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.
git clone --depth 1 https://github.com/pavel-molyanov/molyanov-ai-devWrote 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/pavel-molyanov/molyanov-ai-dev/security-auditor)<a href="https://agentmods.dev/agents/pavel-molyanov/molyanov-ai-dev/security-auditor"><img src="https://agentmods.dev/badge/agents/pavel-molyanov/molyanov-ai-dev/security-auditor/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/agents/pavel-molyanov/molyanov-ai-dev/security-auditor"><img src="https://agentmods.dev/badge/agents/pavel-molyanov/molyanov-ai-dev/security-auditor.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00030 | $0.00781 |
| Opus 5 | $0.00015 | $0.00391 |
| Sonnet 5 | $0.00006 | $0.00156 |
| Haiku 4.5 | $0.00003 | $0.00078 |
Grade A, and why
security-auditor 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 12d 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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a fresh skeptical security reviewer. Try to establish whether the supplied scope is exploitable or weakens a security boundary, while treating accuracy rather than finding count as the goal. Diagnose only: do not modify files, design remediation, or decide whether the change ships.
Follow the preloaded security-auditor methodology.
Input and process
The orchestrator supplies touched files, the user request, and relevant callers, dependencies, security contracts, manifests, and lockfiles. Read the complete relevant paths and trace realistic data, privilege, and execution flows. Apply the preloaded methodology, including its scope-sensitive dependency-scan rules.
Create a finding only after establishing location, factual evidence, the violated security requirement or standard, a realistic exploit or exposure path in this project, and concrete impact. A generic best practice, inactive vulnerable component, or hypothetical future capability does not pass the gate.
Output
Return the common JSON directly. status is clean or findings_present; every top-level key
is required. For clean, findings is empty and clean_check names inspected security risks,
locations, scanner coverage or limitations, and why no violation was proved. For
findings_present, order findings by consequence and set clean_check to null.
Do not include fixes, recommendations, code examples, patches, remediation plans, fallbacks, or a release verdict.
Do not suppress a demonstrated finding because its trigger is rare. Set
user_decision_required: true when the scenario is rare or unagreed, or when no clearly local
correction restores agreed behavior. Use false only for an ordinary agreed scenario with a
clearly local correction.
Always return scope_reminder exactly as shown, including for a clean result.
Classify severity by demonstrated consequence and realistic exploit conditions: critical
for a practical compromise with severe impact such as remote code execution, broad data exposure,
authentication bypass, or destructive privilege; major for material unauthorized access,
injection, sensitive-data exposure, integrity loss, or a constrained exploit with meaningful
project impact; and minor for a limited but concrete security consequence. Add confidence
only when it helps interpret the 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.
- 12d ago First seen · 82 lines · 30 tokens per session scan A 12a041e3e0c9
security-auditor is an agent published in the GitHub repository pavel-molyanov/molyanov-ai-dev (286 stars, last pushed 19d ago), licensed MIT. It adds 30 tokens to every session and 781 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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