How do I install the Common LLM Security skill?

Run npx skillmds@latest add comeonoliver/common-llm-security in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Common LLM Security safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Common LLM Security?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Common LLM Security free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Common LLM Security?

ComeOnOliver (@comeonoliver) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Common LLM Security by comeonoliver

Name: Common LLM Security
Rating: 4.2 (5 reviews)
Author: ComeOnOliver

Common LLM Security

OWASP LLM Top 10 (2025) audit checklist for AI applications, agent tools, RAG pipelines, and prompt construction. Load during any security review touching LLM client code, prompt templates, agent tools, or vector stores. (triggers: LLM security, prompt injection, agent security, RAG security, AI security, openai, anthropic, langchain, LLM review)

ComeOnOliver Updated Sep 8, 2026 61 repo stars

File contents

OWASP LLM Top 10 Security Checklist (2025)

Priority: P0 (CRITICAL)

Implementation Guidelines

Check LLM01 first: Prompt injection is the #1 LLM finding — any user input concatenated directly into a prompt string is an immediate P0.
Check LLM06 next: Agent tools with write/delete/execute capabilities without confirmation are P0.
Mark each item: ✅ not affected | ⚠️ needs review | 🔴 confirmed finding.
P0 finding caps Security score at 40/100 — do not skip any item.
See references/owasp-llm.md for full detection signals.

OWASP LLM Top 10 (2025)

ID	Risk	Key Detection Signal
LLM01	Prompt Injection	User input string-concatenated into prompt. Retrieved docs inserted into system turn.
LLM02	Sensitive Information Disclosure	PII or credentials passed into prompt context. LLM response logged without redaction.
LLM03	Supply Chain	Unverified model weights or plugins. Third-party agent added without trust review.
LLM04	Data & Model Poisoning	User-controlled data written to training sets or embedding stores without validation.
LLM05	Improper Output Handling	LLM output used directly in DOM sink, SQL query, shell command, or redirect URL.
LLM06	Excessive Agency	Agent tool with write/delete/network access — no human-in-the-loop confirmation.
LLM07	System Prompt Leakage	System prompt content returned via tool output, error message, or API response.
LLM08	Vector & Embedding Weaknesses	User text injected into vector store without sanitization. No tenant namespace isolation.
LLM09	Misinformation	LLM output used for critical decisions (medical, financial, legal) without verification.
LLM10	Unbounded Consumption	No `max_tokens` on LLM call. No rate limit on invocations. Agent loop without depth cap.

Anti-Patterns

No prompt concat: Pass user input as a separate user turn, never interpolated into system prompts.
No raw LLM output in sinks: Sanitize LLM responses before writing to DOM, queries, or shell.
No uncapped agent loops: Every agentic recursion must enforce a max iteration/depth limit.

References

OWASP LLM — Full Detection Signals — load when auditing any LLM client code

---name: common-llm-securitydescription: OWASP LLM Top 10 (2025) audit checklist for AI applications, agent tools, RAG pipelines, and prompt construction. Load during any security review touching LLM client code, prompt templates, agent tools, or vector stores. (triggers: LLM security, prompt injection, agent security, RAG security, AI security, openai, anthropic, langchain, LLM review)---# OWASP LLM Top 10 Security Checklist (2025)## **Priority: P0 (CRITICAL)**## Implementation Guidelines- **Check LLM01 first**: Prompt injection is the #1 LLM finding — any user input concatenated directly into a prompt string is an immediate P0.- **Check LLM06 next**: Agent tools with write/delete/execute capabilities without confirmation are P0.- **Mark each item**: ✅ not affected | ⚠️ needs review | 🔴 confirmed finding.- **P0 finding caps Security score at 40/100** — do not skip any item.- See [references/owasp-llm.md](references/owasp-llm.md) for full detection signals.## OWASP LLM Top 10 (2025)| ID | Risk | Key Detection Signal || ----- | ---- | -------------------- || LLM01 | Prompt Injection | User input string-concatenated into prompt. Retrieved docs inserted into system turn. || LLM02 | Sensitive Information Disclosure | PII or credentials passed into prompt context. LLM response logged without redaction. || LLM03 | Supply Chain | Unverified model weights or plugins. Third-party agent added without trust review. || LLM04 | Data & Model Poisoning | User-controlled data written to training sets or embedding stores without validation. || LLM05 | Improper Output Handling | LLM output used directly in DOM sink, SQL query, shell command, or redirect URL. || LLM06 | Excessive Agency | Agent tool with write/delete/network access — no human-in-the-loop confirmation. || LLM07 | System Prompt Leakage | System prompt content returned via tool output, error message, or API response. || LLM08 | Vector & Embedding Weaknesses | User text injected into vector store without sanitization. No tenant namespace isolation. || LLM09 | Misinformation | LLM output used for critical decisions (medical, financial, legal) without verification. || LLM10 | Unbounded Consumption | No `max_tokens` on LLM call. No rate limit on invocations. Agent loop without depth cap. |## Anti-Patterns- **No prompt concat**: Pass user input as a separate `user` turn, never interpolated into system prompts.- **No raw LLM output in sinks**: Sanitize LLM responses before writing to DOM, queries, or shell.- **No uncapped agent loops**: Every agentic recursion must enforce a max iteration/depth limit.## References- [OWASP LLM — Full Detection Signals](references/owasp-llm.md) — load when auditing any LLM client code

Frequently asked questions