incident-response

name	incident-response
description	Use when a security incident has been detected or declared and needs classification, triage, escalation path determination, and forensic evidence collection. Covers SEV1-SEV4 classification, false positive filtering, incident taxonomy, and NIST SP 800-61 lifecycle.
compatibility	opencode

Incident Response

Incident response skill for the full lifecycle from initial triage through forensic collection, severity declaration, and escalation routing. This is NOT threat hunting (see threat-detection) or post-incident compliance mapping (see governance/compliance-mapping) — this is about classifying, triaging, and managing declared security incidents.

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Table of Contents

• Overview
• Incident Triage Tool
• Incident Classification
• Severity Framework
• False Positive Filtering
• Forensic Evidence Collection
• Escalation Paths
• Regulatory Notification Obligations
• Workflows
• Anti-Patterns
• Cross-References

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Overview

What This Skill Does

This skill provides the methodology and tooling for incident triage and response — classifying security events into typed incidents, scoring severity, filtering false positives, determining escalation paths, and initiating forensic evidence collection under chain-of-custody controls.

Distinction from Other Security Skills

Skill	Focus	Approach
incident-response (this)	Active incidents	Reactive — classify, escalate, collect evidence
threat-detection	Pre-incident hunting	Proactive — find threats before alerts fire
cloud-security	Cloud posture assessment	Preventive — IAM, S3, network misconfiguration
red-team	Offensive simulation	Offensive — test detection and response capability

Prerequisites

A security event must be ingested before triage. Events can come from SIEM alerts, EDR detections, threat intel feeds, or user reports. The triage tool accepts JSON event payloads; see the input schema below.

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Incident Triage Tool

The incident_triage.py tool classifies events, checks false positives, scores severity, determines escalation, and performs forensic pre-analysis.

# Classify an event from JSON file
python3 scripts/incident_triage.py --input event.json --classify --json

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

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

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

Input Event Schema

{
  "event_type": "ransomware",
  "host": "prod-db-01",
  "user": "svc_backup",
  "source_ip": "10.1.2.3",
  "timestamp": "2024-01-15T14:32:00Z",
  "raw_payload": {}
}

Exit Codes

Code	Meaning	Required Response
0	SEV3/SEV4 or clean	Standard ticket-based handling
1	SEV2 — elevated	1-hour bridge call, async coordination
2	SEV1 — critical	Immediate 15-minute war room, all-hands

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Incident Classification

Security events are classified into 14 incident types. Classification drives default severity, MITRE technique mapping, and response SLA.

Incident Taxonomy

Incident Type	Default Severity	MITRE Technique	Response SLA
ransomware	SEV1	T1486	15 minutes
data_exfiltration	SEV1	T1048	15 minutes
apt_intrusion	SEV1	T1566	15 minutes
supply_chain_compromise	SEV1	T1195	15 minutes
domain_controller_breach	SEV1	T1078.002	15 minutes
credential_compromise	SEV2	T1110	1 hour
lateral_movement	SEV2	T1021	1 hour
malware_infection	SEV2	T1204	1 hour
insider_threat	SEV2	T1078	1 hour
cloud_account_compromise	SEV2	T1078.004	1 hour
unauthorized_access	SEV3	T1190	4 hours
policy_violation	SEV3	N/A	4 hours
phishing_attempt	SEV4	T1566.001	24 hours
security_alert	SEV4	N/A	24 hours

SEV Escalation Triggers

Any of the following automatically re-declare a higher severity:

Trigger	New Severity
Ransomware note found	SEV1
Active exfiltration confirmed	SEV1
CloudTrail or SIEM disabled	SEV1
Domain controller access confirmed	SEV1
Second system compromised	SEV1
Exfiltration volume exceeds 1 GB	SEV2 minimum
C-suite account accessed	SEV2 minimum

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Severity Framework

SEV Level Matrix

Level	Name	Criteria	Skills Invoked	Escalation Path
SEV1	Critical	Confirmed ransomware; active PII/PHI exfiltration (>10K records); domain controller breach; defense evasion (CloudTrail disabled); supply chain compromise	All skills (parallel)	SOC Lead → CISO → CEO → Board Chair
SEV2	High	Confirmed unauthorized access to sensitive systems; credential compromise with elevated privileges; lateral movement confirmed; ransomware indicators without confirmed execution	triage + containment + forensics	SOC Lead → CISO
SEV3	Medium	Suspected unauthorized access (unconfirmed); malware detected and contained; single account compromise (no priv escalation)	triage + containment	SOC Lead → Security Manager
SEV4	Low	Security alert with no confirmed impact; informational indicator; policy violation with no data risk	triage only	L3 Analyst queue

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False Positive Filtering

The triage tool applies five filters before escalating to prevent false positive inflation.

False Positive Filter Types

Filter	Description	Example Pattern
CI/CD agent activity	Known build/deploy agents flagged as anomalies	jenkins, github-actions, circleci, gitlab-runner
Test environment tagging	Assets tagged as non-production	test-, staging-, dev-, sandbox-
Scheduled job patterns	Expected batch processes triggering alerts	cron, scheduled_task, batch_job, backup_
Whitelisted identities	Explicitly approved service accounts	svc_monitoring, svc_backup, datadog-agent
Scanner activity	Known security scanners and vulnerability tools	nessus, qualys, rapid7, aws_inspector

A confirmed false positive suppresses escalation and logs the suppression reason for audit purposes. Recurring false positives from the same source should be tuned out at the detection layer, not filtered repeatedly at triage.

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Forensic Evidence Collection

Evidence collection follows the DFRWS six-phase framework and the principle of volatile-first acquisition.

DFRWS Six Phases

Phase	Activity	Priority
Identification	Identify what evidence exists and where	Immediate
Preservation	Prevent modification — write-block, snapshot, legal hold	Immediate
Collection	Acquire evidence in order of volatility	Immediate
Examination	Technical analysis of collected evidence	Within 2 hours
Analysis	Interpret findings in investigative context	Within 4 hours
Presentation	Produce findings report with chain of custody	Before incident closure

Volatile Evidence — Collect First

1. Live memory (RAM dump) — lost on reboot
2. Running processes and open network connections (netstat, ps)
3. Logged-in users and active sessions
4. System uptime and current time (for timeline anchoring)
5. Environment variables and loaded kernel modules

Chain of Custody Requirements

Every evidence item must be recorded with:

• SHA-256 hash at acquisition time
• Acquisition timestamp in UTC with timezone offset
• Tool provenance (FTK Imager, Volatility, dd, AWS CloudTrail export)
• Investigator identity
• Transfer log (who had custody and when)

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Escalation Paths

By Severity

Severity	Immediate Contact	Bridge Call	External Notification
SEV1	SOC Lead + CISO (15 min)	Immediate war room	Legal + PR standby; regulatory notification per deadline table
SEV2	SOC Lead (30 min async)	1-hour bridge	Legal notification if PII involved
SEV3	Security Manager (4 hours)	Async only	None unless scope expands
SEV4	L3 Analyst queue (24 hours)	None	None

By Incident Type

Incident Type	Primary Escalation	Secondary
Ransomware / APT	CISO + CEO	Board if data at risk
PII/PHI breach	Legal + CISO	Regulatory body (per deadline table)
Cloud account compromise	Cloud security team	CISO
Insider threat	HR + Legal + CISO	Law enforcement if criminal
Supply chain	CISO + Vendor management	Board

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Regulatory Notification Obligations

The notification clock starts at incident declaration, not at investigation completion.

Framework	Incident Type	Deadline	Penalty
GDPR (EU 2016/679)	Personal data breach	72 hours after discovery	Up to 4% global revenue
PCI-DSS v4.0	Cardholder data breach	24 hours to acquirer	Card brand fines
HIPAA (45 CFR 164)	PHI breach (>500 individuals)	60 days after discovery	Up to $1.9M per violation category
NY DFS 23 NYCRR 500	Cybersecurity event	72 hours to DFS	Regulatory sanctions
SEC Rule (17 CFR 229.106)	Material cybersecurity incident	4 business days after materiality determination	SEC enforcement
CCPA / CPRA	Breach of sensitive PI	Without unreasonable delay	AG enforcement; private right of action
NIS2 (EU 2022/2555)	Significant incident (essential services)	24-hour early warning; 72-hour notification	National authority sanctions

Operational rule: If scope is unclear at declaration, assume the most restrictive applicable deadline and confirm scope within the first response window.

Full deadline reference: references/regulatory-deadlines.md

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Workflows

Workflow 1: Quick Triage (15 Minutes)

For single alert requiring classification before escalation decision:

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

# 2. Review severity, escalation_path, and false_positive_flag in output
# 3. If severity = sev1 or sev2, page SOC Lead immediately
# 4. If false_positive_flag = true, document and close

Decision: Exit code 2 = SEV1 war room now. Exit code 1 = SEV2 bridge call within 30 minutes.

Workflow 2: Full Incident Response (SEV1)

T+0   Detection arrives (SIEM alert, EDR, user report)
T+5   Classify with incident_triage.py --classify --false-positive-check
T+10  If SEV1: page CISO, open war room, start regulatory clock
T+15  Initiate forensic collection (volatile evidence first)
T+15  Containment assessment (parallel with forensics)
T+30  Human approval gate for any containment action
T+45  Execute approved containment
T+60  Assess containment effectiveness, brief Legal if PII/PHI scope
T+4h  Final forensic evidence package, dwell time estimate
T+8h  Eradication and recovery plan
T+72h Regulatory notification submission (if GDPR/NIS2 triggered)

# Full classification with forensic context
python3 scripts/incident_triage.py --input incident.json \
  --classify --false-positive-check --severity sev1 --json > incident_triage_output.json

# Forensic pre-analysis
python3 scripts/incident_triage.py --input incident.json --json | \
  jq '.forensic_findings, .chain_of_custody_steps'

Workflow 3: Tabletop Exercise Simulation

Simulate incidents at specific severity levels without real events:

# Simulate SEV1 ransomware incident
echo '{"event_type": "ransomware", "host": "prod-db-01", "user": "svc_backup"}' | \
  python3 scripts/incident_triage.py --classify --severity sev1 --json

# Simulate SEV2 credential compromise
echo '{"event_type": "credential_compromise", "user": "admin_user", "source_ip": "203.0.113.5"}' | \
  python3 scripts/incident_triage.py --classify --false-positive-check --json

# Verify escalation paths for all 14 incident types
for type in ransomware data_exfiltration credential_compromise lateral_movement; do
  echo "{\"event_type\": \"$type\"}" | python3 scripts/incident_triage.py --classify --json
done

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Anti-Patterns

1. Starting the notification clock at investigation completion — Regulatory clocks (GDPR 72 hours, PCI 24 hours) start at discovery, not investigation completion. Declaring late exposes the organization to maximum penalties even if the incident itself was minor.
2. Containing before collecting volatile evidence — Rebooting or isolating a system destroys RAM, running processes, and active connections. Forensic collection of volatile evidence must happen in parallel with containment, never after.
3. Skipping false positive verification before escalation — Escalating every alert to SEV1 degrades SOC credibility and causes alert fatigue. Always run false positive filters before paging the CISO.
4. Undocumented incident command decisions — Every decision made during a SEV1, including decisions made under uncertainty, must be logged in the evidence chain with timestamp and rationale. Undocumented decisions cannot be defended in regulatory investigations.
5. Treating incident closure as investigation completion — Incidents are closed when eradication and recovery are complete, not when the investigation is done. The forensic report and regulatory submissions may continue after operational closure.
6. Single-source classification — Classifying an incident from a single data source (one SIEM alert) without corroborating evidence frequently leads to misclassification. Collect at least two independent signals before declaring SEV1.
7. Bypassing human approval gates for containment — Automated containment actions (network isolation, credential revocation) taken without human approval can cause production outages, destroy evidence, and create liability. Human approval is non-negotiable for all mutating containment actions.

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Cross-References

Skill	Relationship
threat-detection	Confirmed hunting findings escalate to incident-response for triage and classification
cloud-security	Cloud posture findings (IAM compromise, S3 exposure) may trigger incident classification
red-team	Red team findings validate detection coverage; confirmed gaps become hunting hypotheses
security-pen-testing	Pen test vulnerabilities exploited in the wild escalate to incident-response for active incident handling