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owasp/secure-agent-playbook117 installs

llm-risk-assess

Comprehensive LLM security assessment against OWASP Top 10 for LLM Applications 2025. Use when reviewing LLM-integrated applications, RAG pipelines, chatbots, AI agents, or GenAI features. Covers prompt injection, data poisoning, supply chain, excessive agency, and more with real-world attack scenarios and testing methodologies.

How do I install this agent skill?

npx skills add https://github.com/owasp/secure-agent-playbook --skill llm-risk-assess
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubpass

    The skill provides a legitimate framework for performing LLM security assessments based on OWASP standards. While the content is safe and educational, the assessment process inherently involves ingesting untrusted data from target applications, which creates a potential surface for indirect prompt injection.

  • Socketwarn

    1 alert: gptSecurity

  • Snykpass

    Risk: LOW · No issues

What does this agent skill do?

LLM Risk Assessment (2025)

Comprehensive evaluation of LLM applications against OWASP Top 10 for LLM Applications 2025. Follow the detailed procedure in plays/llm-risk-assess.md.

Steps

  1. Architecture & Threat Modeling

    • Map LLM provider (OpenAI, Anthropic, local models)
    • Document data flows: user input → preprocessing → prompt construction → LLM → output processing → actions
    • Identify RAG components, tool integrations, memory systems
    • Define trust boundaries and attack surfaces
  2. Automated Security Testing

    • Run prompt injection probes (Garak, Giskard, custom scripts)
    • Test output handling vulnerabilities
    • Scan for secrets in prompts and configurations
    • Validate vector database security
  3. Assess All 10 OWASP LLM 2025 Risks with attack scenarios:

    • LLM01 Prompt Injection — Direct/indirect injection, jailbreaks, goal hijacking, delimiter bypasses
    • LLM02 Sensitive Information Disclosure — Training data leakage, PII exposure, system info extraction, memorized secrets
    • LLM03 Supply Chain — Model poisoning, malicious dependencies, insecure plugins, provenance issues
    • LLM04 Data and Model Poisoning — Training data poisoning, RAG poisoning, embedding manipulation
    • LLM05 Improper Output Handling — XSS, command injection, SQLi, path traversal via LLM outputs
    • LLM06 Excessive Agency — Unauthorized tool calls, permission escalation, dangerous action chains
    • LLM07 System Prompt Leakage — Prompt extraction attacks, secret disclosure, instruction reverse engineering
    • LLM08 Vector and Embedding Weaknesses — Adversarial embeddings, retrieval poisoning, similarity attacks
    • LLM09 Misinformation — Hallucinations, authoritative presentation, grounding failures, harmful domains
    • LLM10 Unbounded Consumption — Token exhaustion, cost attacks, resource exhaustion, DoS
  4. Red Team Testing

    • Attempt real-world attack scenarios
    • Test defense bypasses and evasion techniques
    • Validate guardrails and safety controls

Output

Comprehensive LLM security report:

  • Architecture diagram with trust boundaries
  • Risk matrix (all 10 categories with severity/status)
  • Detailed findings with proof-of-concept examples
  • Red team test results and bypass techniques
  • Remediation roadmap with code examples
  • Defense validation checklist

OWASP References

  • OWASP Top 10 for LLM Applications 2025
  • OWASP AI Exchange (owaspai.org)
  • OWASP AI Testing Guide
  • OWASP Cheat Sheet: Prompt Injection Prevention
  • OWASP Prompt Injection Taxonomy (Arcanum)

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

<a href="https://skillzs.dev/skills/owasp/secure-agent-playbook/llm-risk-assess">View llm-risk-assess on skillZs</a>