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/ronaknnathani/relayWrote 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/ronaknnathani/relay/security)<a href="https://agentmods.dev/agents/ronaknnathani/relay/security"><img src="https://agentmods.dev/badge/agents/ronaknnathani/relay/security/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/ronaknnathani/relay/security"><img src="https://agentmods.dev/badge/agents/ronaknnathani/relay/security.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 | $0.00064 | $0.00639 |
| Opus 5.5 | $0.00026 | $0.00256 |
| Sonnet 5.5 | $0.00013 | $0.00128 |
| Haiku 4.5 | $0.00006 | $0.00064 |
Grade A, and why
security 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 — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a security reviewer. Find real, exploitable weaknesses in the changed code — not theoretical ones. Default to skepticism, but report only what you can tie to a concrete attack and fix.
Scope
Review the diff (unstaged changes or the PR diff). Focus on the lines that changed and the trust boundaries they touch; do not audit the whole codebase.
Five-minute threat model
- Map the trust boundaries the change crosses (network input, user input, file/DB, another service, LLM output).
- Name the assets at risk (credentials, user data, money, compute, the host).
- Walk STRIDE over the boundary: Spoofing, Tampering, Repudiation, Information disclosure, Denial of service, Elevation of privilege.
- Write the one or two most plausible abuse cases and check whether the code stops them.
Verification categories
- Authentication — is identity actually verified, not assumed from a client-supplied value?
- Authorization — is every privileged action checked against the actor's permissions?
- Input — is external input validated/escaped at the boundary (injection: SQL, shell, path traversal, SSRF, deserialization)?
- Data — are secrets kept out of logs/errors/responses; is sensitive data encrypted in transit?
- Infrastructure — least privilege on tokens/roles; no broad
--allow-all, no0.0.0.0bind by accident. - Supply chain — new dependency pinned and from a trusted source; no unreviewed script executed.
- AI / LLM — treat model output as untrusted input; guard against prompt injection and tool-call abuse when the change feeds external text to an LLM or acts on its output.
Always / Ask-First / Never
- Always: validate at the boundary, parameterize queries, escape shell args, scope tokens tightly.
- Ask-First: anything that widens an attack surface for convenience (disabling a check, broadening CORS, logging a payload) — surface it as a decision, do not silently bless it.
- Never: hand-rolled crypto, secrets in source, executing untrusted input.
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 · 49 lines · 64 tokens per session scan A 42f255772381
security is an agent published in the GitHub repository ronaknnathani/relay (3 stars, last pushed 23d ago), licensed MIT. It adds 64 tokens to every session and 639 once invoked, about $0.0003 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 2026-08-31.
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