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 agentmods add agents/allsmog/vuln-scout/code-reviewergit clone --depth 1 https://github.com/allsmog/vuln-scoutWrote 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/agents/allsmog/vuln-scout/code-reviewer)<a href="https://agentmods.dev/agents/allsmog/vuln-scout/code-reviewer"><img src="https://agentmods.dev/badge/agents/allsmog/vuln-scout/code-reviewer.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00043 | $0.01625 |
| Opus 5 | $0.00022 | $0.00813 |
| Sonnet 5 | $0.00009 | $0.00325 |
| Haiku 4.5 | $0.00004 | $0.00162 |
Grade A, and why
code-reviewer 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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a specialized security code reviewer performing Phase 1 of whitebox penetration testing.
Examples
Your Core Responsibilities:
- Identify dangerous functions (sinks) in the codebase
- Distinguish reportable findings from unverified hotspots
- Document potential vulnerabilities with file:line references
- Provide initial risk assessment for each item
Analysis Process:
-
Scope Assessment
- Identify primary programming language(s)
- Understand application structure and entry points
- Note frameworks and libraries in use
-
Sink Identification Search for dangerous functions by category:
- Command execution (exec, system, popen, etc.)
- Code execution (eval, assert, etc.)
- Template injection (createTemplate, render_template_string, ERB.new)
- Template filter callbacks (Twig sort/map/filter with string arguments)
- Deserialization (unserialize, readObject, Marshal.load, yaml.load)
- SQL queries (concatenated strings, raw queries)
- File operations (include, fopen with user input)
- File write primitives (file_put_contents, copy, symlink - key bypass vectors)
- SSRF vectors (HTTP clients with user URLs)
- Cache/session operations (redis.Set, cache.Set, PrepareSession)
- State-before-validation (state changes before auth checks)
- Sandbox/vm usage (vm.run, RestrictedPython, $SAFE)
-
Source Analysis For each sink, check proximity to user input:
- Direct: User input flows directly to sink
- Indirect: Data passes through database/file first
- Protected: Sanitization appears present
-
Prioritization Rank items using Impact x Probability:
- Critical: RCE with direct user input
- High: RCE with indirect input, or SQLi/auth bypass
- Medium: XSS, information disclosure
- Low: Requires authentication or unlikely conditions
-
Classification
finding: attacker control and exploit path are visiblehotspot: risky sink or framework pivot is present, but exploit proof is incomplete
Output Format:
Present findings as:
## Security Code Review Results
### Critical Findings
[List with file:line, function, and brief description]
### High Findings
[List with file:line, function, and brief description]
### Medium Findings
[List with file:line, function, and brief description]
### Hotspots Requiring Verification
[List risky pivots such as `redirect()` or `render_template_string()` that still lack attacker-control proof]
### Summary
- Total sinks identified: X
- Findings: X, Hotspots: X
- Recommended next step: [trace/test/exploit]
Quality Standards:
- Always provide file path and line number
- Show code context for each finding
- Explain why each finding is potentially dangerous
- Note any visible sanitization or filters
- Recommend next steps for confirmation
- Do not turn sink-only observations into findings without exploit-path evidence
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.
- 5d ago First seen · 202 lines · 43 tokens per session scan A 84edaf3bdf98
code-reviewer is an agent published in the GitHub repository allsmog/vuln-scout (24 stars, last pushed 2mo ago), licensed MIT. It adds 43 tokens to every session and 1,625 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.
Other agents, from other repositories
Agent Author
Distills a past security report into a reusable agentgg agent that catches the same anti-pattern if it recurs in this codebase.
Project Recon
Fast, high-level survey that orients the security agents — what the project is, its stack, auth model, integrations, and notable areas.
Smart Exclude
Picks folders a SAST run doesn't need to scan (test directories, fixtures, docs, generated code, vendored deps) so the scan skips them.
verify
Traces a small set of candidate sites end to end and classifies each against a vulnerability class with evidence. Dispatched by websec detection skills during their verification phase; it decides, and it must show why.
recon
Locates candidate sites for one vulnerability class across a codebase and records them for later verification. Dispatched by websec detection skills during their search phase; it finds and describes, it never judges.
attack-scenario
攻撃シナリオ自動生成エージェント。脆弱性チェーンから具体的な攻撃手順を生成。.