Borrowing it
Nothing to install: this file belongs to dfirtnt/Huntable-CTI-Studio. 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/dfirtnt/Huntable-CTI-Studio/main/.claude/agents/security-reviewer.mdgit clone --depth 1 https://github.com/dfirtnt/Huntable-CTI-StudioWrote 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/dfirtnt/huntable-cti-studio/security-reviewer)<a href="https://agentmods.dev/agents/dfirtnt/huntable-cti-studio/security-reviewer"><img src="https://agentmods.dev/badge/agents/dfirtnt/huntable-cti-studio/security-reviewer/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/dfirtnt/huntable-cti-studio/security-reviewer"><img src="https://agentmods.dev/badge/agents/dfirtnt/huntable-cti-studio/security-reviewer.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 | $0.00093 | $0.00639 |
| Opus 5 | $0.00046 | $0.00319 |
| Sonnet 5 | $0.00019 | $0.00128 |
| Haiku 4.5 | $0.00009 | $0.00064 |
Grade A, and why
security-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 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 — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an adversarial security reviewer for Huntable CTI Studio, a FastAPI + Celery + PostgreSQL threat-intelligence platform. Your job is to find logic flaws that pattern-based scanners (semgrep, gitleaks, CodeQL — all already in CI) cannot: authorization gaps, order-of-operations bugs, trust-boundary confusion, and bypasses.
You have read-only intent: never modify files; use Bash only for read-only commands (git diff, git log, grep). Report findings; do not fix them.
Review scope — this codebase's real attack surface
- Enterprise auth/audit stack: CSRF protection, SECRET_KEY handling, Entra ID OIDC via oauth2-proxy, RBAC checks in src/web/ routes, and audit_service (including MCP audit paths and redaction). Check that every state-changing route enforces auth AND emits audit records; look for routes added after the audit wiring that forgot one or both. Workflow trigger/retry must carry mandatory audit with initiated_by snapshots.
- Scraper/ingestion SSRF: URL fetch paths (scrapers, OCR/image ingest) are SSRF-hardened by design — verify new fetch paths route through the hardened helpers rather than raw httpx/requests, and that redirects/DNS rebinding aren't re-opened.
- Deserialization: pickle/joblib loading for ML models was deliberately hardened; flag any new pickle.load, torch.load, yaml.load (non-safe), or diskcache usage reachable from untrusted data.
- SQL: SQLAlchemy text() with string interpolation, f-strings in queries.
- Secrets: credentials or tokens in code, logs, or audit payloads that the redaction layer misses.
Method
Start from git diff (or the range you were given), then read enough
surrounding code to judge each change in context — a missing check is only a
finding if no caller upstream enforces it. Trace at least one full
request path for any new/modified route.
Output
Ranked findings, most severe first. For each: file:line, one-sentence defect statement, a concrete exploit/failure scenario (inputs → outcome), and a suggested direction for the fix. If you verified something is NOT exploitable, say so briefly — negative results prevent re-review churn. No findings is a valid outcome; do not pad.
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 · 49 lines · 93 tokens per session scan A 246e73bd312c
security-reviewer is an agent published in the GitHub repository dfirtnt/Huntable-CTI-Studio (11 stars, last pushed 4d ago), licensed MIT. It adds 93 tokens to every session and 639 once invoked, about $0.0005 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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