Incident Response Playbook
Incident Response Playbook
This guide provides step-by-step procedures for responding to AI agent skill security incidents, from initial detection through full recovery.
Incident Types & Severity Levels
Severity Classification
CRITICAL (Red)
- Active exploitation in production
- Mass deployment of malicious skills
- Data exfiltration confirmed
- System compromise in progress
- Response time: 1 hour
HIGH (Orange)
- Confirmed malicious skill found
- Potential widespread exposure
- Vulnerability affecting many users
- Active campaign detected
- Response time: 4 hours
MEDIUM (Yellow)
- Suspicious skill behavior detected
- Potential vulnerability identified
- Limited user impact
- Investigation needed
- Response time: 1 business day
LOW (Blue)
- Minor security finding
- No immediate risk
- Policy violation
- Documentation issue
- Response time: 1 week
Incident Response Workflow
Detect
↓
Analyze & Classify
↓
Notify Stakeholders
↓
Contain & Mitigate
↓
Investigate
↓
Remediate
↓
Communicate
↓
Post-Incident Review
Playbook 1: Malicious Skill Discovery
Scenario
A malicious skill has been discovered in a registry.
Detection Indicators
- ✓ Automated scanner flags on installation
- ✓ User reports suspicious behavior
- ✓ Manual security review finds issues
- ✓ Threat intelligence indicates compromise
- ✓ Unusual network activity detected
Step 1: Initial Response (Immediate - 15 minutes)
1.1 Confirm Detection
# Verify skill details
skill_id="suspicious-skill-123"
platform="openclap"
# Pull skill metadata
curl -s https://api.${platform}.dev/skills/${skill_id} | jq .
# Check download statistics
curl -s https://api.${platform}.dev/skills/${skill_id}/stats | jq .
# Review recent reviews/reports
curl -s https://api.${platform}.dev/skills/${skill_id}/reports | jq .
1.2 Create Incident Ticket
Incident: Malicious Skill Discovery
ID: INC-2026-0001
Severity: HIGH
Skill ID: suspicious-skill-123
Platform: OpenClaw
Discovered: 2026-03-22T10:30:00Z
Reported By: Security Team
Status: OPEN
1.3 Assemble Response Team
- Security Engineer (Lead)
- Platform Administrator
- Threat Intelligence Analyst
- Communications Officer
- Legal/Compliance (if needed)
Step 2: Analysis & Classification (30 minutes)
2.1 Analyze Skill Content
# Automated analysis
from ast10_scanner import SkillAnalyzer
analyzer = SkillAnalyzer()
skill_content = download_skill('suspicious-skill-123')
analysis = analyzer.comprehensive_scan(skill_content)
# Check findings
for finding in analysis.vulnerabilities:
if finding.severity == 'critical':
print(f"CRITICAL: {finding.description}")
print(f"Evidence: {finding.evidence}")
2.2 Determine Maliciousness
Indicators of Compromise:
- Obfuscated or encoded payloads
- Unauthorized data exfiltration attempts
- Command injection patterns
- Credential harvesting code
- Communication to known C2 servers
- Process modification/persistence
- Lateral movement attempts
2.3 Classify Incident
Type: MALWARE
Subtype: Information Stealer
TTPs: Credential Harvesting, Data Exfiltration
Severity: CRITICAL
Estimated Impact: 12,400+ installations
Step 3: Notification & Escalation (30 minutes)
3.1 Notify Internal Teams
TO: Security Operations Center
CC: Executive Team, Legal
PRIORITY: CRITICAL
Subject: CRITICAL - Malicious Skill Found: [skill-id]
Details:
- Skill ID: suspicious-skill-123
- Downloads: 12,400+
- Type: Information Stealer
- Confidence: 95%
- Status: Under Investigation
Actions Initiated:
- Skill flagged for removal
- Platform notifications queued
- Incident response activated
3.2 Notify Platform Operators
Affected Platforms: OpenClaw, Claude Code
Urgency: IMMEDIATE ACTION REQUIRED
The following skill has been identified as malicious:
- ID: suspicious-skill-123
- Classification: Critical Malware
- Estimated Impact: 12,400+ affected users
- Recommended Action: Immediate removal
We request:
1. Immediate skill removal from registry
2. User notifications
3. Download halt
4. User support coordination
Step 4: Containment & Mitigation (1 hour)
4.1 Remove Malicious Skill
# Platform-specific removal
# OpenClaw
claw skill remove suspicious-skill-123 --force --reason "CRITICAL: Malware discovered"
# Claude Code
claude skill remove suspicious-skill-123 --emergency
# Cursor
cursor skill revoke suspicious-skill-123 --immediate
# VS Code
vsce withdraw suspicious-skill-123 --force
4.2 Issue User Alerts
Alert Template:
SECURITY ALERT: Malicious Skill Detected
A skill you may have installed has been identified as malicious:
Skill Name: [name]
Skill ID: suspicious-skill-123
Download Date: [optional]
Risk: HIGH
Actions You Should Take:
1. Uninstall the skill immediately
2. Reset any API keys or credentials
3. Check your data for unauthorized access
4. Report if you've noticed suspicious activity
Steps to Uninstall:
[Platform-specific instructions]
Questions? Contact: [email protected]
4.3 Block Installation
Quarantine Rule:
- Skill ID: suspicious-skill-123
- Reason: Malware detection
- Scan Result: 95% confidence malicious
- Action: Block installation
- Duration: Permanent until reviewed
Step 5: Investigation (2-4 hours)
5.1 Detailed Analysis
# Extract skill components
unzip skill-archive.zip -d /tmp/skill-analysis
# Static analysis
ast10-scan /tmp/skill-analysis --detailed
# Check for obfuscation
entropy-check /tmp/skill-analysis
string-analysis /tmp/skill-analysis
# Network analysis
grep -r "http\|dns\|socket" /tmp/skill-analysis
5.2 Build Indicators of Compromise
{
"iocs": [
{
"type": "domain",
"value": "malicious.example.com",
"confidence": "high"
},
{
"type": "ip_address",
"value": "192.0.2.1",
"confidence": "high"
},
{
"type": "file_hash",
"value": "abc123def456...",
"confidence": "very_high"
}
]
}
5.3 Determine Scope & Timeline
Timeline:
- 2026-01-15: Skill created
- 2026-01-20: First downloads (23 users)
- 2026-02-10: Downloaded 1,200 times
- 2026-03-01: Peak downloads (8,400 total)
- 2026-03-22: Malicious behavior reported
Affected Users: ~12,400
Geographical Distribution: Global
Platforms: OpenClaw (primary), Claude Code (secondary)
Step 6: Remediation (1-3 days)
6.1 User Support
Support Actions:
- [ ] Create FAQ page
- [ ] Set up dedicated support phone line
- [ ] Email affected users with remediation steps
- [ ] Provide credential reset assistance
- [ ] Monitor for follow-up incidents
Resources:
- Credential reset guide: [link]
- FAQ: [link]
- Emergency support: 1-800-SECURITY
6.2 System Cleanup
For affected users:
# Step 1: Stop all agents
systemctl stop agent-service
# Step 2: Remove malicious skill
rm -rf ~/.agent/skills/suspicious-skill-123
# Step 3: Clear caches
rm -rf ~/.agent/cache/*
# Step 4: Reset credentials
generate-new-api-keys
# Step 5: Restart agents
systemctl start agent-service
# Step 6: Verify clean state
agent-security-check
6.3 Infrastructure Hardening
Post-Incident Hardening:
- [ ] Increase automated scanning sensitivity
- [ ] Add skill behavior monitoring
- [ ] Implement stricter code review
- [ ] Deploy behavioral analysis
- [ ] Add user activity monitoring
- [ ] Implement 2FA for publisher accounts
Step 7: Communication (Ongoing)
7.1 Public Statement (Template)
# Security Incident: Malicious Skill Removal
## What Happened
On March 22, 2026, our security team identified a malicious skill
in the OpenClaw registry designed to steal user credentials.
## Impact
- 12,400 installations
- 0 confirmed credential thefts detected
- All affected installations removed
## Actions Taken
- Immediately removed skill from all registries
- Notified all users
- Enhanced detection systems
- Provided remediation guidance
## What You Should Do
1. Check if you installed "suspicious-skill-123"
2. Uninstall if present
3. Reset credentials as precaution
4. Keep software updated
## Timeline
[Detailed timeline of discovery and response]
## Questions?
Contact: [email protected]
7.2 Status Updates
- Hour 1: Initial notification
- Hour 4: Removal complete notification
- Day 1: Detailed incident report
- Week 1: Post-incident review complete
- Month 1: Preventive measures deployed
Step 8: Post-Incident Review (1 week)
8.1 Blameless Postmortem
# Incident Postmortem: Malicious Skill INC-2026-0001
## Timeline
[Detailed timeline with all actions]
## Detection Analysis
- How did we detect it?
- Could we have detected earlier?
- What were the warning signs?
## Response Analysis
- What worked well?
- What could be improved?
- Was communication effective?
## Root Cause
[Understanding of how malicious skill was published]
## Preventive Actions
1. [Action to prevent recurrence]
2. [Action to detect faster]
3. [Action to contain better]
## Lessons Learned
[Key insights from incident]
8.2 Process Improvements
Improvements Implemented:
- [ ] Automated behavioral analysis for all skills
- [ ] Real-time threat intelligence integration
- [ ] Enhanced code review procedures
- [ ] Publisher account security hardening
- [ ] User notification automation
- [ ] Faster skill removal workflows
Playbook 2: Data Breach via Skill
Scenario
A skill has been used to exfiltrate sensitive user data.
Response Priorities
- Immediate (15 min): Stop data flow, notify affected users
- Urgent (1 hour): Contain scope, preserve evidence
- Short-term (1 day): Notify authorities, support users
- Medium-term (1 week): Full investigation, remediation
- Long-term (1 month): Prevention, lessons learned
Critical Actions
# 1. Stop exfiltration
firewall-rule --block destination=attacker-ip --priority=critical
# 2. Isolate affected systems
agent shutdown --affected-users=[list]
# 3. Preserve logs
backup-logs --critical-only /data/incidents/inc-2026-0001
# 4. Revoke compromised credentials
revoke-credentials --all-affected-users
# 5. Notify users
send-incident-notification --template=data_breach --recipients=[list]
Regulatory Compliance
- Notify regulators within required timeframe (typically 72 hours)
- Consult legal team
- Prepare regulatory notifications
- Document all steps for audit
Playbook 3: Supply Chain Attack Detection
Scenario
Compromised dependencies could propagate malware.
Detection Process
1. Scan dependency tree
2. Check each dependency's integrity
3. Verify signatures
4. Check for known vulnerabilities
5. Analyze behavioral changes
Response
1. Isolate affected versions
2. Notify dependent skills
3. Provide patched versions
4. Update threat intelligence
5. Communicate to users
Escalation Contacts
Internal Escalation
- Level 1: Security Team Lead
- Level 2: CISO
- Level 3: Executive Team / Board
External Notification
- Platforms: [email protected]
- Media: [email protected]
- Users: [email protected]
Incident Support
- 24/7 Incident Hotline: [Number]
- Email: [email protected]
- Chat: #incidents on Slack
Resources & Templates
Playbooks updated: March 2026. Review quarterly and after each major incident.
Example
Put whatever you like here: news, screenshots, features, supporters, or remove this file and don’t use tabs at all.
Leadership & Founding Members
Project Leadership
Current Leaders
Ken Huang
Hammad Atta
Fabio Cerullo
Aonan Guan
Bhavya Gupta
Niv Hoffman
Iftach Orr
Akram Sheriff
AIVSS Distinguished Review Board
The OWASP AIVSS project’s Distinguished Review Board comprises world-renowned cybersecurity leaders, former government officials, and industry pioneers who provide strategic guidance and expert oversight for the AI Vulnerability Scoring System framework. We thank them for their guidance, several of whom have also supported this project’s work.
Rob Joyce
Advisor to PwC and OpenAI, Former Special Assistant to the President and Cybersecurity Coordinator
Jason Clinton
Deputy CISO, Anthropic
Amy R. Steagall
Chief Information Security Officer, Stanford University
Martin Stanley
AI Risk Management Framework Lead, NIST
Apostol Vassilev
Research Supervisor, NIST
Andrew Coyne
CISO, Banner Health, Former CISO, Mayo Clinic
Kevin Rocque
Managing Director/Executive Vice President, Global Technology Risk Officer, TD Bank
Jeff Williams
Former Global OWASP Chair, Founder and CTO, Contrast Security
Michael Tran Duff
University Chief Information Security and Data Privacy Officer, Harvard University
Emil Bender Lassen
Standards Lead, AIUC-1
Agentic Skills Top 10 Founding Members
Founding members of the OWASP Agentic Skills Top 10 project itself — project leads, co-leads, and additional contributors — listed alphabetically. Several also contribute to the sibling OWASP AIVSS project listed above.
Ken Huang
Project Lead, Agentic Skills Top 10
Hammad Atta
Co-Lead, Agentic Skills Top 10
Manish Bhatt
Security Researcher, AWS
Fabio Cerullo
Co-Lead, Agentic Skills Top 10
David Girard
Senior Director, AI Security & AI Alliances, Trend Micro
Aonan Guan
Co-Lead, Agentic Skills Top 10
Bhavya Gupta
Co-Lead, Agentic Skills Top 10
Pamela Gupta
Founder & CEO, OutSecure / Trusted AI
Idan Habler
Staff AI/ML Security Researcher, Intuit
Niv Hoffman
CTO, Air Security
Charles Iheagwara
AI/ML Security Leader, AstraZeneca
Sushmitha Janapareddy
Director - Security Integrations, American Express
Edward Lee
Vice President, Lead AI Security, JP Morgan
KJ Lian
Senior Manager, Data & AI (Public Sector), AWS
Vineeth Sai Narajala
Application Security, AWS
Iftach Orr
Co-Lead, Agentic Skills Top 10
Kanna Sekar
Cyber Security, Google
Akram Sheriff
Co-Lead, Agentic Skills Top 10
Dennis Xu
Research VP, AI, Gartner
OWASP AIVSS Founding Members
The OWASP AIVSS (Agentic AI Vulnerability Scoring System) project is a sibling OWASP initiative focused on scoring the severity of agentic AI vulnerabilities. Its founding members are recognized here as OWASP founding members in the agentic AI security space; many of them have also contributed directly to the Agentic Skills Top 10 project’s research and review process.
Sunil Agrawal
Chief Information Security Officer, Glean
David Ames
Partner, PwC
Michael Bargury
Founder and CTO, Zenity
Joshua Beck
Application Security Architect, SAS
Manish Bhatt
Security Researcher, Amazon Kuiper Security
Mark Breitenbach
Security Engineer, Dropbox
Anat Bremler-Barr
Professor of Computer Science, Tel Aviv University
Siah Burke
HIPAA Security Officer, Siah.ai
David Campbell
AI Security, Scale AI
Ying-Jung Chen
AI safety researcher, PhD, Georgia Institute of Technology
Anton Chuvakin
Security Solution Strategy, Google
Jason Clinton
CISO, Anthorphic
Adam Dawson
Staff AI Security Researcher, Dreadnode
Leon Derczynski
Principal Research Scientist, NVIDIA
Walker Lee Dimon
AI Security Researcher, MITRE
Marissa Dotter
AI Security Researcher, MITRE
Dan Goldberg
ISO Market Lead, Omnicom
David Haber
CEO, Lakera
Idan Habler
Staff AI/ML Security Researcher, Intuit
Jason Haddix
Founder, Arcanum Information Security
Keith Hoodlet
Director of AI/ML & AppSec, Trail of Bits
Ken Huang
AIVSS Project Lead, OWASP
Chris Hughes
CEO, Aquia
Charles Iheagwara
AI/ML Security Leader, AstraZeneca
Krystal Jackson
Researcher, Center for Long-Term Cybersecurity, UC Berkeley
Sushmitha Janapareddy
Director - Security Integrations, American Express
Rob Joyce
Former Cybersecurity Director of NSA, Advisor to PwC, PwC
Diana Kelley
CISO, Noma Security
Prashant Kulkarni
Lead AI Security Research Engineer, Google Cloud
Mahesh Lambe
Founder, MIT, Unify Dynamics
Edward Lee
Vice President, Lead AI Security, JP Morgan
Nate Lee
CEO, Cloudsec.ai
Vishwas Manral
CEO, Precize.ai
Daniela Muhaj
Executive-in-Residence for Research & Development, AI 2030
Vineeth Sai Narajala
Application Security, AWS
Om Narayan
AI Security Researcher, AWS
Varun Pant
Engineering and Product Leader, AI applications at the Automated Reasoning Group, AWS
Advait Patel
Senior Site Reliability Engineer (DevSecOps + Cloud + AIOps), Broadcom, IEEE
Alex Polyakov
CEO, adversa.ai
Ramesh Raskar
Professor & Director, MIT Media Lab
Ron F. Del Rosario
VP-Head of AI Security, SAP
Tal Shapira
Co-Founder & CTO, Reco AI
Akram Sheriff
Senior AI/ML Software Engineering Leader, Cisco
Samantha Siau
Security and Compliance, Anthropic
Kevin Simmonds
Partner on AI Offensive Security, PWC
Martin Stanley
NIST AI RMF Lead, Independent
Omar A. Turner
General Manager of Security, Microsoft
Apostol Vassilev
AI Research Team Supervisor, NIST
Matthew Versaggi
AI Fellow, White House Presidential Innovation Fellow
David Webb
Agency Cybersecurity Officer, Cybersecurity and Infrastructure Security Agency
Dennis Xu
Research VP, AI, Gartner
Xiaochen Zhang
Executive Director and Chief Responsible AI Officer, AI 2030
Recognition
We extend our gratitude to all founding members who have contributed to establishing this crucial framework for AI security assessment. Their vision and dedication have been instrumental in shaping the Agentic Skills Top 10 project.
Get Involved
Interested in contributing to the Agentic Skills Top 10 project? We welcome new contributors and leaders. Please see our Contribution Guidelines for more information on how to get involved.