llm-top-10
From the author
Reviews LLM-powered applications against the OWASP Top 10 for Large Language Model Applications (2025 edition). Auto-invoked when reviewing code that integrates LLM APIs, builds RAG pipelines, or deploys AI-powered features. Produces a structured findings report mapped to LLM01-LLM10 with severity ratings, CWE mappings, and prioritized remediation guidance.
Install
npx skills add UnitOneAI/SecuritySkills --skill llm-top-10 -a claude-code
Installs to .claude/skills/llm-top-10/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
Want your agent to suggest skills while you type? See how to use skills from your IDE.
Safety checks on SKILL.md
No warnings.
Why 78
aiqbench computes the trust score from public signals. It is not a security audit, so read a skill before you install it.
Similar skills
Closest to this one by what they do and when they are used.
- owasp-top-10-webUnitOneAI/SecuritySkillsReviews web applications against the OWASP Top 10:2021 vulnerability categories. Auto-invoked when reviewing web application code, server configurations, or when a user asks for a general security review of a web application. Produces structured findings mapped to A01-A10 with CWE references, severity ratings, and specific remediation guidance.Security★ 91
- owasp-securityagamm/claude-code-owaspReviews code for security vulnerabilities and guides secure implementation using OWASP Top 10:2025, ASVS 5.0, the OWASP Top 10 for LLM Applications (2026), and the OWASP Top 10 for Agentic Applications (2026). Use when reviewing code or a diff for security issues, implementing authentication, authorization, sessions, or cryptography, handling untrusted input, files, or URLs, hardening config, dependencies, or CI, or building LLM and AI agent features.Security★ 395
- 16-ai-llm-securityMasriyan/Claude-Code-CyberSecurity-SkillLLM and AI application security testing — prompt injection, jailbreak resistance, OWASP LLM Top 10 (2025), RAG and agent/tool-use security, model supply chain, and AI red teaming for authorized assessmentsSecurity★ 504
- prompt-injectionUnitOneAI/SecuritySkillsTests LLM applications for prompt injection vulnerabilities per OWASP LLM01:2025. Covers direct injection (user input manipulating model behavior) and indirect injection (external content containing hidden instructions). Auto-invoked when reviewing LLM applications that process external content, build RAG pipelines, or accept user input that reaches a language model. Produces a test report with categorized findings and defense recommendations.Security★ 91
- agentic-top-10UnitOneAI/SecuritySkillsReviews agentic AI systems against the OWASP Top 10 security risks for autonomous AI agents. Auto-invoked when reviewing multi-agent architectures, AI agent deployments, or systems where LLMs have tool access and act autonomously. Covers permission models, tool security, memory integrity, trust boundaries, and human oversight. Produces a structured assessment with risk ratings and architectural recommendations.Security★ 91
- ai-threat-testing26zl/cybersec-toolkitOffensive AI security testing and exploitation framework. Systematically tests LLM applications for OWASP Top 10 vulnerabilities including prompt injection, model extraction, data poisoning, and supply chain attacks. Integrates with pentest workflows to discover and exploit AI-specific threats.Testing★ 80
Ratings & reviews
—
no reviews
Tried this skill? Rate it to help others. Sign in
Discussion
Join the discussion. Sign in