Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add mastepanoski/claude-skills --skill owasp-llm-top10git clone --depth 1 https://github.com/mastepanoski/claude-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mastepanoski/claude-skills/owasp-llm-top10)<a href="https://agentmods.dev/skills/mastepanoski/claude-skills/owasp-llm-top10"><img src="https://agentmods.dev/badge/skills/mastepanoski/claude-skills/owasp-llm-top10/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mastepanoski/claude-skills/owasp-llm-top10"><img src="https://agentmods.dev/badge/skills/mastepanoski/claude-skills/owasp-llm-top10.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00048 | $0.02051 |
| Opus 5.5 | $0.00019 | $0.00820 |
| Sonnet 5.5 | $0.00010 | $0.00410 |
| Haiku 4.5 | $0.00005 | $0.00205 |
Grade B, and why
owasp-llm-top10 scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 17d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Instruction-override phrasingmediumPrompt injection
Text telling the model to disregard its earlier instructions or safety rules is the shape of a prompt injection, whoever wrote it.
- [ ] Attempt to override system instructions Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
How it starts
The opening of the file, as written. The whole thing — 213 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OWASP Top 10 for LLM Applications Security Audit
This skill enables AI agents to perform a comprehensive security assessment of Large Language Model (LLM) and Generative AI applications using the OWASP Top 10 for LLM Applications 2025, published by the OWASP GenAI Security Project.
The OWASP Top 10 for LLM Applications identifies the most critical security risks in systems that integrate large language models, covering vulnerabilities from prompt injection to unbounded resource consumption. This is the authoritative industry standard for LLM application security.
Use this skill to identify security vulnerabilities, assess risk exposure, prioritize remediation, and establish secure development practices for AI-powered applications.
Combine with "NIST AI RMF" for comprehensive risk management or "ISO 42001 AI Governance" for governance compliance.
When to Use This Skill
Invoke this skill when:
- Auditing security of LLM-powered applications before deployment
- Reviewing GenAI integrations for security vulnerabilities
- Assessing RAG (Retrieval-Augmented Generation) systems
- Evaluating chatbot or AI assistant security
- Conducting penetration testing of AI features
- Building secure AI application architectures
- Reviewing third-party AI API integrations
- Preparing for security compliance reviews
- Responding to AI-related security incidents
Inputs Required
When executing this audit, gather:
- application_description: Description of the AI application (purpose, LLM used, architecture, features, user base) [REQUIRED]
- architecture_details: System architecture (APIs, databases, vector stores, plugins, integrations) [OPTIONAL but recommended]
- llm_provider: LLM provider and model (OpenAI GPT-4, Anthropic Claude, self-hosted, etc.) [OPTIONAL]
- deployment_context: Deployment environment (cloud, on-premise, hybrid, edge) [OPTIONAL]
- data_sensitivity: Types of data processed (PII, financial, health, proprietary) [OPTIONAL]
- existing_controls: Current security measures (auth, rate limiting, content filtering) [OPTIONAL]
- specific_concerns: Known vulnerabilities or areas of focus [OPTIONAL]
- testing_authorization: Explicit authorization, environment, and boundaries for active testing [REQUIRED for live or active tests]
- safe_testing_mode: documentation-only, staging, production-readonly, or production-approved [OPTIONAL, defaults to documentation-only unless authorization is clear]
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 17d ago Changed · -493 lines 8c9a291beff4
- 1mo ago First seen · 706 lines · 48 tokens per session scan B f5e1c54e6aa6
owasp-llm-top10 is a skill published in the GitHub repository mastepanoski/claude-skills (59 stars, last pushed 17d ago), licensed MIT. It adds 48 tokens to every session and 2,051 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it B with 1 finding (instruction-override phrasing). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
agent-config
Use when writing or editing agent configuration, especially permission rules in settings.json, skills, hooks, or MCP servers. Covers the permission-matching behaviour that makes a rule grant more than it reads, and how to check configuration with agentfile.
chinese-documentation
A Chinese technical-documentation style guide covering spacing, punctuation, numbers, terminology, and links when Chinese and English appear together.
systematic-debugging
A step-by-step method for finding the underlying cause of technical problems before changing code. It covers reading errors, reproducing failures, checking recent changes, and tracing data across system components.
contract-builder
Maintain an execution contract only for an existing legacy change that requires one. New direct/planned changes do not invoke this skill when a contract is absent.
code-reviewer
Review completed implementation batches for spec compliance and code quality. Invoke after execution batches complete, before merging, or when a review gate is reached in the workflow.
workflow-start
Primary entry point for the spec-superflow state-machine workflow. Invoke only when the user explicitly requests spec-superflow or an active change contains .spec-superflow.yaml and the user asks to continue that change. Generic proposal, specs, design, task, or contract files are not activation signals.