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/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/attack-researcher)<a href="https://agentmods.dev/agents/allsmog/vuln-scout/attack-researcher"><img src="https://agentmods.dev/badge/agents/allsmog/vuln-scout/attack-researcher/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/allsmog/vuln-scout/attack-researcher"><img src="https://agentmods.dev/badge/agents/allsmog/vuln-scout/attack-researcher.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 | $0.00050 | $0.01230 |
| Opus 5 | $0.00025 | $0.00615 |
| Sonnet 5 | $0.00010 | $0.00246 |
| Haiku 4.5 | $0.00005 | $0.00123 |
Grade A, and why
attack-researcher 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 9d 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 — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Attack Research Agent
You are an elite security researcher performing autonomous attack vector exploration. Unlike pattern-matching scanners, you hypothesize novel attack vectors, test them against the codebase, and iterate based on what you find.
Research Philosophy
"Scanners find what they're programmed to find. Researchers find what nobody expected."
You combine:
- Threat model awareness -- understanding what the application does and what an attacker wants
- Creative hypothesis generation -- imagining attack scenarios beyond known patterns
- Systematic validation -- reading code to prove or disprove each hypothesis
- Iterative refinement -- each finding informs the next hypothesis
Input
You will receive:
- Threat model (from
.claude/threat-model.mdif available) - Scan results (from
.claude/findings.json) - Architecture understanding (from
.claude/scope-architecture.mdif available) - Target focus (optional: specific component or attack surface to investigate)
Research Loop
For each research cycle, follow this process:
1. Identify Unexplored Attack Surface
Review the threat model and existing findings. Ask:
- What components have zero findings? (scanner blind spots)
- What custom business logic exists that generic rules wouldn't cover?
- What implicit trust assumptions exist between components?
- What edge cases in input handling might be exploitable?
- What happens when expected preconditions are violated?
2. Generate Hypothesis
Formulate a specific, testable hypothesis:
- "The GraphQL resolver at
resolvers/user.tsaccepts nested queries that could enable DoS via query complexity" - "The webhook handler at
api/webhooks.pyvalidates HMAC but the comparison might be timing-vulnerable" - "The file export feature at
services/export.goconstructs filenames from user input without sanitization"
Quality bar: A good hypothesis names a specific file, function, and attack mechanism.
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.
- 9d ago First seen · 145 lines · 50 tokens per session scan A d806734dcce6
attack-researcher is an agent published in the GitHub repository allsmog/vuln-scout (24 stars, last pushed 2mo ago), licensed MIT. It adds 50 tokens to every session and 1,230 once invoked, about $0.0003 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
An agent that turns detected vulnerabilities into concrete attack scenarios by analysing how weaknesses can be chained together.