Sail
pillar-labs/sail-skill
Apply the SAIL (Secure AI Lifecycle) V2 framework by Pillar Security to secure AI applications and agents.
Comprehensive AI security verification using OWASP AI Security Verification Standard (AISVS) framework.
Install AI Security Verification
$ npx skills add OWASP/secure-agent-playbook --skill ai-security-verification -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install OWASP/secure-agent-playbook ai-security-verification --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/OWASP/secure-agent-playbook.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/ai-security-skills/skills/ai-security-verification .claude/skills/ai-security-verification && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "ai-security-verification" agent skill from https://github.com/OWASP/secure-agent-playbook/tree/main/plugins/ai-security-skills/skills/ai-security-verification into .claude/skills/ai-security-verification/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-security-verification", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/OWASP/secure-agent-playbook/tree/main/plugins/ai-security-skills/skills/ai-security-verificationType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add OWASP/secure-agent-playbook --skill ai-security-verification -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install OWASP/secure-agent-playbook ai-security-verification --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OWASP/secure-agent-playbook.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/ai-security-skills/skills/ai-security-verification .agents/skills/ai-security-verification && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ai-security-verification" agent skill from https://github.com/OWASP/secure-agent-playbook/tree/main/plugins/ai-security-skills/skills/ai-security-verification into .agents/skills/ai-security-verification/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-security-verification", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add OWASP/secure-agent-playbook --skill ai-security-verification -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install OWASP/secure-agent-playbook ai-security-verification --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OWASP/secure-agent-playbook.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/ai-security-skills/skills/ai-security-verification .cursor/skills/ai-security-verification && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "ai-security-verification" agent skill from https://github.com/OWASP/secure-agent-playbook/tree/main/plugins/ai-security-skills/skills/ai-security-verification into .cursor/skills/ai-security-verification/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-security-verification", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/OWASP/secure-agent-playbook.git --path plugins/ai-security-skills/skills/ai-security-verification--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add OWASP/secure-agent-playbook --skill ai-security-verification -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install OWASP/secure-agent-playbook ai-security-verification --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OWASP/secure-agent-playbook.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/ai-security-skills/skills/ai-security-verification .gemini/skills/ai-security-verification && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "ai-security-verification" agent skill from https://github.com/OWASP/secure-agent-playbook/tree/main/plugins/ai-security-skills/skills/ai-security-verification into .gemini/skills/ai-security-verification/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-security-verification", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install OWASP/secure-agent-playbook ai-security-verificationInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add OWASP/secure-agent-playbook --skill ai-security-verification -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/OWASP/secure-agent-playbook.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/ai-security-skills/skills/ai-security-verification .github/skills/ai-security-verification && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "ai-security-verification" agent skill from https://github.com/OWASP/secure-agent-playbook/tree/main/plugins/ai-security-skills/skills/ai-security-verification into .github/skills/ai-security-verification/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-security-verification", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add OWASP/secure-agent-playbook --skill ai-security-verification -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install OWASP/secure-agent-playbook ai-security-verification --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OWASP/secure-agent-playbook.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/ai-security-skills/skills/ai-security-verification .opencode/skills/ai-security-verification && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "ai-security-verification" agent skill from https://github.com/OWASP/secure-agent-playbook/tree/main/plugins/ai-security-skills/skills/ai-security-verification into .opencode/skills/ai-security-verification/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-security-verification", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
ai-security-verification- GitHub stars
- 187
- Token cost
- ~876 tokens
- SKILL.md length
- 332 words
- Files
- 1
- Skills in repo
- 14
- Repo updated
- First seen
- Licence
- CC-BY-4.0
At a glance
Comprehensive AI security verification using OWASP AI Security Verification Standard (AISVS) framework.
- Works in 12 steps: Training Data Governance & Bias… → User Input Validation — Evaluate input… → Model Lifecycle Management & Change… → …
- Verifying an AI-driven application
- SKILL.md covers Steps, Output and OWASP References
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
AI Security Verification is an agent skill from OWASP/secure-agent-playbook. 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.
Its SKILL.md is about 880 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Security, covering Prompt injection and agent security and Web application vulnerabilities. The repository describes itself as: OWASP Secure Agent Playbook Project. The licence is CC-BY-4.0.
When your agent uses it
- Verifying an AI-driven application
- LLM-integrated system against AISVS
- Preparing for an AI security audit
- Checking security and ethical controls across 13 categories from training data governance to human oversight
Example prompts
- “/ai-security-verification”
Workflow steps
12 steps, taken from the first numbered list in SKILL.md.
- Training Data Governance & Bias Management — Assess data quality, provenance, bias detection, and governance controls throughout the data…
- User Input Validation — Evaluate input sanitization, prompt injection defenses, adversarial input detection, and boundary validation…
- Model Lifecycle Management & Change Control — Review model versioning, deployment controls, rollback capabilities, and change management…
- Infrastructure, Configuration & Deployment Security — Examine deployment security, container hardening, network controls, and…
- Access Control & Identity — Verify authentication mechanisms, authorization controls, privilege management, and identity governance.
- Supply Chain Security for Models, Frameworks & Data — Assess third-party model security, dependency management, and supply chain integrity.
- Model Behavior, Output Control & Safety Assurance — Evaluate output validation, safety guardrails, behavior monitoring, and harmful…
- Memory, Embeddings & Vector Database Security — Review vector database security, embedding protection, memory isolation, and context…
- Autonomous Orchestration & Agentic Action Security — Assess agent coordination security, tool access controls, and autonomous…
- Adversarial Robustness & Attack Resistance — Test resilience against adversarial examples, evasion attacks, and model extraction attempts.
- Privacy Protection & Personal Data Management — Verify privacy controls, data minimization, consent management, and regulatory compliance.
- Monitoring, Logging & Anomaly Detection — Evaluate security monitoring, audit logging, anomaly detection, and incident response…
What it can do on your machine
Read from SKILL.md and the folder at commit 1b5fd4c. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
AI Security Verification loads about 876 tokens when it runs. Until then it costs about 94 tokens; SKILL.md has 332 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from OWASP/secure-agent-playbook at commit 1b5fd4c, republished under its CC-BY-4.0 licence (© OWASP). 332 words, ~876 tokens.
Download SKILL.mdSave it as
.claude/skills/ai-security-verification/SKILL.md (or your agent's skills folder).- name
- ai-security-verification
- description
- 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.
- license
- CC-BY-4.0
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
Training Data Governance & Bias Management — Assess data quality, provenance, bias detection, and governance controls throughout the data lifecycle.
User Input Validation — Evaluate input sanitization, prompt injection defenses, adversarial input detection, and boundary validation mechanisms.
Model Lifecycle Management & Change Control — Review model versioning, deployment controls, rollback capabilities, and change management processes.
Infrastructure, Configuration & Deployment Security — Examine deployment security, container hardening, network controls, and infrastructure configuration.
Access Control & Identity — Verify authentication mechanisms, authorization controls, privilege management, and identity governance.
Supply Chain Security for Models, Frameworks & Data — Assess third-party model security, dependency management, and supply chain integrity.
Model Behavior, Output Control & Safety Assurance — Evaluate output validation, safety guardrails, behavior monitoring, and harmful content prevention.
Memory, Embeddings & Vector Database Security — Review vector database security, embedding protection, memory isolation, and context management.
Autonomous Orchestration & Agentic Action Security — Assess agent coordination security, tool access controls, and autonomous decision-making safeguards.
Adversarial Robustness & Attack Resistance — Test resilience against adversarial examples, evasion attacks, and model extraction attempts.
Privacy Protection & Personal Data Management — Verify privacy controls, data minimization, consent management, and regulatory compliance.
Monitoring, Logging & Anomaly Detection — Evaluate security monitoring, audit logging, anomaly detection, and incident response capabilities.
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
© OWASP, CC-BY-4.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in plugins/ai-security-skills/skills/ai-security-verification of OWASP/secure-agent-playbook.
Open the folder on GitHubat commit 1b5fd4c
Compare with similar skills
AI Security Verification next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| AI Security Verification this skillOWASP/secure-agent-playbook | 187 | — | ~876 | Automated safety check: Pass | CC-BY-4.0 | |
| Sailpillar-labs/sail-skill | 113 | — | ~5.1k | Automated safety check: Pass | Custom licence | |
| Agent Tool Abuse DetectionTencent/AI-Infra-Guard | 6.8k | — | ~1.5k | Automated safety check: Notes | Apache-2.0 | |
| Secureclawadversa-ai/secureclaw | 347 | 1 repos | ~193 | Automated safety check: Pass | MIT | |
| Csono-session/pstack | 135 | — | ~12k | Automated safety check: Notes | MIT | |
| AI LLM Agent Securityzhaji2333/CkSKILLS | 114 | — | ~4.7k | Automated safety check: Warn | MIT |
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Related
Categories
Questions about AI Security Verification
What does AI Security Verification do?
Comprehensive AI security verification using OWASP AI Security Verification Standard (AISVS) framework. AI Security Verification is an agent skill from OWASP/secure-agent-playbook. Comprehensive AI security verification using OWASP AI Security Verification Standard (AISVS) framework.
When should I use AI Security Verification?
AI Security Verification fits situations like: verifying an AI-driven application; LLM-integrated system against AISVS; preparing for an AI security audit; checking security and ethical controls across 13 categories from training data governance to human oversight.
How do I install AI Security Verification in Claude Code?
Run `npx skills add OWASP/secure-agent-playbook --skill ai-security-verification -a claude-code`. Or copy the skill folder (plugins/ai-security-skills/skills/ai-security-verification in OWASP/secure-agent-playbook) into .claude/skills/ai-security-verification in your project. Claude Code loads it when a task matches its description.
How do I install AI Security Verification in Codex?
Run `npx skills add OWASP/secure-agent-playbook --skill ai-security-verification -a codex`. Or copy the skill folder (plugins/ai-security-skills/skills/ai-security-verification in OWASP/secure-agent-playbook) into .agents/skills/ai-security-verification in your project. Codex loads it when a task matches its description.
Can I use AI Security Verification in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add OWASP/secure-agent-playbook --skill ai-security-verification -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ai-security-verification, .gemini/skills/ai-security-verification, .github/skills/ai-security-verification and .opencode/skills/ai-security-verification in your project.
What does AI Security Verification need to run?
SKILL.md names no scripts, command-line tools or credentials: AI Security Verification is instructions for the agent only.
Does AI Security Verification access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is AI Security Verification safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does AI Security Verification use?
AI Security Verification is published under the CC-BY-4.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does AI Security Verification use?
About 876 tokens (SKILL.md is roughly 3.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to AI Security Verification?
Skills that share tags, products or a category with AI Security Verification: Sail (pillar-labs/sail-skill, 113 stars), Agent Tool Abuse Detection (Tencent/AI-Infra-Guard, 6.8k stars), Secureclaw (adversa-ai/secureclaw, 347 stars) and Cso (no-session/pstack, 135 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains AI Security Verification?
OWASP (a GitHub organization) maintains it in OWASP/secure-agent-playbook, which has 187 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on September 25, 2026.
Source: OWASP/secure-agent-playbook on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.