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 skills add Encod3d-Sec/TORCH --skill hunt-ssrfgit clone --depth 1 https://github.com/Encod3d-Sec/TORCHWrote 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/skills/encod3d-sec/torch/hunt-ssrf)<a href="https://agentmods.dev/skills/encod3d-sec/torch/hunt-ssrf"><img src="https://agentmods.dev/badge/skills/encod3d-sec/torch/hunt-ssrf.svg" alt="Measured on agentmods" 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 | $0.00045 | $0.02467 |
| Opus 5 | $0.00023 | $0.01234 |
| Sonnet 5 | $0.00009 | $0.00493 |
| Haiku 4.5 | $0.00005 | $0.00247 |
Grade C, and why
hunt-ssrf scanned grade C with 3 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 8d 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.
Cloud metadata endpointhighServer-side request forgery
One request to 169.254.169.254 can return temporary IAM credentials.
http://169.254.169.254/latest/meta-data/iam/security-credentials/ Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
as a raw URL PREFIX with no hardcoded scheme (e.g. pycurl `setopt(URL, server + '/path')`, `requests.get(host+path)`; Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
return subprocess.run(['curl','-s','-m','10', 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.
Hunt: SSRF
Assumes hunt-core for the scope gate, two-account rule, confirmation gate, enumeration
limits, stop conditions, wiki protocol, FIND output, and Deadends. Do not re-derive any of that here.
Wiki
qmd_query "SSRF server-side request forgery cloud metadata" via wiki-search MCP
Hub: [[web-moc]] (live web index). Primary page: [[wiki/payloads/ssrf]]. Payload arsenal: wiki/payloads/ssrf.md.
Bypass variants: [[dns-rebinding]] (hostname re-resolution TOCTOU past an allowlist),
[[open-redirect]] (chain a trusted redirect to an internal target).
Confirmation gate
Blind SSRF claims require OOB confirmation. No exceptions.
NOT confirmation: URL echo in error message, different status code, delayed response alone. IS confirmation: DNS lookup or HTTP request to your unique Collaborator/interactsh subdomain.
When you plant a blind/OOB SSRF payload, append a row to targets/<eng>/oob.md: | <token> | <sink url+param> | ssrf | <date> | waiting | | (columns: token | sink | class | planted | status | source, where token = your unique Collaborator/interactsh label). The recon-capture hook auto-correlates incoming callbacks to flip the row to HIT and SessionStart surfaces HITs; a HIT row is the confirmation gate to scaffold the FIND. Do NOT claim a blind SSRF without a HIT row.
Setup OOB before testing (full channel guide: wiki oob-callbacks - DNS-vs-HTTP, self-hosted interactsh, DNS exfil):
interactsh-client -v # or use Burp Collaborator
# Tag each sink: dlsrcurl.<collab>, import.<collab>, webhook.<collab>
Attack Surface Signals
URL patterns:
?url= ?uri= ?src= ?source= ?feed= ?host= ?target= ?dest=
?redirect= ?callback= ?image= ?fetch= ?load= ?endpoint=
/api/*/preview /api/*/fetch /api/*/import /api/*/webhook /api/*/render
High-value tech: Kubernetes (internal API), GCP/AWS/Azure (metadata), headless browsers (PDF/screenshot), link-preview features, file-import pipelines.
Check SCHEME control EARLY (before grinding host/port bypasses). If the sink concatenates your input
as a raw URL PREFIX with no hardcoded scheme (e.g. pycurl setopt(URL, server + '/path'), requests.get(host+path);
tell: the default value has no http://, like server=host:8087), you control the scheme, not just the
host -> try file:///etc/passwd and file:///<app-source> for a straight LFI, and gopher:// for
internal TCP. The moment file:// reads a file, READ THE APP SOURCE FIRST - it reveals the real ports/
auth/next-steps faster than any probing, and on Flask debug=True a file-read computes the console PIN ->
RCE ([[werkzeug-debug-console-rce]]). Also: pointing the sink at your own listener leaks its outbound
request headers (API keys/tokens). See [[wiki/payloads/ssrf]] "Scheme-controllable SSRF -> file:// LFI".
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.
- 8d ago First seen · 145 lines · 45 tokens per session scan C b4a183a16c3c
hunt-ssrf is a skill published in the GitHub repository Encod3d-Sec/TORCH (314 stars, last pushed 6d ago), licensed MIT. It adds 45 tokens to every session and 2,467 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it C with 3 findings (cloud metadata endpoint, makes network calls, runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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