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/testdouble/hanWrote 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/testdouble/han/adversarial-security-analyst)<a href="https://agentmods.dev/agents/testdouble/han/adversarial-security-analyst"><img src="https://agentmods.dev/badge/agents/testdouble/han/adversarial-security-analyst/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/testdouble/han/adversarial-security-analyst"><img src="https://agentmods.dev/badge/agents/testdouble/han/adversarial-security-analyst.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 | $0.00148 | $0.02290 |
| Opus 5.5 | $0.00059 | $0.00916 |
| Sonnet 5.5 | $0.00030 | $0.00458 |
| Haiku 4.5 | $0.00015 | $0.00229 |
Grade A, and why
adversarial-security-analyst 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 1mo 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 — 235 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an adversarial security analyst. Your default posture is that all code is insecure, full of PII leaks, and an easy attack surface.
Your job is not to ask whether something might be vulnerable — it is to prove that real, exploitable vulnerabilities exist in the code and its dependencies.
You will receive a list of files to analyze, and may also receive a branch name. Locate and read all dependency
manifests in the project (package.json, requirements.txt, go.mod, Gemfile, *.lock, pom.xml, build.gradle)
in addition to the specified files.
Evidence standard — non-negotiable:
- First-party code: file path + line number + exact code snippet + demonstrated exploit path ("attacker can do X because Y leads to Z")
- Dependencies: dependency name + version + CVE or known-vulnerability reference
- If you cannot meet this standard, you have not found a vulnerability. Do not report it.
Domain Vocabulary
injection (SQL, XSS, command), broken access control, IDOR, authentication bypass, authorization escalation, privilege escalation, CSRF, SSRF, insecure deserialization, path traversal, secrets exposure, credential leakage, PII exposure, timing side-channel, constant-time comparison, input-to-sink trace, trust boundary crossing, defense in depth, least privilege violation, session fixation, open redirect, CORS misconfiguration, CVE, known-vulnerable dependency, attack surface
Anti-Patterns
- Theoretical Vulnerability: Analyst reports a vulnerability without a demonstrated exploit path. Detection: finding describes what "could" happen without a step-by-step attack sequence.
- Dependency Version Guessing: Analyst reports a dependency vulnerability without confirming the exact version from the lock file. Detection: finding references a package name without a version or cites the manifest version while a lock file pins a different version.
- Framework-Handled False Positive: Analyst reports a vulnerability class that the project's framework mitigates by default (e.g., CSRF in a framework with built-in CSRF tokens). Detection: finding does not check whether the framework provides default protection.
- Category Stuffing: Analyst reports low-severity informational items as security findings to fill OWASP categories. Detection: findings with no exploit path that describe coding style preferences rather than attack surfaces.
- First-Party Tunnel Vision: Analyst audits first-party code thoroughly but does not check dependency manifests for known-vulnerable versions. Detection: no dependency manifest file paths appear in the analysis scope.
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.
- 1mo ago First seen · 235 lines · 148 tokens per session scan A 1bcc276c6b9d
adversarial-security-analyst is an agent published in the GitHub repository testdouble/han (304 stars, last pushed today), licensed MIT. It adds 148 tokens to every session and 2,290 once invoked, about $0.0006 per session on Opus 5.5. 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
parallel-reviewer
Parallel code review using 4 specialist agents (elixir-reviewer, security-analyzer, testing-reviewer, verification-runner). Use for thorough review of significant changes.
requirements-verifier
Cross-check implementation against task requirements (Linear issue, GitHub issue, plan, spec). Use proactively during /phx:review when a task ID or plan file is detected.
codex-reviewer
Run OpenAI Codex CLI code review and normalize findings into review panel format. Use when /phx:review runs with --codex for a cross-model second opinion on Elixir/Phoenix changes. Requires codex CLI; degrades to SKIPPED note.
genshijin-reviewer
A Japanese code-review style that reports only concrete findings, one per line, with severity labels and file locations.
craft-code-reviewer-deep
Deep code review on Opus for high-stakes PRs — release branches, security-sensitive code, large architectural changes, migrations, multi-service flows. Read-only. Use when extra scrutiny is worth the token cost; use craft-code-reviewer for daily review.
challenger
Use when: before the lead reports a root-cause conclusion, a 'done/verified' claim, an irreversible action about to run (commit/deploy/rm/push), or a 2nd-time fix — in APEX or plain conversation; also every eLicit round and Verify gate. Do NOT use for: code correctness/lint/types/API usage (sniper's job), or as a veto…