vuw.ac.nz/comp/Publications/archive/CS-TR-06/ - CS-TR-06-12.pdf - (http://www.mcs.vuw.ac.nz/comp/Publications/archive/CS-TR-06/CS- - TR-06-12.pdf) - ics: FIRST.ORG CTI SIG - MISP Proposal for ICS/OT Threat Attribution - (IOC) Project - iep: Forum of Incident Response and Security Teams (FIRST) - Information Exchange Policy (IEP) framework - iep2-policy: Forum of Incident Response and Security Teams (FIRST) + *drugs* : A taxonomy based on the superclass and class of drugs. + Based on https://www.drugbank.ca/releases/latest + (https://www.drugbank.ca/releases/latest) + + *economical-impact* : Economical impact is a taxonomy to describe the + financial impact as positive or negative gain to the tagged + information (e.g. data exfiltration loss, a positive gain for an + adversary). + + *ecsirt* : Incident Classification by the ecsirt.net version mkVI of + 31 March 2015 enriched with IntelMQ taxonomy-type mapping. + + *enisa* : The present threat taxonomy is an initial version that has + been developed on the basis of available ENISA material. This + material has been used as an ENISA-internal structuring aid for + information collection and threat consolidation purposes. It emerged + in the time period 2012-2015. + + *estimative-language* : Estimative language to describe quality and + credibility of underlying sources, data, and methodologies based + Intelligence Community Directive 203 (ICD 203) and JP 2-0, Joint + Intelligence + + *eu-marketop-and-publicadmin* : Market operators and public + administrations that must comply to some notifications requirements + under EU NIS directive + + *eu-nis-sector-and-subsectors* : Sectors, subsectors, and digital + services as identified by the NIS Directive + + *euci* : EU classified information (EUCI) means any information or + material designated by a EU security classification, the unauthorised + disclosure of which could cause varying degrees of prejudice to the + interests of the European Union or of one or more of the Member + States. + + *europol-event* : This taxonomy was designed to describe the type of + events + + *europol-incident* : This taxonomy was designed to describe the type + of incidents by class. + + *event-assessment* : A series of assessment predicates describing the + event assessment performed to make judgement(s) under a certain level + of uncertainty. + + *event-classification* : Classification of events as seen in tools + such as RT/IR, MISP and other -Dulaunoy & Iklody Expires 26 June 2024 [Page 16] +Dulaunoy & Iklody Expires 3 July 2025 [Page 16] -Internet-Draft MISP taxonomy format December 2023 +Internet-Draft MISP taxonomy format December 2024 - Information Exchange Policy (IEP) v2.0 Policy - iep2-reference: Forum of Incident Response and Security Teams - (FIRST) Information Exchange Policy (IEP) v2.0 Reference - ifx-vetting: The IFX taxonomy is used to categorise information - (MISP events and attributes) to aid in the intelligence vetting - process - incident-disposition: How an incident is classified in its process - to be resolved. The taxonomy is inspired from NASA Incident - Response and Management Handbook. https://www.nasa.gov/ - pdf/589502main_ITS-HBK-2810.09-02%20%5bNASA%20Information%20Securi - ty%20Incident%20Management%5d.pdf#page=9 (https://www.nasa.gov/ - pdf/589502main_ITS-HBK-2810.09-02%20%5bNASA%20Information%20Securi - ty%20Incident%20Management%5d.pdf#page=9) - infoleak: A taxonomy describing information leaks and especially - information classified as being potentially leaked. The taxonomy - is based on the work by CIRCL on the AIL framework. The taxonomy - aim is to be used at large to improve classification of leaked - information. - information-origin: Taxonomy for tagging information by its origin: - human-generated or AI-generated. - information-security-data-source: Taxonomy to classify the - information security data sources. - information-security-indicators: A full set of operational - indicators for organizations to use to benchmark their security - posture. - interactive-cyber-training-audience: Describes the target of cyber - training and education. - interactive-cyber-training-technical-setup: The technical setup - consists of environment structure, deployment, and orchestration. - interactive-cyber-training-training-environment: The training - environment details the environment around the training, - consisting of training type and scenario. - interactive-cyber-training-training-setup: The training setup - further describes the training itself with the scoring, roles, the - training mode as well as the customization level. - interception-method: The interception method used to intercept - traffic. - ioc: An IOC classification to facilitate automation of malicious and - non malicious artifacts - iot: Internet of Things taxonomy, based on IOT UK report - https://iotuk.org.uk/wp-content/uploads/2017/01/IOT-Taxonomy- - Report.pdf (https://iotuk.org.uk/wp-content/uploads/2017/01/IOT- - Taxonomy-Report.pdf) - kill-chain: The Cyber Kill Chain, a phase-based model developed by - Lockheed Martin, aims to help categorise and identify the stage of - an attack. - maec-delivery-vectors: Vectors used to deliver malware based on MAEC - 5.0 + *exercise* : Exercise is a taxonomy to describe if the information is + part of one or more cyber or crisis exercise. + + *extended-event* : Reasons why an event has been extended. This + taxonomy must be used on the extended event. The competitive + analysis aspect is from Psychology of Intelligence Analysis by + Richard J. Heuer, Jr. ref:http://www.foo.be/docs/intelligence/ + PsychofIntelNew.pdf (http://www.foo.be/docs/intelligence/ + PsychofIntelNew.pdf) + + *failure-mode-in-machine-learning* : The purpose of this taxonomy is + to jointly tabulate both the of these failure modes in a single + place. Intentional failures wherein the failure is caused by an + active adversary attempting to subvert the system to attain her goals + – either to misclassify the result, infer private training data, or + to steal the underlying algorithm. Unintentional failures wherein + the failure is because an ML system produces a formally correct but + completely unsafe outcome. + + *false-positive* : This taxonomy aims to ballpark the expected amount + of false positives. + + *file-type* : List of known file types. + + *financial* : Financial taxonomy to describe financial services, + infrastructure and financial scope. + + *flesch-reading-ease* : Flesch Reading Ease is a revised system for + determining the comprehension difficulty of written material. The + scoring of the flesh score can have a maximum of 121.22 and there is + no limit on how low a score can be (negative score are valid). + + *fpf* : The Future of Privacy Forum (FPF) visual guide to practical + de-identification (https://fpf.org/2016/04/25/a-visual-guide-to- + practical-data-de-identification/) taxonomy is used to evaluate the + degree of identifiability of personal data and the types of + pseudonymous data, de-identified data and anonymous data. The work + of FPF is licensed under a creative commons attribution 4.0 + international license. + + *fr-classif* : French gov information classification system + + *gdpr* : Taxonomy related to the REGULATION (EU) 2016/679 OF THE + EUROPEAN PARLIAMENT AND OF THE COUNCIL on the protection of natural + persons with regard to the processing of personal data and on the + free movement of such data, and repealing Directive 95/46/EC (General + Data Protection Regulation) -Dulaunoy & Iklody Expires 26 June 2024 [Page 17] + +Dulaunoy & Iklody Expires 3 July 2025 [Page 17] -Internet-Draft MISP taxonomy format December 2023 +Internet-Draft MISP taxonomy format December 2024 - maec-malware-behavior: Malware behaviours based on MAEC 5.0 - maec-malware-capabilities: Malware Capabilities based on MAEC 5.0 - maec-malware-obfuscation-methods: Obfuscation methods used by - malware based on MAEC 5.0 - malware_classification: Classification based on different - categories. Based on https://www.sans.org/reading- - room/whitepapers/incident/malware-101-viruses-32848 - (https://www.sans.org/reading-room/whitepapers/incident/malware- - 101-viruses-32848) - misinformation-website-label: classification for the identification - of type of misinformation among websites. Source:False, - Misleading, Clickbait-y, and/or Satirical News Sources by Melissa - Zimdars 2019 - misp: MISP taxonomy to infer with MISP behavior or operation. - misp-workflow: MISP workflow taxonomy to support result of workflow - execution. - monarc-threat: MONARC Threats Taxonomy - ms-caro-malware: Malware Type and Platform classification based on - Microsoft's implementation of the Computer Antivirus Research - Organization (CARO) Naming Scheme and Malware Terminology. Based - on https://www.microsoft.com/en-us/security/portal/mmpc/shared/ - malwarenaming.aspx (https://www.microsoft.com/en- - us/security/portal/mmpc/shared/malwarenaming.aspx), - https://www.microsoft.com/security/portal/mmpc/shared/ - glossary.aspx - (https://www.microsoft.com/security/portal/mmpc/shared/ - glossary.aspx), - https://www.microsoft.com/security/portal/mmpc/shared/ - objectivecriteria.aspx - (https://www.microsoft.com/security/portal/mmpc/shared/ - objectivecriteria.aspx), and http://www.caro.org/definitions/ - index.html (http://www.caro.org/definitions/index.html). Malware - families are extracted from Microsoft SIRs since 2008 based on - https://www.microsoft.com/security/sir/archive/default.aspx - (https://www.microsoft.com/security/sir/archive/default.aspx) and - https://www.microsoft.com/en-us/security/portal/threat/ - threats.aspx (https://www.microsoft.com/en- - us/security/portal/threat/threats.aspx). Note that SIRs do NOT - include all Microsoft malware families. - ms-caro-malware-full: Malware Type and Platform classification based - on Microsoft's implementation of the Computer Antivirus Research - Organization (CARO) Naming Scheme and Malware Terminology. Based - on https://www.microsoft.com/en-us/security/portal/mmpc/shared/ - malwarenaming.aspx (https://www.microsoft.com/en- - us/security/portal/mmpc/shared/malwarenaming.aspx), - https://www.microsoft.com/security/portal/mmpc/shared/ - glossary.aspx - (https://www.microsoft.com/security/portal/mmpc/shared/ + *gea-nz-activities* : Information needed to track or monitor moments, + periods or events that occur over time. This type of information is + focused on occurrences that must be tracked for business reasons or + represent a specific point in the evolution of ‘The Business’. + + *gea-nz-entities* : Information relating to instances of entities or + things. + + *gea-nz-motivators* : Information relating to authority or + governance. + + *gsma-attack-category* : Taxonomy used by GSMA for their information + sharing program with telco describing the attack categories + + *gsma-fraud* : Taxonomy used by GSMA for their information sharing + program with telco describing the various aspects of fraud + + *gsma-network-technology* : Taxonomy used by GSMA for their + information sharing program with telco describing the types of + infrastructure. WiP + + *honeypot-basic* : Updated (CIRCL, Seamus Dowling and EURECOM) from + Christian Seifert, Ian Welch, Peter Komisarczuk, ‘Taxonomy of + Honeypots’, Technical Report CS-TR-06/12, VICTORIA UNIVERSITY OF + WELLINGTON, School of Mathematical and Computing Sciences, June 2006, + http://www.mcs.vuw.ac.nz/comp/Publications/archive/CS-TR-06/CS-TR- + 06-12.pdf (http://www.mcs.vuw.ac.nz/comp/Publications/archive/CS-TR- + 06/CS-TR-06-12.pdf) + + *ics* : FIRST.ORG CTI SIG - MISP Proposal for ICS/OT Threat + Attribution (IOC) Project + + *iep* : Forum of Incident Response and Security Teams (FIRST) + Information Exchange Policy (IEP) framework + + *iep2-policy* : Forum of Incident Response and Security Teams (FIRST) + Information Exchange Policy (IEP) v2.0 Policy + + *iep2-reference* : Forum of Incident Response and Security Teams + (FIRST) Information Exchange Policy (IEP) v2.0 Reference + + *ifx-vetting* : The IFX taxonomy is used to categorise information + (MISP events and attributes) to aid in the intelligence vetting + process + + *incident-disposition* : How an incident is classified in its process + to be resolved. The taxonomy is inspired from NASA Incident Response + and Management Handbook. https://www.nasa.gov/pdf/589502main_ITS-HBK- -Dulaunoy & Iklody Expires 26 June 2024 [Page 18] +Dulaunoy & Iklody Expires 3 July 2025 [Page 18] -Internet-Draft MISP taxonomy format December 2023 +Internet-Draft MISP taxonomy format December 2024 - glossary.aspx), - https://www.microsoft.com/security/portal/mmpc/shared/ - objectivecriteria.aspx - (https://www.microsoft.com/security/portal/mmpc/shared/ - objectivecriteria.aspx), and http://www.caro.org/definitions/ - index.html (http://www.caro.org/definitions/index.html). Malware - families are extracted from Microsoft SIRs since 2008 based on - https://www.microsoft.com/security/sir/archive/default.aspx - (https://www.microsoft.com/security/sir/archive/default.aspx) and - https://www.microsoft.com/en-us/security/portal/threat/ - threats.aspx (https://www.microsoft.com/en- - us/security/portal/threat/threats.aspx). Note that SIRs do NOT - include all Microsoft malware families. - mwdb: Malware Database (mwdb) Taxonomy - Tags used across the - platform - nato: NATO classification markings. - nis: The taxonomy is meant for large scale cybersecurity incidents, - as mentioned in the Commission Recommendation of 13 September - 2017, also known as the blueprint. It has two core parts: The - nature of the incident, i.e. the underlying cause, that triggered - the incident, and the impact of the incident, i.e. the impact on - services, in which sector(s) of economy and society. - nis2: The taxonomy is meant for large scale cybersecurity incidents, - as mentioned in the Commission Recommendation of 13 May 2022, also - known as the provisional agreement. It has two core parts: The - nature of the incident, i.e. the underlying cause, that triggered - the incident, and the impact of the incident, i.e. the impact on - services, in which sector(s) of economy and society. - open_threat: Open Threat Taxonomy v1.1 base on James Tarala of SANS - http://www.auditscripts.com/resources/ - open_threat_taxonomy_v1.1a.pdf - (http://www.auditscripts.com/resources/ - open_threat_taxonomy_v1.1a.pdf), https://files.sans.org/summit/ - Threat_Hunting_Incident_Response_Summit_2016/PDFs/Using-Open- - Tools-to-Convert-Threat-Intelligence-into-Practical-Defenses- - James-Tarala-SANS-Institute.pdf (https://files.sans.org/summit/ - Threat_Hunting_Incident_Response_Summit_2016/PDFs/Using-Open- - Tools-to-Convert-Threat-Intelligence-into-Practical-Defenses- - James-Tarala-SANS-Institute.pdf), https://www.youtube.com/ - watch?v=5rdGOOFC_yE (https://www.youtube.com/watch?v=5rdGOOFC_yE), - and - https://www.rsaconference.com/writable/presentations/file_upload/ - str-r04_using-an-open-source-threat-model-for-prioritized-defense- - final.pdf - (https://www.rsaconference.com/writable/presentations/file_upload/ - str-r04_using-an-open-source-threat-model-for-prioritized-defense- - final.pdf) - osint: Open Source Intelligence - Classification (MISP taxonomies) + 2810.09- + 02%20%5bNASA%20Information%20Security%20Incident%20Management%5d.pdf# + page=9 (https://www.nasa.gov/pdf/589502main_ITS-HBK-2810.09- + 02%20%5bNASA%20Information%20Security%20Incident%20Management%5d.pdf# + page=9) + + *infoleak* : A taxonomy describing information leaks and especially + information classified as being potentially leaked. The taxonomy is + based on the work by CIRCL on the AIL framework. The taxonomy aim is + to be used at large to improve classification of leaked information. + + *information-origin* : Taxonomy for tagging information by its + origin: human-generated or AI-generated. + + *information-security-data-source* : Taxonomy to classify the + information security data sources. + + *information-security-indicators* : A full set of operational + indicators for organizations to use to benchmark their security + posture. + + *interactive-cyber-training-audience* : Describes the target of cyber + training and education. + + *interactive-cyber-training-technical-setup* : The technical setup + consists of environment structure, deployment, and orchestration. + + *interactive-cyber-training-training-environment* : The training + environment details the environment around the training, consisting + of training type and scenario. + + *interactive-cyber-training-training-setup* : The training setup + further describes the training itself with the scoring, roles, the + training mode as well as the customization level. + + *interception-method* : The interception method used to intercept + traffic. + + *ioc* : An IOC classification to facilitate automation of malicious + and non malicious artifacts + + *iot* : Internet of Things taxonomy, based on IOT UK report + https://iotuk.org.uk/wp-content/uploads/2017/01/IOT-Taxonomy- + Report.pdf (https://iotuk.org.uk/wp-content/uploads/2017/01/IOT- + Taxonomy-Report.pdf) -Dulaunoy & Iklody Expires 26 June 2024 [Page 19] + + + +Dulaunoy & Iklody Expires 3 July 2025 [Page 19] -Internet-Draft MISP taxonomy format December 2023 +Internet-Draft MISP taxonomy format December 2024 - pandemic: Pandemic - passivetotal: Tags from RiskIQ's PassiveTotal service - pentest: Penetration test (pentest) classification. - phishing: Taxonomy to classify phishing attacks including - techniques, collection mechanisms and analysis status. - poison-taxonomy: Non-exhaustive taxonomy of natural poison - political-spectrum: A political spectrum is a system to characterize - and classify different political positions in relation to one - another. - priority-level: After an incident is scored, it is assigned a - priority level. The six levels listed below are aligned with - NCCIC, DHS, and the CISS to help provide a common lexicon when - discussing incidents. This priority assignment drives NCCIC - urgency, pre-approved incident response offerings, reporting - requirements, and recommendations for leadership escalation. - Generally, incident priority distribution should follow a similar - pattern to the graph below. Based on https://www.us-cert.gov/ - NCCIC-Cyber-Incident-Scoring-System (https://www.us-cert.gov/ - NCCIC-Cyber-Incident-Scoring-System). - pyoti: PyOTI automated enrichment schemes for point in time - classification of indicators. - ransomware: Ransomware is used to define ransomware types and the - elements that compose them. - ransomware-roles: The seven roles seen in most ransomware incidents. - retention: Add a retenion time to events to automatically remove the - IDS-flag on ip-dst or ip-src attributes. We calculate the time - elapsed based on the date of the event. Supported time units are: - d(ays), w(eeks), m(onths), y(ears). The numerical_value is just - for sorting in the web-interface and is not used for calculations. - rsit: Reference Security Incident Classification Taxonomy - rt_event_status: Status of events used in Request Tracker. - runtime-packer: Runtime or software packer used to combine - compressed or encrypted data with the decompression or decryption - code. This code can add additional obfuscations mechanisms - including polymorphic-packer or other obfuscation techniques. - This taxonomy lists all the known or official packer used for - legitimate use or for packing malicious binaries. - scrippsco2-fgc: Flags describing the sample - scrippsco2-fgi: Flags describing the sample for isotopic data (C14, - O18) - scrippsco2-sampling-stations: Sampling stations of the Scripps CO2 - Program - sentinel-threattype: Sentinel indicator threat types. - smart-airports-threats: Threat taxonomy in the scope of securing - smart airports by ENISA. https://www.enisa.europa.eu/publications/ - securing-smart-airports (https://www.enisa.europa.eu/publications/ - securing-smart-airports) - social-engineering-attack-vectors: Attack vectors used in social + *kill-chain* : The Cyber Kill Chain, a phase-based model developed by + Lockheed Martin, aims to help categorise and identify the stage of an + attack. + + *maec-delivery-vectors* : Vectors used to deliver malware based on + MAEC 5.0 + + *maec-malware-behavior* : Malware behaviours based on MAEC 5.0 + + *maec-malware-capabilities* : Malware Capabilities based on MAEC 5.0 + + *maec-malware-obfuscation-methods* : Obfuscation methods used by + malware based on MAEC 5.0 + + *malware_classification* : Classification based on different + categories. Based on https://www.sans.org/reading- + room/whitepapers/incident/malware-101-viruses-32848 + (https://www.sans.org/reading-room/whitepapers/incident/malware-101- + viruses-32848) + + *misinformation-website-label* : classification for the + identification of type of misinformation among websites. + Source:False, Misleading, Clickbait-y, and/or Satirical News Sources + by Melissa Zimdars 2019 + + *misp* : MISP taxonomy to infer with MISP behavior or operation. + + *misp-workflow* : MISP workflow taxonomy to support result of + workflow execution. + + *monarc-threat* : MONARC Threats Taxonomy + + *ms-caro-malware* : Malware Type and Platform classification based on + Microsoft's implementation of the Computer Antivirus Research + Organization (CARO) Naming Scheme and Malware Terminology. Based on + https://www.microsoft.com/en-us/security/portal/mmpc/shared/ + malwarenaming.aspx (https://www.microsoft.com/en- + us/security/portal/mmpc/shared/malwarenaming.aspx), + https://www.microsoft.com/security/portal/mmpc/shared/glossary.aspx + (https://www.microsoft.com/security/portal/mmpc/shared/ + glossary.aspx), + https://www.microsoft.com/security/portal/mmpc/shared/ + objectivecriteria.aspx + (https://www.microsoft.com/security/portal/mmpc/shared/ + objectivecriteria.aspx), and http://www.caro.org/definitions/ + index.html (http://www.caro.org/definitions/index.html). Malware + families are extracted from Microsoft SIRs since 2008 based on + https://www.microsoft.com/security/sir/archive/default.aspx -Dulaunoy & Iklody Expires 26 June 2024 [Page 20] +Dulaunoy & Iklody Expires 3 July 2025 [Page 20] -Internet-Draft MISP taxonomy format December 2023 +Internet-Draft MISP taxonomy format December 2024 - engineering as described in 'A Taxonomy of Social Engineering - Defense Mechanisms' by Dalal Alharthi and others. - srbcert: SRB-CERT Taxonomy - Schemes of Classification in Incident - Response and Detection - state-responsibility: A spectrum of state responsibility to more - directly tie the goals of attribution to the needs of - policymakers. - stealth_malware: Classification based on malware stealth techniques. - Described in https://vxheaven.org/lib/pdf/ - Introducing%20Stealth%20Malware%20Taxonomy.pdf - (https://vxheaven.org/lib/pdf/ - Introducing%20Stealth%20Malware%20Taxonomy.pdf) - stix-ttp: TTPs are representations of the behavior or modus operandi - of cyber adversaries. - targeted-threat-index: The Targeted Threat Index is a metric for - assigning an overall threat ranking score to email messages that - deliver malware to a victim's computer. The TTI metric was first - introduced at SecTor 2013 by Seth Hardy as part of the talk - "RATastrophe: Monitoring a Malware Menagerie" along with Katie - Kleemola and Greg Wiseman. - thales_group: Thales Group Taxonomy - was designed with the aim of - enabling desired sharing and preventing unwanted sharing between - Thales Group security communities. - threatmatch: The ThreatMatch Sectors, Incident types, Malware types - and Alert types are applicable for any ThreatMatch instances and - should be used for all CIISI and TIBER Projects. - threats-to-dns: An overview of some of the known attacks related to - DNS as described by Torabi, S., Boukhtouta, A., Assi, C., & - Debbabi, M. (2018) in Detecting Internet Abuse by Analyzing - Passive DNS Traffic: A Survey of Implemented Systems. IEEE - Communications Surveys & Tutorials, 1-1. doi:10.1109/ - comst.2018.2849614 - tlp: The Traffic Light Protocol (TLP) (v2.0) was created to - facilitate greater sharing of potentially sensitive information - and more effective collaboration. Information sharing happens - from an information source, towards one or more recipients. TLP - is a set of four standard labels (a fifth label is included in - amber to limit the diffusion) used to indicate the sharing - boundaries to be applied by the recipients. Only labels listed in - this standard are considered valid by FIRST. This taxonomy - includes additional labels for backward compatibility which are no - more validated by FIRST SIG. - tor: Taxonomy to describe Tor network infrastructure - trust: The Indicator of Trust provides insight about data on what - can be trusted and known as a good actor. Similar to a whitelist - but on steroids, reusing features one would use with Indicators of - Compromise, but to filter out what is known to be good. - type: Taxonomy to describe different types of intelligence gathering + (https://www.microsoft.com/security/sir/archive/default.aspx) and + https://www.microsoft.com/en-us/security/portal/threat/threats.aspx + (https://www.microsoft.com/en-us/security/portal/threat/ + threats.aspx). Note that SIRs do NOT include all Microsoft malware + families. + + *ms-caro-malware-full* : Malware Type and Platform classification + based on Microsoft's implementation of the Computer Antivirus + Research Organization (CARO) Naming Scheme and Malware Terminology. + Based on https://www.microsoft.com/en-us/security/portal/mmpc/shared/ + malwarenaming.aspx (https://www.microsoft.com/en- + us/security/portal/mmpc/shared/malwarenaming.aspx), + https://www.microsoft.com/security/portal/mmpc/shared/glossary.aspx + (https://www.microsoft.com/security/portal/mmpc/shared/ + glossary.aspx), + https://www.microsoft.com/security/portal/mmpc/shared/ + objectivecriteria.aspx + (https://www.microsoft.com/security/portal/mmpc/shared/ + objectivecriteria.aspx), and http://www.caro.org/definitions/ + index.html (http://www.caro.org/definitions/index.html). Malware + families are extracted from Microsoft SIRs since 2008 based on + https://www.microsoft.com/security/sir/archive/default.aspx + (https://www.microsoft.com/security/sir/archive/default.aspx) and + https://www.microsoft.com/en-us/security/portal/threat/threats.aspx + (https://www.microsoft.com/en-us/security/portal/threat/ + threats.aspx). Note that SIRs do NOT include all Microsoft malware + families. + + *mwdb* : Malware Database (mwdb) Taxonomy - Tags used across the + platform + + *nato* : NATO classification markings. + + *nis* : The taxonomy is meant for large scale cybersecurity + incidents, as mentioned in the Commission Recommendation of 13 + September 2017, also known as the blueprint. It has two core parts: + The nature of the incident, i.e. the underlying cause, that triggered + the incident, and the impact of the incident, i.e. the impact on + services, in which sector(s) of economy and society. + + *nis2* : The taxonomy is meant for large scale cybersecurity + incidents, as mentioned in the Commission Recommendation of 13 May + 2022, also known as the provisional agreement. It has two core + parts: The nature of the incident, i.e. the underlying cause, that + triggered the incident, and the impact of the incident, i.e. the + impact on services, in which sector(s) of economy and society. -Dulaunoy & Iklody Expires 26 June 2024 [Page 21] + + +Dulaunoy & Iklody Expires 3 July 2025 [Page 21] -Internet-Draft MISP taxonomy format December 2023 +Internet-Draft MISP taxonomy format December 2024 - discipline which can be described the origin of intelligence. - unified-kill-chain: The Unified Kill Chain is a refinement to the - Kill Chain. - use-case-applicability: The Use Case Applicability categories - reflect standard resolution categories, to clearly display - alerting rule configuration problems. - veris: Vocabulary for Event Recording and Incident Sharing (VERIS) - vmray: VMRay taxonomies to map VMRay Thread Identifier scores and - artifacts. - vocabulaire-des-probabilites-estimatives: Ce vocabulaire attribue - des valeurs en pourcentage à certains énoncés de - probabilité - workflow: Workflow support language is a common language to support - intelligence analysts to perform their analysis on data and - information. + *open_threat* : Open Threat Taxonomy v1.1 base on James Tarala of + SANS http://www.auditscripts.com/resources/ + open_threat_taxonomy_v1.1a.pdf + (http://www.auditscripts.com/resources/ + open_threat_taxonomy_v1.1a.pdf), https://files.sans.org/summit/ + Threat_Hunting_Incident_Response_Summit_2016/PDFs/Using-Open-Tools- + to-Convert-Threat-Intelligence-into-Practical-Defenses-James-Tarala- + SANS-Institute.pdf (https://files.sans.org/summit/ + Threat_Hunting_Incident_Response_Summit_2016/PDFs/Using-Open-Tools- + to-Convert-Threat-Intelligence-into-Practical-Defenses-James-Tarala- + SANS-Institute.pdf), https://www.youtube.com/watch?v=5rdGOOFC_yE + (https://www.youtube.com/watch?v=5rdGOOFC_yE), and + https://www.rsaconference.com/writable/presentations/file_upload/str- + r04_using-an-open-source-threat-model-for-prioritized-defense- + final.pdf + (https://www.rsaconference.com/writable/presentations/file_upload/ + str-r04_using-an-open-source-threat-model-for-prioritized-defense- + final.pdf) + + *organizational-cyber-harm* : A taxonomy to classify organizational + cyber harms based on categories like physical, economic, + psychological, reputational, and social/societal impacts. + + *osint* : Open Source Intelligence - Classification (MISP taxonomies) + + *pandemic* : Pandemic + + *passivetotal* : Tags from RiskIQ's PassiveTotal service + + *pentest* : Penetration test (pentest) classification. + + *pfc* : Le Protocole des feux de circulation (PFC) est basé sur le + standard « Traffic Light Protocol (TLP) » conçu par le FIRST. Il a + pour objectif d’informer sur les limites autorisées pour la diffusion + des informations. Il est classé selon des codes de couleurs. + + *phishing* : Taxonomy to classify phishing attacks including + techniques, collection mechanisms and analysis status. + + *poison-taxonomy* : Non-exhaustive taxonomy of natural poison + + *political-spectrum* : A political spectrum is a system to + characterize and classify different political positions in relation + to one another. + + *priority-level* : After an incident is scored, it is assigned a + priority level. The six levels listed below are aligned with NCCIC, + DHS, and the CISS to help provide a common lexicon when discussing + + + +Dulaunoy & Iklody Expires 3 July 2025 [Page 22] + +Internet-Draft MISP taxonomy format December 2024 + + + incidents. This priority assignment drives NCCIC urgency, pre- + approved incident response offerings, reporting requirements, and + recommendations for leadership escalation. Generally, incident + priority distribution should follow a similar pattern to the graph + below. Based on https://www.cisa.gov/news-events/news/cisa-national- + cyber-incident-scoring-system-nciss (https://www.cisa.gov/news- + events/news/cisa-national-cyber-incident-scoring-system-nciss). + + *pyoti* : PyOTI automated enrichment schemes for point in time + classification of indicators. + + *ransomware* : Ransomware is used to define ransomware types and the + elements that compose them. + + *ransomware-roles* : The seven roles seen in most ransomware + incidents. + + *retention* : Add a retenion time to events to automatically remove + the IDS-flag on ip-dst or ip-src attributes. We calculate the time + elapsed based on the date of the event. Supported time units are: + d(ays), w(eeks), m(onths), y(ears). The numerical_value is just for + sorting in the web-interface and is not used for calculations. + + *rsit* : Reference Security Incident Classification Taxonomy + + *rt_event_status* : Status of events used in Request Tracker. + + *runtime-packer* : Runtime or software packer used to combine + compressed or encrypted data with the decompression or decryption + code. This code can add additional obfuscations mechanisms including + polymorphic-packer or other obfuscation techniques. This taxonomy + lists all the known or official packer used for legitimate use or for + packing malicious binaries. + + *scrippsco2-fgc* : Flags describing the sample + + *scrippsco2-fgi* : Flags describing the sample for isotopic data + (C14, O18) + + *scrippsco2-sampling-stations* : Sampling stations of the Scripps CO2 + Program + + *sentinel-threattype* : Sentinel indicator threat types. + + *smart-airports-threats* : Threat taxonomy in the scope of securing + smart airports by ENISA. https://www.enisa.europa.eu/publications/ + securing-smart-airports (https://www.enisa.europa.eu/publications/ + securing-smart-airports) + + + +Dulaunoy & Iklody Expires 3 July 2025 [Page 23] + +Internet-Draft MISP taxonomy format December 2024 + + + *social-engineering-attack-vectors* : Attack vectors used in social + engineering as described in 'A Taxonomy of Social Engineering Defense + Mechanisms' by Dalal Alharthi and others. + + *srbcert* : SRB-CERT Taxonomy - Schemes of Classification in Incident + Response and Detection + + *state-responsibility* : A spectrum of state responsibility to more + directly tie the goals of attribution to the needs of policymakers. + + *stealth_malware* : Classification based on malware stealth + techniques. Described in https://vxheaven.org/lib/pdf/ + Introducing%20Stealth%20Malware%20Taxonomy.pdf + (https://vxheaven.org/lib/pdf/ + Introducing%20Stealth%20Malware%20Taxonomy.pdf) + + *stix-ttp* : TTPs are representations of the behavior or modus + operandi of cyber adversaries. + + *targeted-threat-index* : The Targeted Threat Index is a metric for + assigning an overall threat ranking score to email messages that + deliver malware to a victim’s computer. The TTI metric was first + introduced at SecTor 2013 by Seth Hardy as part of the talk + “RATastrophe: Monitoring a Malware Menagerie” along with Katie + Kleemola and Greg Wiseman. + + *thales_group* : Thales Group Taxonomy - was designed with the aim of + enabling desired sharing and preventing unwanted sharing between + Thales Group security communities. + + *threatmatch* : The ThreatMatch Sectors, Incident types, Malware + types and Alert types are applicable for any ThreatMatch instances + and should be used for all CIISI and TIBER Projects. + + *threats-to-dns* : An overview of some of the known attacks related + to DNS as described by Torabi, S., Boukhtouta, A., Assi, C., & + Debbabi, M. (2018) in Detecting Internet Abuse by Analyzing Passive + DNS Traffic: A Survey of Implemented Systems. IEEE Communications + Surveys & Tutorials, 1–1. doi:10.1109/comst.2018.2849614 + + + + + + + + + + + + +Dulaunoy & Iklody Expires 3 July 2025 [Page 24] + +Internet-Draft MISP taxonomy format December 2024 + + + *tlp* : The Traffic Light Protocol (TLP) (v2.0) was created to + facilitate greater sharing of potentially sensitive information and + more effective collaboration. Information sharing happens from an + information source, towards one or more recipients. TLP is a set of + four standard labels (a fifth label is included in amber to limit the + diffusion) used to indicate the sharing boundaries to be applied by + the recipients. Only labels listed in this standard are considered + valid by FIRST. This taxonomy includes additional labels for + backward compatibility which are no more validated by FIRST SIG. + + *tor* : Taxonomy to describe Tor network infrastructure + + *trust* : The Indicator of Trust provides insight about data on what + can be trusted and known as a good actor. Similar to a whitelist but + on steroids, reusing features one would use with Indicators of + Compromise, but to filter out what is known to be good. + + *type* : Taxonomy to describe different types of intelligence + gathering discipline which can be described the origin of + intelligence. + + *unified-kill-chain* : The Unified Kill Chain is a refinement to the + Kill Chain. + + *unified-ransomware-kill-chain* : The Unified Ransomware Kill Chain, + a intelligence driven model developed by Oleg Skulkin, aims to track + every single phase of a ransomware attack. + + *use-case-applicability* : The Use Case Applicability categories + reflect standard resolution categories, to clearly display alerting + rule configuration problems. + + *veris* : Vocabulary for Event Recording and Incident Sharing (VERIS) + + *vmray* : VMRay taxonomies to map VMRay Thread Identifier scores and + artifacts. + + *vocabulaire-des-probabilites-estimatives* : Ce vocabulaire attribue + des valeurs en pourcentage à certains énoncés de probabilité + + *vulnerability* : A taxonomy for describing vulnerabilities + (software, hardware, or social) on different scales or with + additional available information. + + *workflow* : Workflow support language is a common language to + support intelligence analysts to perform their analysis on data and + information. + + + + +Dulaunoy & Iklody Expires 3 July 2025 [Page 25] + +Internet-Draft MISP taxonomy format December 2024 + 5. JSON Schema @@ -1226,14 +1434,6 @@ Internet-Draft MISP taxonomy format December 2023 "type": "string" }, "value": { - - - -Dulaunoy & Iklody Expires 26 June 2024 [Page 22] - -Internet-Draft MISP taxonomy format December 2023 - - "type": "string" }, "required": [ @@ -1250,6 +1450,14 @@ Internet-Draft MISP taxonomy format December 2023 "additionalProperties": false, "properties": { "entry": { + + + +Dulaunoy & Iklody Expires 3 July 2025 [Page 26] + +Internet-Draft MISP taxonomy format December 2024 + + "$ref": "#/defs/entry" }, "predicate": { @@ -1282,14 +1490,6 @@ Internet-Draft MISP taxonomy format December 2023 }, "value": { "type": "string" - - - -Dulaunoy & Iklody Expires 26 June 2024 [Page 23] - -Internet-Draft MISP taxonomy format December 2023 - - }, "exclusive": { "type": "boolean" @@ -1306,6 +1506,14 @@ Internet-Draft MISP taxonomy format December 2023 "properties": { "version": { "type": "integer" + + + +Dulaunoy & Iklody Expires 3 July 2025 [Page 27] + +Internet-Draft MISP taxonomy format December 2024 + + }, "description": { "type": "string" @@ -1338,14 +1546,6 @@ Internet-Draft MISP taxonomy format December 2023 "items": { "type": "string" } - - - -Dulaunoy & Iklody Expires 26 June 2024 [Page 24] - -Internet-Draft MISP taxonomy format December 2023 - - }, "predicates": { "$ref": "#/defs/predicates" @@ -1362,12 +1562,22 @@ Internet-Draft MISP taxonomy format December 2023 ] } + + + +Dulaunoy & Iklody Expires 3 July 2025 [Page 28] + +Internet-Draft MISP taxonomy format December 2024 + + 6. Acknowledgements The authors wish to thank all the MISP community who are supporting the creation of open standards in threat intelligence sharing. -7. Normative References +7. References + +7.1. Normative References [RFC2119] Bradner, S., "Key words for use in RFCs to Indicate Requirement Levels", BCP 14, RFC 2119, @@ -1379,29 +1589,21 @@ Internet-Draft MISP taxonomy format December 2023 DOI 10.17487/RFC8259, December 2017, . -8. Informative References +7.2. Informative References [JSON-SCHEMA] Wright, A., "JSON Schema: A Media Type for Describing JSON Documents", 2016, . - [MISP-P] Community, M., "MISP Project - Malware Information Sharing - Platform and Threat Sharing", . + [MISP-P] Community, M., "MISP Project - Open Source Threat + Intelligence Platform and Open Standards For Threat + Information Sharing", . [MISP-T] Community, M., "MISP Taxonomies - shared and common vocabularies of tags", . - - - - -Dulaunoy & Iklody Expires 26 June 2024 [Page 25] - -Internet-Draft MISP taxonomy format December 2023 - - [machine-tags] Cope, A. S., "Machine tags", 2007, + + + + + +Recommendations on Naming Threat Actors + + + + + + + + + + + + + + + + + + + + + + + + + +
Internet-DraftRecommendations on Naming Threat ActorsDecember 2024
Dulaunoy & BourmeauExpires 24 June 2025[Page]
+
+
+
+
Workgroup:
+
Network Working Group
+
Internet-Draft:
+
draft-00
+
Published:
+
+ +
+
Intended Status:
+
Informational
+
Expires:
+
+
Authors:
+
+
+
A. Dulaunoy
+
CIRCL
+
+
+
P. Bourmeau
+
Cubessa
+
+
+
+
+

Recommendations on Naming Threat Actors

+
+

Abstract

+

This document provides advice on the naming of threat actors (also known as malicious actors). +The objective is to provide practical advice for organizations such as security vendors or organizations attributing +incidents to a group of threat actors. It also discusses the implications of naming a threat actor for intelligence analysts +and threat intelligence platforms such as MISP [MISP-P].

+
+
+
+

+Status of This Memo +

+

+ This Internet-Draft is submitted in full conformance with the + provisions of BCP 78 and BCP 79.

+

+ Internet-Drafts are working documents of the Internet Engineering Task + Force (IETF). Note that other groups may also distribute working + documents as Internet-Drafts. The list of current Internet-Drafts is + at https://datatracker.ietf.org/drafts/current/.

+

+ Internet-Drafts are draft documents valid for a maximum of six months + and may be updated, replaced, or obsoleted by other documents at any + time. It is inappropriate to use Internet-Drafts as reference + material or to cite them other than as "work in progress."

+

+ This Internet-Draft will expire on 24 June 2025.

+
+
+ +
+
+

+Table of Contents +

+ +
+
+
+
+

+1. Introduction +

+

In threat intelligence, a name can be assigned to a threat actor without specific guidelines. This leads to issues such +as:

+
    +
  • A proliferation of threat actor names generating overlaps or different names for similar threat actors (e.g., some threat actors have more than 10 synonyms). +
  • +
  • Ambiguity in the words used to name the threat actor in different contexts (e.g., using common words). +
  • +
  • Lack of a clearly defined text format to describe the same threat actor (e.g., Is the threat actor name case-sensitive? Is there a dash or a space between the words?). +
  • +
  • Confusion between techniques/tools used by a threat actor versus its name (e.g., naming a threat actor after a specific malware used). +
  • +
  • Lack of source and reasoning from vendors when they describe their threat actor names (e.g., did they name the threat actor after a specific set of campaigns or a specific set of targets?). +
  • +
  • Lack of time-based information about the threat actor name, such as date of naming or a UUID. +
  • +
  • Lack of an open, mirrored "registry" of reference, accessible to all, where a new threat actor name can be registered, or where all already named threat actors can be accessed. The "registry" can contain the time-based information mentioned above; it is a tool. +
  • +
+

This document proposes a set of guidelines for naming threat actors. The goal is to reduce the issues mentioned above.

+
+
+

+1.1. Conventions and Terminology +

+

The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", +"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this +document are to be interpreted as described in RFC 2119 [RFC2119].

+
+
+
+
+
+
+

+2. Recommendations +

+

The recommendations listed below provide a minimal set of guidelines when assigning a new name to a threat actor.

+
+
+

+2.1. Reusing Threat Actor Names +

+

Before creating a new threat actor name, you MUST consider a review of existing threat actor names from databases such as the threat actor MISP galaxy [MISP-G]. Proliferation of threat actor names is a significant challenge for day-to-day analyst work. If your defined threat actor matches an existing threat actor, you MUST reuse an existing threat actor name. If there is no matching threat actor name, you SHALL create a new threat actor name, following the best practices defined in this document.

+
+
+
+
+

+2.2. Uniqueness +

+

When choosing a threat actor name, uniqueness is a critical property. The threat actor name MUST be unique and not already in use in different contexts. The name MUST NOT be a word from a dictionary, which could be used in other contexts.

+
+
+
+
+

+2.3. Format +

+

The name of the threat actor SHALL be composed of a single word. If there are multiple parts, such as a decimal value or a counter, the values MUST be separated with a dash. Single words are preferred to ease keyword searches by analysts in public sources.

+
+
+
+
+

+2.4. Encoding +

+

The name of the threat actor MUST be expressed in 7-bit ASCII. Assigning a localized name to a threat actor MAY create ambiguity due to different localized versions of the same threat actor.

+
+
+
+
+

+2.5. Avoid Confusing Actor Names with Malware Names +

+

The name of the threat actor MUST NOT be based on the tools, techniques, or patterns used by the threat actor. A notorious example in the threat intelligence community is Turla, which can refer to a threat actor but also to a malware used by this group or other groups.

+
+
+
+
+

+2.6. Directory +

+

A reference registry of threat actors is RECOMMENDED to ensure consistency of names accross different parties such as the threat actor MISP galaxy [MISP-G].

+
+
+
+
+
+
+

+3. Examples +

+

Some known examples are included below and serve as references for good and bad practices in naming threat actors. The following threat actor names are considered good examples:

+
    +
  • APT-1 +
  • +
  • TA-505 +
  • +
+

The following threat actor names are considered examples to avoid:

+
    +
  • GIF89a (Word also used for the GIF header) +
  • +
  • ShadyRAT (Confusion between the name and the tool) +
  • +
  • Group 3 (Common name used for other use-cases) +
  • +
  • ZooPark (Name is used to describe something else) +
  • +
+
+
+
+
+

+4. Security Considerations +

+

Naming a threat actor could include sensitive references to a case or an incident. Before releasing a name, the creator MUST review the name to ensure no sensitive information is included in the threat actor name.

+
+
+
+
+

+5. Acknowledgements +

+

The authors wish to thank all contributors who provided feedback through the now-defunct Twitter and other new social networks.

+
+
+
+
+

+6. References +

+
+
+
+

+7. References +

+
+

+7.1. Normative References +

+
+
[MISP-G]
+
+Community, M., "MISP Galaxy - Public repository", <https://github.com/MISP/misp-galaxy>.
+
+
[RFC2119]
+
+Bradner, S., "Key words for use in RFCs to Indicate Requirement Levels", BCP 14, RFC 2119, DOI 10.17487/RFC2119, , <https://www.rfc-editor.org/info/rfc2119>.
+
+
+
+
+

+7.2. Informative References +

+
+
[MISP-P]
+
+Community, M., "MISP Project - Open Source Threat Intelligence Platform and Open Standards For Threat Information Sharing", <https://github.com/MISP>.
+
+
+
+
+
+
+

+Authors' Addresses +

+
+
Alexandre Dulaunoy
+
Computer Incident Response Center Luxembourg
+
122, rue Adolphe Fischer
+
L-L-1521 Luxembourg +
+
Luxembourg
+
+Phone: ++352 247 88444 +
+ +
+
+
Pauline Bourmeau
+
Cubessa
+ +
+
+
+ + + diff --git a/rfc/threat-actor-naming.txt b/rfc/threat-actor-naming.txt new file mode 100644 index 0000000..4c1cdf7 --- /dev/null +++ b/rfc/threat-actor-naming.txt @@ -0,0 +1,280 @@ + + + + +Network Working Group A. Dulaunoy +Internet-Draft CIRCL +Intended status: Informational P. Bourmeau +Expires: 24 June 2025 Cubessa + 21 December 2024 + + + Recommendations on Naming Threat Actors + draft-00 + +Abstract + + This document provides advice on the naming of threat actors (also + known as malicious actors). The objective is to provide practical + advice for organizations such as security vendors or organizations + attributing incidents to a group of threat actors. It also discusses + the implications of naming a threat actor for intelligence analysts + and threat intelligence platforms such as MISP [MISP-P]. + +Status of This Memo + + This Internet-Draft is submitted in full conformance with the + provisions of BCP 78 and BCP 79. + + Internet-Drafts are working documents of the Internet Engineering + Task Force (IETF). Note that other groups may also distribute + working documents as Internet-Drafts. The list of current Internet- + Drafts is at https://datatracker.ietf.org/drafts/current/. + + Internet-Drafts are draft documents valid for a maximum of six months + and may be updated, replaced, or obsoleted by other documents at any + time. It is inappropriate to use Internet-Drafts as reference + material or to cite them other than as "work in progress." + + This Internet-Draft will expire on 24 June 2025. + +Copyright Notice + + Copyright (c) 2024 IETF Trust and the persons identified as the + document authors. All rights reserved. + + This document is subject to BCP 78 and the IETF Trust's Legal + Provisions Relating to IETF Documents (https://trustee.ietf.org/ + license-info) in effect on the date of publication of this document. + Please review these documents carefully, as they describe your rights + and restrictions with respect to this document. + + + + + +Dulaunoy & Bourmeau Expires 24 June 2025 [Page 1] + +Internet-Draft Recommendations on Naming Threat Actors December 2024 + + +Table of Contents + + 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2 + 1.1. Conventions and Terminology . . . . . . . . . . . . . . . 3 + 2. Recommendations . . . . . . . . . . . . . . . . . . . . . . . 3 + 2.1. Reusing Threat Actor Names . . . . . . . . . . . . . . . 3 + 2.2. Uniqueness . . . . . . . . . . . . . . . . . . . . . . . 3 + 2.3. Format . . . . . . . . . . . . . . . . . . . . . . . . . 3 + 2.4. Encoding . . . . . . . . . . . . . . . . . . . . . . . . 3 + 2.5. Avoid Confusing Actor Names with Malware Names . . . . . 4 + 2.6. Directory . . . . . . . . . . . . . . . . . . . . . . . . 4 + 3. Examples . . . . . . . . . . . . . . . . . . . . . . . . . . 4 + 4. Security Considerations . . . . . . . . . . . . . . . . . . . 4 + 5. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 4 + 6. References . . . . . . . . . . . . . . . . . . . . . . . . . 4 + 7. References . . . . . . . . . . . . . . . . . . . . . . . . . 4 + 7.1. Normative References . . . . . . . . . . . . . . . . . . 4 + 7.2. Informative References . . . . . . . . . . . . . . . . . 5 + Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 5 + +1. Introduction + + In threat intelligence, a name can be assigned to a threat actor + without specific guidelines. This leads to issues such as: + + * A proliferation of threat actor names generating overlaps or + different names for similar threat actors (e.g., some threat + actors have more than 10 synonyms). + * Ambiguity in the words used to name the threat actor in different + contexts (e.g., using common words). + * Lack of a clearly defined text format to describe the same threat + actor (e.g., Is the threat actor name case-sensitive? Is there a + dash or a space between the words?). + * Confusion between techniques/tools used by a threat actor versus + its name (e.g., naming a threat actor after a specific malware + used). + * Lack of source and reasoning from vendors when they describe their + threat actor names (e.g., did they name the threat actor after a + specific set of campaigns or a specific set of targets?). + * Lack of time-based information about the threat actor name, such + as date of naming or a UUID. + * Lack of an open, mirrored "registry" of reference, accessible to + all, where a new threat actor name can be registered, or where all + already named threat actors can be accessed. The "registry" can + contain the time-based information mentioned above; it is a tool. + + This document proposes a set of guidelines for naming threat actors. + The goal is to reduce the issues mentioned above. + + + +Dulaunoy & Bourmeau Expires 24 June 2025 [Page 2] + +Internet-Draft Recommendations on Naming Threat Actors December 2024 + + +1.1. Conventions and Terminology + + The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", + "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this + document are to be interpreted as described in RFC 2119 [RFC2119]. + +2. Recommendations + + The recommendations listed below provide a minimal set of guidelines + when assigning a new name to a threat actor. + +2.1. Reusing Threat Actor Names + + Before creating a new threat actor name, you MUST consider a review + of existing threat actor names from databases such as the threat + actor MISP galaxy [MISP-G]. Proliferation of threat actor names is a + significant challenge for day-to-day analyst work. If your defined + threat actor matches an existing threat actor, you MUST reuse an + existing threat actor name. If there is no matching threat actor + name, you SHALL create a new threat actor name, following the best + practices defined in this document. + +2.2. Uniqueness + + When choosing a threat actor name, uniqueness is a critical property. + The threat actor name MUST be unique and not already in use in + different contexts. The name MUST NOT be a word from a dictionary, + which could be used in other contexts. + +2.3. Format + + The name of the threat actor SHALL be composed of a single word. If + there are multiple parts, such as a decimal value or a counter, the + values MUST be separated with a dash. Single words are preferred to + ease keyword searches by analysts in public sources. + +2.4. Encoding + + The name of the threat actor MUST be expressed in 7-bit ASCII. + Assigning a localized name to a threat actor MAY create ambiguity due + to different localized versions of the same threat actor. + + + + + + + + + + +Dulaunoy & Bourmeau Expires 24 June 2025 [Page 3] + +Internet-Draft Recommendations on Naming Threat Actors December 2024 + + +2.5. Avoid Confusing Actor Names with Malware Names + + The name of the threat actor MUST NOT be based on the tools, + techniques, or patterns used by the threat actor. A notorious + example in the threat intelligence community is Turla, which can + refer to a threat actor but also to a malware used by this group or + other groups. + +2.6. Directory + + A reference registry of threat actors is RECOMMENDED to ensure + consistency of names accross different parties such as the threat + actor MISP galaxy [MISP-G]. + +3. Examples + + Some known examples are included below and serve as references for + good and bad practices in naming threat actors. The following threat + actor names are considered good examples: + + * APT-1 + * TA-505 + + The following threat actor names are considered examples to avoid: + + * GIF89a (Word also used for the GIF header) + * ShadyRAT (Confusion between the name and the tool) + * Group 3 (Common name used for other use-cases) + * ZooPark (Name is used to describe something else) + +4. Security Considerations + + Naming a threat actor could include sensitive references to a case or + an incident. Before releasing a name, the creator MUST review the + name to ensure no sensitive information is included in the threat + actor name. + +5. Acknowledgements + + The authors wish to thank all contributors who provided feedback + through the now-defunct Twitter and other new social networks. + +6. References + +7. References + +7.1. Normative References + + + + +Dulaunoy & Bourmeau Expires 24 June 2025 [Page 4] + +Internet-Draft Recommendations on Naming Threat Actors December 2024 + + + [MISP-G] Community, M., "MISP Galaxy - Public repository", + . + + [RFC2119] Bradner, S., "Key words for use in RFCs to Indicate + Requirement Levels", BCP 14, RFC 2119, + DOI 10.17487/RFC2119, March 1997, + . + +7.2. Informative References + + [MISP-P] Community, M., "MISP Project - Open Source Threat + Intelligence Platform and Open Standards For Threat + Information Sharing", . + +Authors' Addresses + + Alexandre Dulaunoy + Computer Incident Response Center Luxembourg + 122, rue Adolphe Fischer + L-L-1521 Luxembourg + Luxembourg + Phone: +352 247 88444 + Email: alexandre.dulaunoy@circl.lu + + + Pauline Bourmeau + Cubessa + Email: Pauline@cubessa.io + + + + + + + + + + + + + + + + + + + + + + + +Dulaunoy & Bourmeau Expires 24 June 2025 [Page 5] diff --git a/standards.md b/standards.md index 903871a..058c8f6 100644 --- a/standards.md +++ b/standards.md @@ -49,6 +49,12 @@ Galaxy library: [HTML](https://www.misp-galaxy.org) - [PDF](https://www.misp-pro Lead: [MISP Project](https://www.misp-project.org/) +## Threat Actor Naming + +This document provides advice on the naming of threat actors (also known as malicious actors). The objective is to provide practical advice for organizations such as security vendors or organizations attributing incidents to a group of threat actors. It also discusses the implications of naming a threat actor for intelligence analysts and threat intelligence platforms such as MISP. + +Specification: [TXT](https://www.misp-standard.org/rfc/threat-actor-naming.txt) - [HTML](https://www.misp-standard.org/rfc/threat-actor-naming.html) + ## SightingDB format This document describes the format used by SightingDB to give automated context to a given Attribute by counting occurrences and tracking times of observability. SightingDB was designed to provide to MISP and other tools an interoperable, scalable and fast way to store and retrieve attributes sightings. @@ -57,8 +63,3 @@ Specification: [TXT](https://www.misp-standard.org/rfc/sightingdb-format.txt) - Lead: [Devo Inc](https://www.devo.com/) -# Upcoming standards - -- MISP warninglist format - -