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.
npx agentmods add skills/alexandermattturner/agent-glovebox/vuln-researchnpx skills add AlexanderMattTurner/agent-glovebox --skill vuln-researchgit clone --depth 1 https://github.com/AlexanderMattTurner/agent-gloveboxWhat 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 | $0.00197 | $0.02772 |
| Opus 5 | $0.00098 | $0.01386 |
| Sonnet 5 | $0.00039 | $0.00554 |
| Haiku 4.5 | $0.00020 | $0.00277 |
Grade A, and why
vuln-research 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
This is the rule the whole activity hangs off, because the economics run against you. Generating a plausible vulnerability narrative is cheap and verifying one is expensive, so an unverified report moves your cost onto w How it starts
The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Vulnerability research
The load-bearing rule
A finding you cannot reproduce is not a finding. It is a hypothesis, and it stays one until a command you can name turns it into evidence. Report the hypothesis as a hypothesis or drop it — never as a vulnerability.
This is the rule the whole activity hangs off, because the economics run against you. Generating a plausible vulnerability narrative is cheap and verifying one is expensive, so an unverified report moves your cost onto whoever reads it. The curl project watched its confirmed-vulnerability rate fall from over 15% to under 5% as unverified AI reports arrived, and closed a seven-year bug bounty on 31 January 2026 rather than keep paying that tax. The recovery is the instructive half: by April 2026 the slop had stopped and the AI-assisted reports that replaced it were mostly valid, because reporters started verifying before sending.
Scope this skill holds
This skill fires when the deliverable is a claim about real software being exploitable. That is a different job from the reviews this tree already has, so pick the right one and do not run two:
- A pending diff before a PR →
peer-review. - A single-pass look at the current branch → the built-in
security-review. - A whole-codebase multi-axis audit ending in a fix plan →
parallel-audit. - Proving an isolation layer still engages, with tests →
stress-test. - A vulnerability claim you intend to act on or send somewhere → this skill.
Deliver the finding set you were asked for. Do not widen a bounded question ("is this one path exploitable?") into a full audit.
1. Read the threat model before you read the code
Score every candidate against SECURITY.md, not against a generic vulnerability pattern. This tree states its threat model explicitly: the agent itself is the attacker, and it assumes that agent can run any shell as glovebox-agent, read its own guardrails, and spawn sub-agents. It also states what is out of scope — outside attackers, host compromise, base-image supply chain, deliberate bypass flags, and post-session merged code.
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.
- today Changed e6bbfe9ad294
- yesterday First seen · 120 lines · 197 tokens per session scan A 2bf9f45b2168
vuln-research is a skill published in the GitHub repository AlexanderMattTurner/agent-glovebox (57 stars, last pushed today), licensed Apache-2.0. It adds 197 tokens to every session and 2,772 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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