anti
806301e179
10 YAMLs for the behavioral / cross-event cohort per Appendix B: beaconing, data destruction, ransom note, web exfil, DB mass-read, credentials-in-files, k8s SA token harvest, Docker host escape, LLMNR poisoning, TFTP router-config retrieval. Every rule is lifter-bound (BehavioralLifter / IdentityLifter) — the v0 RuleEngine cannot count, aggregate, or compose cross-event signals, so these YAMLs declare the technique mappings the lifter will consume by rule_id at E.3.9. Their match specs use a 'kind: lifter:*' shape inert to the regex matcher. test_behavioral_rules.py asserts each YAML compiles, none fire from the v0 engine (FP regression guard against a YAML drifting into a regex), and an xfail(strict=True, reason='impl phase E.3.9') precision case that will flip green when the lifter lands.
20 lines
434 B
YAML
20 lines
434 B
YAML
rule_id: R0039
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rule_version: 1
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name: llmnr_poisoning
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description: |
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Responder-style LLMNR/NBT-NS spoofed reply pattern observed
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on the network sniffer. BehavioralLifter (E.3.9) reads the
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network-event aggregate.
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applies_to:
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- session
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match:
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kind: lifter:llmnr_poisoning
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emits:
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- tactic: TA0009
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technique_id: T1557
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sub_technique_id: T1557.001
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confidence: 0.9
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evidence_fields:
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- poisoned_query
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- victim_host
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