134 lines
3.9 KiB
Python
134 lines
3.9 KiB
Python
import datetime as dt
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import pytz
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FAKE_TIME = dt.datetime(2017, 1, 1, 12, 34, 56, tzinfo=pytz.utc)
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ATTACK_PATTERN_ID = "attack-pattern--0c7b5b88-8ff7-4a4d-aa9d-feb398cd0061"
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CAMPAIGN_ID = "campaign--8e2e2d2b-17d4-4cbf-938f-98ee46b3cd3f"
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COURSE_OF_ACTION_ID = "course-of-action--8e2e2d2b-17d4-4cbf-938f-98ee46b3cd3f"
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IDENTITY_ID = "identity--311b2d2d-f010-4473-83ec-1edf84858f4c"
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INDICATOR_ID = "indicator--a740531e-63ff-4e49-a9e1-a0a3eed0e3e7"
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INTRUSION_SET_ID = "intrusion-set--4e78f46f-a023-4e5f-bc24-71b3ca22ec29"
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MALWARE_ID = "malware--9c4638ec-f1de-4ddb-abf4-1b760417654e"
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MARKING_DEFINITION_ID = "marking-definition--613f2e26-407d-48c7-9eca-b8e91df99dc9"
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OBSERVED_DATA_ID = "observed-data--b67d30ff-02ac-498a-92f9-32f845f448cf"
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RELATIONSHIP_ID = "relationship--df7c87eb-75d2-4948-af81-9d49d246f301"
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REPORT_ID = "report--84e4d88f-44ea-4bcd-bbf3-b2c1c320bcb3"
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SIGHTING_ID = "sighting--bfbc19db-ec35-4e45-beed-f8bde2a772fb"
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THREAT_ACTOR_ID = "threat-actor--8e2e2d2b-17d4-4cbf-938f-98ee46b3cd3f"
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TOOL_ID = "tool--8e2e2d2b-17d4-4cbf-938f-98ee46b3cd3f"
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VULNERABILITY_ID = "vulnerability--0c7b5b88-8ff7-4a4d-aa9d-feb398cd0061"
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MARKING_IDS = [
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"marking-definition--613f2e26-407d-48c7-9eca-b8e91df99dc9",
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"marking-definition--443eb5c3-a76c-4a0a-8caa-e93998e7bc09",
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"marking-definition--57fcd772-9c1d-41b0-8d1f-3d47713415d9",
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"marking-definition--462bf1a6-03d2-419c-b74e-eee2238b2de4",
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"marking-definition--68520ae2-fefe-43a9-84ee-2c2a934d2c7d",
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"marking-definition--2802dfb1-1019-40a8-8848-68d0ec0e417f",
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]
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RELATIONSHIP_IDS = [
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'relationship--06520621-5352-4e6a-b976-e8fa3d437ffd',
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'relationship--181c9c09-43e6-45dd-9374-3bec192f05ef',
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'relationship--a0cbb21c-8daf-4a7f-96aa-7155a4ef8f70'
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]
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# *_KWARGS contains all required arguments to create an instance of that STIX object
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# *_MORE_KWARGS contains all the required arguments, plus some optional ones
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ATTACK_PATTERN_KWARGS = dict(
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name="Phishing",
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)
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CAMPAIGN_KWARGS = dict(
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name="Green Group Attacks Against Finance",
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description="Campaign by Green Group against a series of targets in the financial services sector.",
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)
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CAMPAIGN_MORE_KWARGS = dict(
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type='campaign',
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id=CAMPAIGN_ID,
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created_by_ref="identity--f431f809-377b-45e0-aa1c-6a4751cae5ff",
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created="2016-04-06T20:03:00.000Z",
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modified="2016-04-06T20:03:00.000Z",
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name="Green Group Attacks Against Finance",
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description="Campaign by Green Group against a series of targets in the financial services sector.",
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)
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COURSE_OF_ACTION_KWARGS = dict(
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name="Block",
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)
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IDENTITY_KWARGS = dict(
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name="John Smith",
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identity_class="individual",
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)
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INDICATOR_KWARGS = dict(
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labels=['malicious-activity'],
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pattern="[file:hashes.MD5 = 'd41d8cd98f00b204e9800998ecf8427e']",
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)
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INTRUSION_SET_KWARGS = dict(
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name="Bobcat Breakin",
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)
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MALWARE_KWARGS = dict(
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labels=['ransomware'],
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name="Cryptolocker",
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)
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MALWARE_MORE_KWARGS = dict(
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type='malware',
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id=MALWARE_ID,
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created="2016-04-06T20:03:00.000Z",
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modified="2016-04-06T20:03:00.000Z",
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labels=['ransomware'],
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name="Cryptolocker",
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description="A ransomware related to ..."
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)
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OBSERVED_DATA_KWARGS = dict(
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first_observed=FAKE_TIME,
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last_observed=FAKE_TIME,
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number_observed=1,
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objects={
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"0": {
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"type": "windows-registry-key",
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"key": "HKEY_LOCAL_MACHINE\\System\\Foo\\Bar",
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}
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}
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)
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REPORT_KWARGS = dict(
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labels=["campaign"],
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name="Bad Cybercrime",
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published=FAKE_TIME,
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object_refs=[INDICATOR_ID],
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)
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RELATIONSHIP_KWARGS = dict(
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relationship_type="indicates",
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source_ref=INDICATOR_ID,
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target_ref=MALWARE_ID,
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)
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SIGHTING_KWARGS = dict(
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sighting_of_ref=INDICATOR_ID,
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)
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THREAT_ACTOR_KWARGS = dict(
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labels=["crime-syndicate"],
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name="Evil Org",
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)
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TOOL_KWARGS = dict(
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labels=["remote-access"],
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name="VNC",
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)
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VULNERABILITY_KWARGS = dict(
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name="Heartbleed",
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)
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