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incident-response

Classify and triage security incidents through the full NIST SP 800-61 lifecycle: SEV1-4 severity scoring, false positive filtering, forensic evidence collection, and escalation routing.

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SebastianLuser/claude-code-arcane3 stars(GitHub 3 + cccskills 0)

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Files included (4)

  • SKILL.md4.6 KB
  • references/playbooks-and-comms.md4.0 KB
  • references/regulatory-deadlines.md7.4 KB
  • scripts/incident_triage.py26.9 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Incident Response

Full lifecycle incident response from initial triage through forensic collection, severity declaration, and escalation routing. This is NOT threat hunting (see threat-detection) or post-incident review (see incident-commander).


Workflow

Step 1: Classify the Event

python3 scripts/incident_triage.py --input event.json --classify --false-positive-check --json

The triage tool classifies events into 14 incident types, scores severity, filters false positives, and determines escalation paths.

Exit codes: 0 = SEV3/4 (standard handling), 1 = SEV2 (1-hour bridge), 2 = SEV1 (immediate war room).

Step 2: Determine Severity

LevelCriteriaEscalation Path
SEV1Confirmed ransomware; active PII exfil >10K records; domain controller breach; CloudTrail disabledSOC Lead -> CISO -> CEO -> Board
SEV2Unauthorized access to sensitive systems; credential compromise with priv-esc; lateral movement confirmedSOC Lead -> CISO
SEV3Suspected unauthorized access (unconfirmed); malware contained; single account compromiseSOC Lead -> Security Manager
SEV4Alert with no confirmed impact; policy violation with no data riskL3 Analyst queue

Auto-escalation triggers: ransomware note found, active exfiltration confirmed, CloudTrail/SIEM disabled, second system compromised, C-suite account accessed.

Step 3: Filter False Positives

Five filters run before escalation: CI/CD agent activity, test environment tagging, scheduled job patterns, whitelisted service accounts, scanner activity. Recurring false positives should be tuned at the detection layer.

Step 4: Collect Forensic Evidence

Follow DFRWS six-phase framework (Identification -> Preservation -> Collection -> Examination -> Analysis -> Presentation). Collect volatile evidence first (RAM, running processes, network connections) before any containment action.

Chain of custody: SHA-256 hash at acquisition, UTC timestamp, tool provenance, investigator identity, transfer log.

Step 5: Escalate and Notify

Regulatory notification deadlines (clock starts at incident declaration):

FrameworkDeadline
GDPR72 hours
PCI-DSS v4.024 hours to acquirer
HIPAA (>500 individuals)60 days
SEC Rule4 business days
NIS224-hour early warning; 72-hour notification

Full deadline reference with penalties: references/regulatory-deadlines.md

→ Read references/playbooks-and-comms.md for the compromised-credentials playbook (GitHub, npm, cloud, app secrets), AI incident classes with their first actions, and the internal, stakeholder and external notification templates


Tool Reference

incident_triage.py

# Classify with false positive filtering
python3 scripts/incident_triage.py --input event.json --classify --false-positive-check --json

# Force severity for tabletop exercises
python3 scripts/incident_triage.py --input event.json --severity sev1 --json

# Read from stdin
echo '{"event_type": "ransomware", "host": "prod-db-01"}' | \
  python3 scripts/incident_triage.py --classify --json

Input schema: {"event_type": "...", "host": "...", "user": "...", "source_ip": "...", "timestamp": "...", "raw_payload": {}}


Anti-Patterns

  1. Starting notification clock at investigation completion -- regulatory clocks start at discovery, not investigation end
  2. Containing before collecting volatile evidence -- rebooting destroys RAM and active connections
  3. Skipping false positive verification -- escalating every alert degrades SOC credibility
  4. Undocumented command decisions -- every SEV1 decision needs timestamp and rationale
  5. Bypassing human approval for containment -- automated containment without approval can cause outages and destroy evidence
  6. Single-source classification -- collect at least two independent signals before declaring SEV1

Cross-References

SkillRelationship
threat-detectionConfirmed hunting findings escalate here for triage
cloud-securityCloud posture findings may trigger incident classification
red-teamRed team findings validate detection coverage
security-pen-testingExploited pen test vulnerabilities escalate for active incident handling

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