Specifications used in the MISP project including MISP core format
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  1. Network Working Group A. Dulaunoy
  2. Internet-Draft A. Iklody
  3. Intended status: Informational CIRCL
  4. Expires: June 2, 2018 November 29, 2017
  5. MISP taxonomy format
  6. draft-dulaunoy-misp-taxonomy-format
  7. Abstract
  8. This document describes the MISP taxonomy format which describes a
  9. simple JSON format to represent machine tags (also called triple
  10. tags) vocabularies. A public directory of common vocabularies called
  11. MISP taxonomies is available and relies on the MISP taxonomy format.
  12. MISP taxonomies are used to classify cyber security events, threats,
  13. suspicious events, or indicators.
  14. Status of This Memo
  15. This Internet-Draft is submitted in full conformance with the
  16. provisions of BCP 78 and BCP 79.
  17. Internet-Drafts are working documents of the Internet Engineering
  18. Task Force (IETF). Note that other groups may also distribute
  19. working documents as Internet-Drafts. The list of current Internet-
  20. Drafts is at https://datatracker.ietf.org/drafts/current/.
  21. Internet-Drafts are draft documents valid for a maximum of six months
  22. and may be updated, replaced, or obsoleted by other documents at any
  23. time. It is inappropriate to use Internet-Drafts as reference
  24. material or to cite them other than as "work in progress."
  25. This Internet-Draft will expire on June 2, 2018.
  26. Copyright Notice
  27. Copyright (c) 2017 IETF Trust and the persons identified as the
  28. document authors. All rights reserved.
  29. This document is subject to BCP 78 and the IETF Trust's Legal
  30. Provisions Relating to IETF Documents
  31. (https://trustee.ietf.org/license-info) in effect on the date of
  32. publication of this document. Please review these documents
  33. carefully, as they describe your rights and restrictions with respect
  34. to this document. Code Components extracted from this document must
  35. include Simplified BSD License text as described in Section 4.e of
  36. Dulaunoy & Iklody Expires June 2, 2018 [Page 1]
  37. Internet-Draft MISP taxonomy format November 2017
  38. the Trust Legal Provisions and are provided without warranty as
  39. described in the Simplified BSD License.
  40. Table of Contents
  41. 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
  42. 1.1. Conventions and Terminology . . . . . . . . . . . . . . . 3
  43. 2. Format . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
  44. 2.1. Overview . . . . . . . . . . . . . . . . . . . . . . . . 3
  45. 2.2. predicates . . . . . . . . . . . . . . . . . . . . . . . 4
  46. 2.3. values . . . . . . . . . . . . . . . . . . . . . . . . . 4
  47. 2.4. optional fields . . . . . . . . . . . . . . . . . . . . . 4
  48. 2.4.1. colour . . . . . . . . . . . . . . . . . . . . . . . 4
  49. 2.4.2. description . . . . . . . . . . . . . . . . . . . . . 5
  50. 2.4.3. numerical_value . . . . . . . . . . . . . . . . . . . 5
  51. 3. Directory . . . . . . . . . . . . . . . . . . . . . . . . . . 6
  52. 3.1. Sample Manifest . . . . . . . . . . . . . . . . . . . . . 7
  53. 4. Sample Taxonomy in MISP taxonomy format . . . . . . . . . . . 7
  54. 4.1. Admiralty Scale Taxonomy . . . . . . . . . . . . . . . . 7
  55. 4.2. Open Source Intelligence - Classification . . . . . . . . 9
  56. 4.3. Available taxonomies in the public directory . . . . . . 11
  57. 5. JSON Schema . . . . . . . . . . . . . . . . . . . . . . . . . 20
  58. 6. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 23
  59. 7. References . . . . . . . . . . . . . . . . . . . . . . . . . 23
  60. 7.1. Normative References . . . . . . . . . . . . . . . . . . 23
  61. 7.2. Informative References . . . . . . . . . . . . . . . . . 23
  62. 7.3. URIs . . . . . . . . . . . . . . . . . . . . . . . . . . 23
  63. Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 24
  64. 1. Introduction
  65. Sharing threat information became a fundamental requirements on the
  66. Internet, security and intelligence community at large. Threat
  67. information can include indicators of compromise, malicious file
  68. indicators, financial fraud indicators or even detailed information
  69. about a threat actor. While sharing such indicators or information,
  70. classification plays an important role to ensure adequate
  71. distribution, understanding, validation or action of the shared
  72. information. MISP taxonomies is a public repository of known
  73. vocabularies that can be used in threat information sharing.
  74. Machine tags were introduced in 2007 [machine-tags] to allow users to
  75. be more precise when tagging their pictures with geolocation. So a
  76. machine tag is a tag which uses a special syntax to provide more
  77. information to users and machines. Machine tags are also known as
  78. triple tags due to their format.
  79. Dulaunoy & Iklody Expires June 2, 2018 [Page 2]
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  81. In the MISP taxonomy context, machine tags help analysts to classify
  82. their cybersecurity events, indicators or threats. MISP taxonomies
  83. can be used for classification, filtering, triggering actions or
  84. visualisation depending on their use in threat intelligence platforms
  85. such as MISP [MISP-P].
  86. 1.1. Conventions and Terminology
  87. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
  88. "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
  89. document are to be interpreted as described in RFC 2119 [RFC2119].
  90. 2. Format
  91. A machine tag is composed of a namespace (MUST), a predicate (MUST)
  92. and an optional value (OPTIONAL).
  93. Machine tags are represented as a string. Below listed are a set of
  94. sample machine tags for different namespaces such as tlp, admiralty-
  95. scale and osint.
  96. tlp:amber
  97. admiralty-scale:information-credibility="1"
  98. osint:source-type="blog-post"
  99. The MISP taxonomy format describes how to define a machine tag
  100. namespace in a parseable format. The objective is to provide a
  101. simple format to describe machine tag (aka triple tag) vocabularies.
  102. 2.1. Overview
  103. The MISP taxonomy format uses the JSON [RFC8259] format. Each
  104. namespace is represented as a JSON object with meta information
  105. including the following fields: namespace, description, version,
  106. type.
  107. namespace defines the overall namespace of the machine tag. The
  108. namespace is represented as a string and MUST be present. The
  109. description is represented as a string and MUST be present. A
  110. version is represented as a unsigned integer MUST be present. A type
  111. defines where a specific taxonomy is applicable and a type can be
  112. applicable at event, user or org level. The type is represented as
  113. an array containing one or more type and SHOULD be present. If a
  114. type is not mentioned, by default, the taxonomy is applicable at
  115. event level only. An exclusive boolean property MAY be present and
  116. defines at namespace level if the predicates are mutually exclusive.
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  119. predicates defines all the predicates available in the namespace
  120. defined. predicates is represented as an array of JSON objects.
  121. predicates MUST be present and MUST at least content one element.
  122. values defines all the values for each predicate in the namespace
  123. defined. values SHOULD be present.
  124. 2.2. predicates
  125. The predicates array contains one or more JSON objects which lists
  126. all the possible predicates. The JSON object contains two fields:
  127. value and expanded. value MUST be present. expanded SHOULD be
  128. present. value is represented as a string and describes the predicate
  129. value. The predicate value MUST not contain spaces or colons.
  130. expanded is represented as a string and describes the human-readable
  131. version of the predicate value. An exclusive property MAY be present
  132. and defines at namespace level if the values are mutually exclusive.
  133. 2.3. values
  134. The values array contain one or more JSON objects which lists all the
  135. possible values of a predicate. The JSON object contains two fields:
  136. predicate and entry. predicate is represented as a string and
  137. describes the predicate value. entry is an array with one or more
  138. JSON objects. The JSON object contains two fields: value and
  139. expanded. value MUST be present. expanded SHOULD be present. value is
  140. represented as a string and describes the machine parsable value.
  141. expanded is represented as a string and describes the human-readable
  142. version of the value.
  143. 2.4. optional fields
  144. 2.4.1. colour
  145. colour fields MAY be used at predicates or values level to set a
  146. specify colour that MAY be used by the implementation. The colour
  147. field is described as an RGB colour fill in hexadecimal
  148. representation.
  149. Example use of the colour field in the Traffic Light Protocol (TLP):
  150. Dulaunoy & Iklody Expires June 2, 2018 [Page 4]
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  152. "predicates": [
  153. {
  154. "colour": "#CC0033",
  155. "expanded": "(TLP:RED) Information exclusively and directly
  156. given to (a group of) individual recipients.
  157. Sharing outside is not legitimate.",
  158. "value": "red"
  159. },
  160. {
  161. "colour": "#FFC000",
  162. "expanded": "(TLP:AMBER) Information exclusively given
  163. to an organization; sharing limited within
  164. the organization to be effectively acted upon.",
  165. "value": "amber"
  166. }...]
  167. 2.4.2. description
  168. description fields MAY be used at predicates or values level to add a
  169. descriptive and human-readable information about the specific
  170. predicate or value. The field is represented as a string.
  171. Implementations MAY use the description field to improve more
  172. contextual information. The description at the namespace level is a
  173. MUST as described above.
  174. 2.4.3. numerical_value
  175. numerical_value fields MAY be used at a predicate or value level to
  176. add a machine-readable numeric value to a specific predicate or
  177. value. The field is represented as a JSON number. Implementations
  178. SHOULD use the decimal value provided to support scoring or
  179. filtering.
  180. The decimal range for numerical_value SHOULD use a range from 0 up to
  181. 100. The range is recommended to support common mathematical
  182. properties among taxonomies.
  183. Example use of the numerical_value in the MISP confidence level:
  184. Dulaunoy & Iklody Expires June 2, 2018 [Page 5]
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  186. {
  187. "predicate": "confidence-level",
  188. "entry": [
  189. {
  190. "expanded": "Completely confident",
  191. "value": "completely-confident",
  192. "numerical_value": 100
  193. },
  194. {
  195. "expanded": "Usually confident",
  196. "value": "usually-confident",
  197. "numerical_value": 75
  198. },
  199. {
  200. "expanded": "Fairly confident",
  201. "value": "fairly-confident",
  202. "numerical_value": 50
  203. },
  204. {
  205. "expanded": "Rarely confident",
  206. "value": "rarely-confident",
  207. "numerical_value": 25
  208. },
  209. {
  210. "expanded": "Unconfident",
  211. "value": "unconfident",
  212. "numerical_value": 0
  213. },
  214. {
  215. "expanded": "Confidence cannot be evaluated",
  216. "value": "confidence-cannot-be-evalued"
  217. }
  218. ]
  219. }
  220. 3. Directory
  221. The MISP taxonomies directory is publicly available [MISP-T] in a git
  222. repository. The repository contains a directory per namespace then a
  223. file machinetag.json which contains the taxonomy as described in the
  224. format above. In the root of the repository, a MANIFEST.json exists
  225. containing a list of all the taxonomies.
  226. The MANIFEST.json file is composed of an JSON object with metadata
  227. like version, license, description, url and path. A taxonomies array
  228. describes the taxonomy available with the description, name and
  229. version field.
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  232. 3.1. Sample Manifest
  233. {
  234. "version": "20161009",
  235. "license": "CC-0",
  236. "description": "Manifest file of MISP taxonomies available.",
  237. "url":
  238. "https://raw.githubusercontent.com/MISP/misp-taxonomies/master/",
  239. "path": "machinetag.json",
  240. "taxonomies": [
  241. {
  242. "description": "The Admiralty Scale (also called the NATO System)
  243. is used to rank the reliability of a source and
  244. the credibility of an information.",
  245. "name": "admiralty-scale",
  246. "version": 1
  247. },
  248. {
  249. "description": "Open Source Intelligence - Classification.",
  250. "name": "osint",
  251. "version": 2
  252. }]
  253. }
  254. 4. Sample Taxonomy in MISP taxonomy format
  255. 4.1. Admiralty Scale Taxonomy
  256. "namespace": "admiralty-scale",
  257. "description": "The Admiralty Scale (also called the NATO System)
  258. is used to rank the reliability of a source and
  259. the credibility of an information.",
  260. "version": 1,
  261. "predicates": [
  262. {
  263. "value": "source-reliability",
  264. "expanded": "Source Reliability"
  265. },
  266. {
  267. "value": "information-credibility",
  268. "expanded": "Information Credibility"
  269. }
  270. ],
  271. "values": [
  272. {
  273. "predicate": "source-reliability",
  274. "entry": [
  275. {
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  278. "value": "a",
  279. "expanded": "Completely reliable"
  280. },
  281. {
  282. "value": "b",
  283. "expanded": "Usually reliable"
  284. },
  285. {
  286. "value": "c",
  287. "expanded": "Fairly reliable"
  288. },
  289. {
  290. "value": "d",
  291. "expanded": "Not usually reliable"
  292. },
  293. {
  294. "value": "e",
  295. "expanded": "Unreliable"
  296. },
  297. {
  298. "value": "f",
  299. "expanded": "Reliability cannot be judged"
  300. }
  301. ]
  302. },
  303. {
  304. "predicate": "information-credibility",
  305. "entry": [
  306. {
  307. "value": "1",
  308. "expanded": "Confirmed by other sources"
  309. },
  310. {
  311. "value": "2",
  312. "expanded": "Probably true"
  313. },
  314. {
  315. "value": "3",
  316. "expanded": "Possibly true"
  317. },
  318. {
  319. "value": "4",
  320. "expanded": "Doubtful"
  321. },
  322. {
  323. "value": "5",
  324. "expanded": "Improbable"
  325. },
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  328. {
  329. "value": "6",
  330. "expanded": "Truth cannot be judged"
  331. }
  332. ]
  333. }
  334. ]
  335. }
  336. 4.2. Open Source Intelligence - Classification
  337. {
  338. "values": [
  339. {
  340. "entry": [
  341. {
  342. "expanded": "Blog post",
  343. "value": "blog-post"
  344. },
  345. {
  346. "expanded": "Technical or analysis report",
  347. "value": "technical-report"
  348. },
  349. {
  350. "expanded": "News report",
  351. "value": "news-report"
  352. },
  353. {
  354. "expanded": "Pastie-like website",
  355. "value": "pastie-website"
  356. },
  357. {
  358. "expanded": "Electronic forum",
  359. "value": "electronic-forum"
  360. },
  361. {
  362. "expanded": "Mailing-list",
  363. "value": "mailing-list"
  364. },
  365. {
  366. "expanded": "Block or Filter List",
  367. "value": "block-or-filter-list"
  368. },
  369. {
  370. "expanded": "Expansion",
  371. "value": "expansion"
  372. }
  373. ],
  374. Dulaunoy & Iklody Expires June 2, 2018 [Page 9]
  375. Internet-Draft MISP taxonomy format November 2017
  376. "predicate": "source-type"
  377. },
  378. {
  379. "predicate": "lifetime",
  380. "entry": [
  381. {
  382. "value": "perpetual",
  383. "expanded": "Perpetual",
  384. "description": "Information available publicly on long-term"
  385. },
  386. {
  387. "value": "ephemeral",
  388. "expanded": "Ephemeral",
  389. "description": "Information available publicly on short-term"
  390. }
  391. ]
  392. },
  393. {
  394. "predicate": "certainty",
  395. "entry": [
  396. {
  397. "numerical_value": 100,
  398. "value": "100",
  399. "expanded": "100% Certainty",
  400. "description": "100% Certainty"
  401. },
  402. {
  403. "numerical_value": 93,
  404. "value": "93",
  405. "expanded": "93% Almost certain",
  406. "description": "93% Almost certain"
  407. },
  408. {
  409. "numerical_value": 75,
  410. "value": "75",
  411. "expanded": "75% Probable",
  412. "description": "75% Probable"
  413. },
  414. {
  415. "numerical_value": 50,
  416. "value": "50",
  417. "expanded": "50% Chances about even",
  418. "description": "50% Chances about even"
  419. },
  420. {
  421. "numerical_value": 30,
  422. "value": "30",
  423. "expanded": "30% Probably not",
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  426. "description": "30% Probably not"
  427. },
  428. {
  429. "numerical_value": 7,
  430. "value": "7",
  431. "expanded": "7% Almost certainly not",
  432. "description": "7% Almost certainly not"
  433. },
  434. {
  435. "numerical_value": 0,
  436. "value": "0",
  437. "expanded": "0% Impossibility",
  438. "description": "0% Impossibility"
  439. }
  440. ]
  441. }
  442. ],
  443. "namespace": "osint",
  444. "description": "Open Source Intelligence - Classification",
  445. "version": 3,
  446. "predicates": [
  447. {
  448. "value": "source-type",
  449. "expanded": "Source Type"
  450. },
  451. {
  452. "value": "lifetime",
  453. "expanded": "Lifetime of the information
  454. as Open Source Intelligence"
  455. },
  456. {
  457. "value": "certainty",
  458. "expanded": "Certainty of the elements mentioned
  459. in this Open Source Intelligence"
  460. }
  461. ]
  462. }
  463. 4.3. Available taxonomies in the public directory
  464. The public directory of MISP taxonomies [MISP-T] contains a variety
  465. of taxonomy in various fields such as:
  466. CERT-XLM:
  467. CERT-XLM Security Incident Classification.
  468. DML:
  469. Dulaunoy & Iklody Expires June 2, 2018 [Page 11]
  470. Internet-Draft MISP taxonomy format November 2017
  471. The Detection Maturity Level (DML) model is a capability maturity
  472. model for referencing ones maturity in detecting cyber attacks.
  473. It's designed for organizations who perform intel-driven detection
  474. and response and who put an emphasis on having a mature detection
  475. program.
  476. PAP:
  477. The Permissible Actions Protocol - or short: PAP - was designed to
  478. indicate how the received information can be used.
  479. access-method:
  480. The access method used to remotely access a system.
  481. accessnow:
  482. Access Now classification to classify an issue (such as security,
  483. human rights, youth rights).
  484. action-taken:
  485. Action taken in the case of a security incident (CSIRT
  486. perspective).
  487. admiralty-scale:
  488. The Admiralty Scale (also called the NATO System) is used to rank
  489. the reliability of a source and the credibility of an information.
  490. adversary:
  491. An overview and description of the adversary infrastructure.
  492. ais-marking:
  493. AIS Marking Schema implementation is maintained by the National
  494. Cybersecurity and Communication Integration Center (NCCIC) of the
  495. U.S. Department of Homeland Security (DHS)
  496. analyst-assessment:
  497. A series of assessment predicates describing the analyst
  498. capabilities to perform analysis. These assessment can be
  499. assigned by the analyst him/herself or by another party evaluating
  500. the analyst.
  501. approved-category-of-action:
  502. A pre-approved category of action for indicators being shared with
  503. partners (MIMIC).
  504. binary-class:
  505. Custom taxonomy for types of binary file.
  506. cccs:
  507. Internal taxonomy for CCCS.
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  509. Internet-Draft MISP taxonomy format November 2017
  510. circl:
  511. CIRCL Taxonomy is a simple scheme for incident classification and
  512. area topic where the incident took place.
  513. collaborative-intelligence:
  514. Collaborative intelligence support language is a common language
  515. to support analysts to perform their analysis to get crowdsourced
  516. support when using threat intelligence sharing platform like MISP.
  517. common-taxonomy:
  518. The Common Taxonomy for Law Enforcement and The National Network
  519. of CSIRTs bridges the gap between the CSIRTs and international Law
  520. Enforcement communities by adding a legislative framework to
  521. facilitate the harmonisation of incident reporting to competent
  522. authorities, the development of useful statistics and sharing
  523. information within the entire cybercrime ecosystem.
  524. copine-scale:
  525. The COPINE Scale is a rating system created in Ireland and used in
  526. the United Kingdom to categorise the severity of images of child
  527. sex abuse.
  528. cryptocurrency-threat:
  529. Threats targetting cryptocurrency, based on CipherTrace report.
  530. csirt_case_classification:
  531. FIRST CSIRT Case Classification.
  532. cssa:
  533. The CSSA agreed sharing taxonomy.
  534. cyber-threat-framework:
  535. Cyber Threat Framework was developed by the US Government to
  536. enable consistent characterization and categorization of cyber
  537. threat events, and to identify trends or changes in the activities
  538. of cyber adversaries. <https://www.dni.gov/index.php/cyber-threat-
  539. framework>
  540. data-classification:
  541. Data classification for data potentially at risk of exfiltration
  542. based on table 2.1 of Solving Cyber Risk book.
  543. dcso-sharing:
  544. DCSO Sharing Taxonomy to classify certain types of MISP events
  545. using the DCSO Event Guide
  546. ddos:
  547. Dulaunoy & Iklody Expires June 2, 2018 [Page 13]
  548. Internet-Draft MISP taxonomy format November 2017
  549. Distributed Denial of Service - or short: DDoS - taxonomy supports
  550. the description of Denial of Service attacks and especially the
  551. types they belong too.
  552. de-vs:
  553. Taxonomy for the handling of protectively marked information in
  554. MISP with German (DE) Government classification markings (VS)
  555. dhs-ciip-sectors:
  556. DHS critical sectors as described in <https://www.dhs.gov/
  557. critical-infrastructure-sectors>.
  558. diamond-model:
  559. The Diamond Model for Intrusion Analysis, a phase-based model
  560. developed by Lockheed Martin, aims to help categorise and identify
  561. the stage of an attack.
  562. dni-ism:
  563. ISM (Information Security Marking Metadata) V13 as described by
  564. DNI.gov (Director of National Intelligence - US).
  565. domain-abuse:
  566. Taxonomy to tag domain names used for cybercrime.
  567. drugs:
  568. A taxonomy based on the superclass and class of drugs, based on
  569. <https://www.drugbank.ca/releases/latest>
  570. economical-impact:
  571. Economical impact is a taxonomy to describe the financial impact
  572. as positive or negative gain to the tagged information.
  573. ecsirt:
  574. eCSIRT incident classification Appendix C of the eCSIRT EU project
  575. including IntelMQ updates.
  576. enisa:
  577. ENISA Threat Taxonomy - A tool for structuring threat information
  578. as published in <https://www.enisa.europa.eu/topics/threat-risk-
  579. management/threats-and-trends/enisa-threat-landscape/etl2015/
  580. enisa-threat-taxonomy-a-tool-for-structuring-threat-information>
  581. estimative-language:
  582. Estimative language - including likelihood or probability of event
  583. based on the Intelligence Community Directive 203 (ICD 203)
  584. (6.2.(a)) and JP 2-0, Joint Intelligence.
  585. eu-marketop-and-publicadmin:
  586. Dulaunoy & Iklody Expires June 2, 2018 [Page 14]
  587. Internet-Draft MISP taxonomy format November 2017
  588. Market operators and public administrations that must comply to
  589. some notifications requirements under EU NIS directive.
  590. eu-nis-sector-and-subsectors:
  591. Sectors and sub sectors as identified by the NIS Directive.
  592. euci:
  593. EU classified information (EUCI) means any information or material
  594. designated by a EU security classification, the unauthorised
  595. disclosure of which could cause varying degrees of prejudice to
  596. the interests of the European Union or of one or more of the
  597. Member States as described in COUNCIL DECISION of 23 September
  598. 2013 on the security rules for protecting EU classified
  599. information
  600. europol-event:
  601. EUROPOL type of events taxonomy.
  602. europol-incident:
  603. EUROPOL class of incident taxonomy.
  604. event-assessment:
  605. A series of assessment predicates describing the event assessment
  606. performed to make judgement(s) under a certain level of
  607. uncertainty.
  608. event-classification:
  609. Event Classification.
  610. exercise:
  611. Exercise is a taxonomy to describe if the information is part of
  612. one or more cyber or crisis exercise.
  613. false-positive:
  614. This taxonomy aims to ballpark the expected amount of false
  615. positives.
  616. file-type:
  617. List of known file types.
  618. flesch-reading-ease:
  619. Flesch Reading Ease is a revised system for determining the
  620. comprehension difficulty of written material. The scoring of the
  621. flesh score can have a maximum of 121.22 and there is no limit on
  622. how low a score can be (negative score are valid).
  623. fpf:
  624. Dulaunoy & Iklody Expires June 2, 2018 [Page 15]
  625. Internet-Draft MISP taxonomy format November 2017
  626. The Future of Privacy Forum (FPF) visual guide to practical de-
  627. identification [1] taxonomy is used to evaluate the degree of
  628. identifiability of personal data and the types of pseudonymous
  629. data, de-identified data and anonymous data. The work of FPF is
  630. licensed under a creative commons attribution 4.0 international
  631. license.
  632. fr-classif:
  633. French gov information classification system.
  634. gdpr:
  635. Taxonomy related to the REGULATION (EU) 2016/679 OF THE EUROPEAN
  636. PARLIAMENT AND OF THE COUNCIL on the protection of natural persons
  637. with regard to the processing of personal data and on the free
  638. movement of such data, and repealing Directive 95/46/EC (General
  639. Data Protection Regulation)
  640. gsma-attack-category:
  641. Taxonomy used by GSMA for their information sharing program with
  642. telco describing the attack categories
  643. gsma-fraud:
  644. Taxonomy used by GSMA for their information sharing program with
  645. telco describing the various aspects of fraud
  646. gsma-network-technology:
  647. Taxonomy used by GSMA for their information sharing program with
  648. telco describing the types of infrastructure. WiP
  649. honeypot-basic:
  650. Christian Seifert, Ian Welch, Peter Komisarczuk, 'Taxonomy of
  651. Honeypots', Technical Report CS-TR-06/12, VICTORIA UNIVERSITY OF
  652. WELLINGTON, School of Mathematical and Computing Sciences, June
  653. 2006, <http://www.mcs.vuw.ac.nz/comp/Publications/archive/CS-TR-
  654. 06/CS-TR-06-12.pdf>
  655. iep:
  656. Forum of Incident Response and Security Teams (FIRST) Information
  657. Exchange Policy (IEP) framework.
  658. ifx-vetting:
  659. The IFX taxonomy is used to categorise information (MISP events
  660. and attributes) to aid in the intelligence vetting process
  661. incident-disposition:
  662. How an incident is classified in its process to be resolved. The
  663. taxonomy is inspired from NASA Incident Response and Management
  664. Handbook.
  665. Dulaunoy & Iklody Expires June 2, 2018 [Page 16]
  666. Internet-Draft MISP taxonomy format November 2017
  667. infoleak:
  668. A taxonomy describing information leaks and especially information
  669. classified as being potentially leaked.
  670. information-security-data-source:
  671. Taxonomy to classify the information security data sources
  672. information-security-indicators:
  673. Information security indicators have been standardized by the ETSI
  674. Industrial Specification Group (ISG) ISI. These indicators
  675. provide the basis to switch from a qualitative to a quantitative
  676. culture in IT Security Scope of measurements: External and
  677. internal threats (attempt and success), user's deviant behaviours,
  678. nonconformities and/or vulnerabilities (software, configuration,
  679. behavioural, general security framework). ETSI GS ISI 001-1
  680. (V1.1.2): ISI Indicators
  681. interception-method:
  682. The interception method used to intercept traffic.
  683. kill-chain:
  684. Cyber Kill Chain from Lockheed Martin as described in
  685. Intelligence-Driven Computer Network Defense Informed by Analysis
  686. of Adversary Campaigns and Intrusion Kill Chains.
  687. maec-delivery-vectors:
  688. Vectors used to deliver malware based on MAEC 5.0
  689. maec-malware-behavior:
  690. Malware behaviours based on MAEC 5.0
  691. maec-malware-capabilities:
  692. Malware Capabilities based on MAEC 5.0
  693. maec-malware-obfuscation-methods:
  694. Obfuscation methods used by malware based on MAEC 5.0
  695. malware_classification:
  696. Malware classification based on a SANS whitepaper about malware.
  697. misp:
  698. Internal MISP taxonomy.
  699. monarc-threat:
  700. MONARC threat taxonomy.
  701. ms-caro-malware:
  702. Dulaunoy & Iklody Expires June 2, 2018 [Page 17]
  703. Internet-Draft MISP taxonomy format November 2017
  704. Malware Type and Platform classification based on Microsoft's
  705. implementation of the Computer Antivirus Research Organization
  706. (CARO) Naming Scheme and Malware Terminology.
  707. ms-caro-malware-full:
  708. Malware Type and Platform classification based on Microsoft's
  709. implementation of the Computer Antivirus Research Organization
  710. (CARO) Naming Scheme and Malware Terminology.
  711. nato:
  712. Marking of Classified and Unclassified materials as described by
  713. the North Atlantic Treaty Organization, NATO.
  714. nis:
  715. NIS Cybersecurity Incident Taxonomy.
  716. open_threat:
  717. Open Threat Taxonomy v1.1 base on James Tarala of SANS ref. -
  718. <http://www.auditscripts.com/resources/
  719. open_threat_taxonomy_v1.1a.pdf>
  720. osint:
  721. Open Source Intelligence - Classification (MISP taxonomies).
  722. passivetotal:
  723. Tags for RiskIQ's passivetotal service
  724. pentest:
  725. Penetration test (pentest) classification.
  726. priority-level:
  727. After an incident is scored, it is assigned a priority level. The
  728. six levels listed below are aligned with NCCIC, DHS, and the CISS
  729. to help provide a common lexicon when discussing incidents. This
  730. priority assignment drives NCCIC urgency, pre-approved incident
  731. response offerings, reporting requirements, and recommendations
  732. for leadership escalation. Generally, incident priority
  733. distribution should follow a similar pattern to the graph below.
  734. Based on <https://www.us-cert.gov/NCCIC-Cyber-Incident-Scoring-
  735. System>.
  736. rsit:
  737. Reference Security Incident Classification Taxonomy.
  738. rt_event_status:
  739. Status of events used in Request Tracker.
  740. runtime-packer:
  741. Dulaunoy & Iklody Expires June 2, 2018 [Page 18]
  742. Internet-Draft MISP taxonomy format November 2017
  743. Runtime or software packer used to combine compressed data with
  744. the decompression code. The decompression code can add additional
  745. obfuscations mechanisms including polymorphic-packer or other
  746. obfuscation techniques. This taxonomy lists all the known or
  747. official packer used for legitimate use or for packing malicious
  748. binaries.
  749. smart-airports-threats:
  750. Threat taxonomy in the scope of securing smart airports by ENISA.
  751. stealth_malware:
  752. Classification based on malware stealth techniques.
  753. stix-ttp:
  754. Representation of the behavior or modus operandi of cyber
  755. adversaries (a.k.a TTP) as normalized in STIX
  756. targeted-threat-index:
  757. The Targeted Threat Index is a metric for assigning an overall
  758. threat ranking score to email messages that deliver malware to a
  759. victim's computer. The TTI metric was first introduced at SecTor
  760. 2013 by Seth Hardy as part of the talk "RATastrophe: Monitoring a
  761. Malware Menagerie" along with Katie Kleemola and Greg Wiseman.
  762. tlp:
  763. The Traffic Light Protocol - or short: TLP - was designed with the
  764. objective to create a favorable classification scheme for sharing
  765. sensitive information while keeping the control over its
  766. distribution at the same time. Extended with TLP:EX:CHR.
  767. tor:
  768. Taxonomy to describe Tor network infrastructure
  769. type:
  770. Taxonomy to describe different types of intelligence gathering
  771. discipline which can be described the origin of intelligence.
  772. use-case-applicability:
  773. The Use Case Applicability categories reflect standard resolution
  774. categories, to clearly display alerting rule configuration
  775. problems.
  776. veris:
  777. Vocabulary for Event Recording and Incident Sharing (VERIS).
  778. vocabulaire-des-probabilites-estimatives:
  779. Vocabulaire des probabilites estimatives
  780. Dulaunoy & Iklody Expires June 2, 2018 [Page 19]
  781. Internet-Draft MISP taxonomy format November 2017
  782. workflow:
  783. Workflow support language is a common language to support
  784. intelligence analysts to perform their analysis on data and
  785. information.
  786. 5. JSON Schema
  787. The JSON Schema [JSON-SCHEMA] below defines the structure of the MISP
  788. taxonomy document as literally described before. The JSON Schema is
  789. used validating a MISP taxonomy. The validation is a _MUST_ if the
  790. taxonomy is included in the MISP taxonomies directory.
  791. {
  792. "$schema": "http://json-schema.org/schema#",
  793. "title": "Validator for misp-taxonomies",
  794. "id": "https://www.github.com/MISP/misp-taxonomies/schema.json",
  795. "defs": {
  796. "entry": {
  797. "type": "array",
  798. "uniqueItems": true,
  799. "items": {
  800. "type": "object",
  801. "additionalProperties": false,
  802. "properties": {
  803. "numerical_value": {
  804. "type": "number"
  805. },
  806. "expanded": {
  807. "type": "string"
  808. },
  809. "description": {
  810. "type": "string"
  811. },
  812. "colour": {
  813. "type": "string"
  814. },
  815. "value": {
  816. "type": "string"
  817. },
  818. "required": [
  819. "value"
  820. ]
  821. }
  822. }
  823. },
  824. "values": {
  825. "type": "array",
  826. "uniqueItems": true,
  827. Dulaunoy & Iklody Expires June 2, 2018 [Page 20]
  828. Internet-Draft MISP taxonomy format November 2017
  829. "items": {
  830. "type": "object",
  831. "additionalProperties": false,
  832. "properties": {
  833. "entry": {
  834. "$ref": "#/defs/entry"
  835. },
  836. "predicate": {
  837. "type": "string"
  838. }
  839. },
  840. "required": [
  841. "predicate"
  842. ]
  843. }
  844. },
  845. "predicates": {
  846. "type": "array",
  847. "uniqueItems": true,
  848. "items": {
  849. "type": "object",
  850. "additionalProperties": false,
  851. "properties": {
  852. "numerical_value": {
  853. "type": "number"
  854. },
  855. "colour": {
  856. "type": "string"
  857. },
  858. "description": {
  859. "type": "string"
  860. },
  861. "expanded": {
  862. "type": "string"
  863. },
  864. "value": {
  865. "type": "string"
  866. },
  867. "exclusive": {
  868. "type": "boolean"
  869. },
  870. "required": [
  871. "value"
  872. ]
  873. }
  874. }
  875. }
  876. },
  877. Dulaunoy & Iklody Expires June 2, 2018 [Page 21]
  878. Internet-Draft MISP taxonomy format November 2017
  879. "type": "object",
  880. "additionalProperties": false,
  881. "properties": {
  882. "version": {
  883. "type": "integer"
  884. },
  885. "description": {
  886. "type": "string"
  887. },
  888. "expanded": {
  889. "type": "string"
  890. },
  891. "namespace": {
  892. "type": "string"
  893. },
  894. "exclusive": {
  895. "type": "boolean"
  896. },
  897. "type": {
  898. "type": "array",
  899. "uniqueItems": true,
  900. "items": {
  901. "type": "string",
  902. "enum": [
  903. "org",
  904. "user",
  905. "attribute",
  906. "event"
  907. ]
  908. }
  909. },
  910. "refs": {
  911. "type": "array",
  912. "uniqueItems": true,
  913. "items": {
  914. "type": "string"
  915. }
  916. },
  917. "predicates": {
  918. "$ref": "#/defs/predicates"
  919. },
  920. "values": {
  921. "$ref": "#/defs/values"
  922. }
  923. },
  924. "required": [
  925. "namespace",
  926. "description",
  927. Dulaunoy & Iklody Expires June 2, 2018 [Page 22]
  928. Internet-Draft MISP taxonomy format November 2017
  929. "version",
  930. "predicates"
  931. ]
  932. }
  933. 6. Acknowledgements
  934. The authors wish to thank all the MISP community who are supporting
  935. the creation of open standards in threat intelligence sharing.
  936. 7. References
  937. 7.1. Normative References
  938. [RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
  939. Requirement Levels", BCP 14, RFC 2119,
  940. DOI 10.17487/RFC2119, March 1997,
  941. <https://www.rfc-editor.org/info/rfc2119>.
  942. [RFC8259] Bray, T., Ed., "The JavaScript Object Notation (JSON) Data
  943. Interchange Format", STD 90, RFC 8259,
  944. DOI 10.17487/RFC8259, December 2017,
  945. <https://www.rfc-editor.org/info/rfc8259>.
  946. 7.2. Informative References
  947. [JSON-SCHEMA]
  948. "JSON Schema: A Media Type for Describing JSON Documents",
  949. 2016,
  950. <https://tools.ietf.org/html/draft-wright-json-schema>.
  951. [machine-tags]
  952. "Machine tags", 2007,
  953. <https://www.flickr.com/groups/51035612836@N01/
  954. discuss/72157594497877875/>.
  955. [MISP-P] MISP, "MISP Project - Malware Information Sharing Platform
  956. and Threat Sharing", <https://github.com/MISP>.
  957. [MISP-T] MISP, "MISP Taxonomies - shared and common vocabularies of
  958. tags", <https://github.com/MISP/misp-taxonomies>.
  959. 7.3. URIs
  960. [1] https://fpf.org/2016/04/25/a-visual-guide-to-practical-data-de-
  961. identification/
  962. Dulaunoy & Iklody Expires June 2, 2018 [Page 23]
  963. Internet-Draft MISP taxonomy format November 2017
  964. Authors' Addresses
  965. Alexandre Dulaunoy
  966. Computer Incident Response Center Luxembourg
  967. 16, bd d'Avranches
  968. Luxembourg L-1611
  969. Luxembourg
  970. Phone: +352 247 88444
  971. Email: alexandre.dulaunoy@circl.lu
  972. Andras Iklody
  973. Computer Incident Response Center Luxembourg
  974. 16, bd d'Avranches
  975. Luxembourg L-1611
  976. Luxembourg
  977. Phone: +352 247 88444
  978. Email: andras.iklody@circl.lu
  979. Dulaunoy & Iklody Expires June 2, 2018 [Page 24]