ai-security-verification
Comprehensive AI security verification using OWASP AI Security Verification Standard (AISVS) framework. Use when verifying an AI-driven application, ML pipeline, or LLM-integrated system against AISVS, preparing for an AI security audit, or checking security and ethical controls across 13 categories from training data governance to human oversight.
- Installs
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/owasp/secure-agent-playbook --skill ai-security-verification- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads ai-security-verification automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
AI Security Verification Standard (AISVS)
Conduct comprehensive security verification of AI-driven applications using the OWASP AI Security Verification Standard (AISVS) framework's 13-category structured checklist. Follow the full procedure in plays/ai-security-verification.md.
Steps
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Training Data Governance & Bias Management — Assess data quality, provenance, bias detection, and governance controls throughout the data lifecycle.
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User Input Validation — Evaluate input sanitization, prompt injection defenses, adversarial input detection, and boundary validation mechanisms.
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Model Lifecycle Management & Change Control — Review model versioning, deployment controls, rollback capabilities, and change management processes.
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Infrastructure, Configuration & Deployment Security — Examine deployment security, container hardening, network controls, and infrastructure configuration.
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Access Control & Identity — Verify authentication mechanisms, authorization controls, privilege management, and identity governance.
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Supply Chain Security for Models, Frameworks & Data — Assess third-party model security, dependency management, and supply chain integrity.
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Model Behavior, Output Control & Safety Assurance — Evaluate output validation, safety guardrails, behavior monitoring, and harmful content prevention.
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Memory, Embeddings & Vector Database Security — Review vector database security, embedding protection, memory isolation, and context management.
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Autonomous Orchestration & Agentic Action Security — Assess agent coordination security, tool access controls, and autonomous decision-making safeguards.
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Adversarial Robustness & Attack Resistance — Test resilience against adversarial examples, evasion attacks, and model extraction attempts.
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Privacy Protection & Personal Data Management — Verify privacy controls, data minimization, consent management, and regulatory compliance.
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Monitoring, Logging & Anomaly Detection — Evaluate security monitoring, audit logging, anomaly detection, and incident response capabilities.
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Human Oversight and Trust — Assess human-in-the-loop controls, explainability mechanisms, and trust calibration measures.
Output
Use the finding format from templates/finding.md. Produce:
- AISVS Compliance Assessment — Verification status across all 13 categories
- Security Control Evaluation — Detailed analysis of implemented controls
- Gap Analysis — Missing or inadequate security measures
- Risk-Based Prioritization — Critical findings requiring immediate attention
- Compliance Roadmap — Structured plan to achieve AISVS compliance
- Verification Evidence — Documentation supporting compliance claims
OWASP References
- OWASP AI Security Verification Standard (AISVS)
- OWASP Top 10 for LLM Applications 2025
- OWASP AI Security and Privacy Guide
- OWASP Application Security Verification Standard (ASVS)
- OWASP AI Testing Guide
- Full procedure:
plays/ai-security-verification.md
FAQ
What does the ai-security-verification skill do?
Comprehensive AI security verification using OWASP AI Security Verification Standard (AISVS) framework. Use when verifying an AI-driven application, ML pipeline, or LLM-integrated system against AISVS, preparing for an AI security audit, or checking security and ethical controls across 13 categories from training data governance to human oversight.
How do I install ai-security-verification?
Run npx skills add https://github.com/owasp/secure-agent-playbook --skill ai-security-verification in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/ai-security-verification/ (personal) or .claude/skills/ai-security-verification/ (project).
Which AI agents can use ai-security-verification?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is ai-security-verification safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains ai-security-verification?
It is published by owasp in owasp/secure-agent-playbook. It has 129 recorded installs.
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