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Use when reviewing code for security vulnerabilities, implementing authentication/authorization, handling user input, or discussing web application security. Covers OWASP Top 10:2025, ASVS 5.0, LLM Top 10 (2025), and Agentic AI security (2026).
Passed 20 of 22 test cases with the skill, and 9 of 22 without it.
and 10 more in the full report
11 fixed9 passed either way2 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 11 test cases the skill fixed. Same model, same prompt, with and without the skill.
In an agentic AI system where an untrusted document overrides the core system objective of an autonomous web-browsing agent, which OWASP Agentic Top 10 (2026) category code and title applies?
| Checked | Without skill | With skill |
|---|---|---|
| Cites ASI01 Agent Goal Hijack as the applicable risk category. | Missed | Passed |
The instructions your model reads when the skill loads.
Apply these standards when writing or reviewing code. For a review, follow the workflow below.
Reference files (read the one the task needs, and only the section you need):
reference/review-checklist.md: coverage checklist for every Top 10 category, plus LLM and agent checks. Read during step 3 of a review.reference/languages.md: per-language pitfalls with unsafe/safe examples for 20+ languages. Read the section for the language under review.reference/config-and-supply-chain.md: A02 and A03 in Dockerfiles, Kubernetes, Terraform, framework config, security headers, lockfiles, and CI/CD. Read when the change touches config, IaC, dependencies, or pipelines.reference/owasp-report.md: attack vectors, mitigations, and worked examples for every Top 10:2025, ASVS 5.0, LLM Top 10, and Agentic item. About 1100 lines: jump to the section you need.Copy this checklist into your response and tick it off as you go:
Security Review Progress:
- [ ] Step 1: Map entry points and trust boundaries
- [ ] Step 2: Load the references this code needs
- [ ] Step 3: Sweep for candidate issues
- [ ] Step 4: Triage every candidate
- [ ] Step 5: Report findings
Step 1: Map entry points and trust boundaries. List where attacker-controlled data enters: routes and handlers, headers and cookies, uploads, webhooks, queue consumers, CLI arguments, third-party API responses, and anything an LLM reads or returns. Note where authentication and authorization are enforced; it is often centralized in middleware rather than per route.
Step 2: Load the references this code needs. The language section of languages.md;
config-and-supply-chain.md if config, IaC, dependencies, or CI changed; the LLM and Agentic
sections of owasp-report.md if the code calls a model or runs an agent.
Step 3: Sweep for candidate issues. Walk review-checklist.md for the categories the code
touches. For each candidate, trace the path from an entry point in step 1 to the sink.
Step 4: Triage every candidate with the rubric in "Before Reporting a Finding" below. Drop candidates that fail it, or downgrade them to defense-in-depth. If a candidate's reachability is unclear, go back to step 1 for that input before deciding.
Step 5: Report findings in the format below, highest severity first.
test cases passed, vs 9 / 22 without
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