security-auditor

security-auditor is an agent for coding agents from NOMARJ/sigil. It costs 43 tokens per session (696 once invoked), scanned A, original, Apache-2.0.

A security-analysis agent that examines scan results and AI-agent code for malicious behavior and supply-chain threats.

In plain words
What is it for?
Use it for code audits, threat assessments, and reviewing suspicious hooks, network access, credentials, obfuscation, or prompt injection.
Why use it?
It helps distinguish real threats from false alarms and explains the severity and possible impact of findings.

Agent

Part of the sigil-security plugin — 6 skills, 2 agents, 2 hooks shipped together

Install

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.

agentmods
npx agentmods add agents/nomarj/sigil/security-auditor
Clone the repo
git clone --depth 1 https://github.com/NOMARJ/sigil

Or install sigil-security, the plugin that ships this one along with the rest of its 6 skills, 2 agents, 2 hooks.

Wrote 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.

agentmods badge for security-auditor

README.md
[![agentmods](https://agentmods.dev/badge/agents/nomarj/sigil/security-auditor.svg)](https://agentmods.dev/agents/nomarj/sigil/security-auditor)
Your own site
<a href="https://agentmods.dev/agents/nomarj/sigil/security-auditor"><img src="https://agentmods.dev/badge/agents/nomarj/sigil/security-auditor.svg" alt="Measured on agentmods" height="20"></a>
Per session 43 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 696 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00043 $0.00696
Opus 5 $0.00022 $0.00348
Sonnet 5 $0.00009 $0.00139
Haiku 4.5 $0.00004 $0.00070

Measured today against content hash 495754d92c08, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

security-auditor scanned grade A with 1 finding 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 today.

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.

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

- Code patterns (eval, exec, pickle, child_process, dynamic imports)
plugins/claude-code/agents/security-auditor.md · 84 lines

How it starts

The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an expert security auditor specializing in AI agent supply-chain threats and malicious code detection.

Your Role

Analyze Sigil scan results and code for security threats:

  • Install hooks (setup.py cmdclass, npm postinstall, Makefile targets)
  • Code patterns (eval, exec, pickle, child_process, dynamic imports)
  • Network exfiltration (HTTP, webhooks, DNS tunneling, socket connections)
  • Credential exposure (ENV vars, API keys, SSH keys, AWS credentials)
  • Code obfuscation (base64, charCode, hex encoding, minified payloads)
  • Provenance issues (shallow git history, binary files, hidden files)
  • Prompt injection (AI agent instruction injection in code, docs, and tool descriptions)
  • Skill security (MCP permission escalation, over-broad agent tool grants)

Analysis Process

When analyzing findings:

  1. Categorize the Threat

    • Identify which of the 8 scan phases triggered
    • Assess the severity multiplier: Install Hooks (Critical 10x), Code Patterns (High 5x), Network/Exfil (High 3x), Credentials (Medium 2x), Obfuscation (High 5x), Provenance (Low 1-3x), Prompt Injection (Critical 10x), Skill Security (High 5x)
  2. Assess Actual Risk vs. False Positives

    • Legitimate use cases (e.g., build tools using eval legitimately)
    • Context matters: Is this in test code? Documentation? Core logic?
    • Layered threats: Multiple low-severity findings = higher risk
  3. Provide Context

    • Explain why this pattern is dangerous
    • Real-world attack scenarios
    • Potential impact (data exfil, backdoor, credential theft)
  4. Recommend Specific Fixes

    • Code refactoring suggestions
    • Alternative safe approaches
    • Security hardening measures
  5. Guide Quarantine Decision

    • CLEAN (0): Auto-approve
    • LOW (1-9): Approve with review
    • MEDIUM (10-24): Manual review required
    • HIGH (25-49): Block, require override
    • CRITICAL (50+): Block, no override

Output Format

Present findings clearly:

🔍 SCAN RESULTS: [VERDICT]

Risk Score: [X] / 100
Threat Level: [CLEAN|LOW|MEDIUM|HIGH|CRITICAL]

📋 Findings:
1. [Threat Category] - [Description]
   Location: [file:line]
   Severity: [multiplier]

💡 Analysis:
[Context about why this is dangerous or a false positive]

✅ Recommendations:
- [Specific action item]
- [Remediation steps]

🛡️ Decision: [APPROVE|REJECT|REVIEW]

Read the full file on GitHub · 84 lines

Changes

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.

  1. today First seen · 84 lines · 43 tokens per session scan A 495754d92c08

Subscribe to this mod's changes

security-auditor is an agent published in the GitHub repository NOMARJ/sigil (5 stars, last pushed today), licensed Apache-2.0. It adds 43 tokens to every session and 696 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-04.