Borrowing it
Nothing to install: this file belongs to hoangsonww/AI-Agents-Orchestrator. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/hoangsonww/AI-Agents-Orchestrator/main/.agents/skills/security-review/SKILL.mdgit clone --depth 1 https://github.com/hoangsonww/AI-Agents-OrchestratorWrote 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/hoangsonww/ai-agents-orchestrator/security-review)<a href="https://agentmods.dev/skills/hoangsonww/ai-agents-orchestrator/security-review"><img src="https://agentmods.dev/badge/skills/hoangsonww/ai-agents-orchestrator/security-review/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/hoangsonww/ai-agents-orchestrator/security-review"><img src="https://agentmods.dev/badge/skills/hoangsonww/ai-agents-orchestrator/security-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector 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 | $0.00031 | $0.00275 |
| Opus 5 | $0.00015 | $0.00138 |
| Sonnet 5 | $0.00006 | $0.00055 |
| Haiku 4.5 | $0.00003 | $0.00028 |
Grade A, and why
security-review scanned grade A with 0 findings 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 11d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Diff to review
Review the current branch changes against main:
git diff main...HEAD
If no diff is available, review the most recent commit:
git diff HEAD~1
Audit the changes for:
- Injection vulnerabilities — SQL injection, XSS, command injection via unsanitized input
- Authentication & authorization gaps — missing auth checks, broken RBAC, token handling issues
- Hardcoded secrets — API keys, passwords, tokens in source code
- Path traversal — unsanitized file paths that could escape intended directories
- Unsafe subprocess calls — raw subprocess without CLICommunicator, shell=True usage
- Dependency issues — known vulnerable packages, pinning concerns
Use the checklist in this skill directory
See references/checklist.md for the full security review checklist.
Report format
For each finding:
- Severity: Critical / High / Medium / Low
- File: path and line number
- Issue: what the vulnerability is
- Fix: concrete remediation steps
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.
- 11d ago First seen · 36 lines · 31 tokens per session scan A 12beb9ec6837
security-review is a skill published in the GitHub repository hoangsonww/AI-Agents-Orchestrator (84 stars, last pushed 3d ago), licensed MIT. It adds 31 tokens to every session and 275 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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