conducting-post-incident-lessons-learned

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Facilitate structured post-incident reviews to identify root causes, document what worked and failed, and produce actionable recommendations to improve future incident response.

AI & Automation 12,642 stars 1468 forks Updated today Apache-2.0

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Skill Content

# Conducting Post-Incident Lessons Learned ## When to Use - After any security incident has been fully resolved and recovery completed - Following tabletop exercises or IR simulations - After significant near-miss events - Quarterly review of accumulated incident trends - When IR playbooks need updating based on real-world experience ## Prerequisites - Incident fully resolved (containment, eradication, recovery complete) - Incident timeline and documentation gathered - All incident responders available for review session - Meeting space for collaborative discussion - Incident ticketing system data for metrics analysis ## Workflow ### Step 1: Gather Incident Data ```bash # Export incident timeline from ticketing system curl -s "https://thehive.local/api/v1/case/$CASE_ID/timeline" \ -H "Authorization: Bearer $THEHIVE_API_KEY" | jq '.' > incident_timeline.json # Extract detection and response metrics from SIEM index=notable incident_id="IR-2024-042" | stats min(_time) as first_alert, max(_time) as last_alert, count as total_alerts, dc(src) as unique_sources # Compile all responder actions and timestamps grep -E "timestamp|action|analyst" /var/log/ir/IR-2024-042/*.json | \ python3 -m json.tool > compiled_actions.json ``` ### Step 2: Conduct Blameless Post-Mortem Meeting ``` Structured Agenda (90 minutes): 1. Incident summary (5 min) - Factual overview 2. Timeline walkthrough (20 min) - Chronological events 3. What worked well (15 min) - Positive outcomes 4. What need...

Details

Author
mukul975
Repository
mukul975/Anthropic-Cybersecurity-Skills
Created
3 months ago
Last Updated
today
Language
Python
License
Apache-2.0

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