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 adriannoes/awesome-agentic-ai --skill hunt-ssrfgit clone --depth 1 https://github.com/adriannoes/awesome-agentic-aiWrote 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/adriannoes/awesome-agentic-ai/hunt-ssrf)<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/hunt-ssrf"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/hunt-ssrf/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/skills/adriannoes/awesome-agentic-ai/hunt-ssrf"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/hunt-ssrf.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 | $0.00031 | $0.04459 |
| Opus 5 | $0.00015 | $0.02230 |
| Sonnet 5 | $0.00006 | $0.00892 |
| Haiku 4.5 | $0.00003 | $0.00446 |
Grade C, and why
hunt-ssrf scanned grade C with 2 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.
Cloud metadata endpointhighServer-side request forgery
One request to 169.254.169.254 can return temporary IAM credentials.
- **Cloud-hosted SaaS products** (GCP metadata at `169.254.169.254` or `metadata.google.internal`, AWS IMDSv1) Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
fetch(userInput) How it starts
The opening of the file, as written. The whole thing — 383 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Crown Jewel Targets
SSRF is highest-value when the target runs on cloud infrastructure (AWS, GCP, Azure) where metadata services expose credentials, or when the server sits inside a complex internal network (Kubernetes clusters, microservice meshes, internal APIs). Priority targets:
- Cloud-hosted SaaS products (GCP metadata at
169.254.169.254ormetadata.google.internal, AWS IMDSv1) - Kubernetes/orchestration platforms — aggregated API servers, metrics-server, kubelet endpoints expose privileged cluster operations
- Internal developer tooling — CI/CD, workflow orchestration (Flyte, Argo), admin panels not exposed externally
- Link preview / URL fetching features — Reddit-style preview APIs, Slack-style unfurling, media processors
- Dataset/file import pipelines — anything that fetches remote URLs on behalf of a user
- Enterprise self-hosted software (GitHub Enterprise, GitLab) — SSRF frequently chains to RCE via internal services
Payouts are highest when SSRF reaches: cloud credentials → account takeover, internal admin APIs → data exfil, or chains to RCE.
OOB-Or-It-Didn't-Happen Gate (Read First)
Claims of blind SSRF require an out-of-band (OOB) confirmation. Always. No exceptions.
OOB means: a Burp Collaborator domain, an interactsh-client listener, a canarytoken, or any DNS+HTTP receiver you control that confirms the server actually made an outbound network connection on your behalf.
What is NOT confirmation of SSRF
- The server echoing your URL back in an error message. Example:
"The Web application at http://evil.example.com/x could not be found"— this is the server formatting your input into an error string, NOT making an outbound HTTP request. The error came from string formatting, not from network failure. - The server returning a different status code for an external URL vs
localhost. Different error responses can come from URL-scheme validators, not from actual fetching. - A delayed response when the URL is sent. Delay can come from DNS resolution attempts within the parser, not from completed HTTP fetches.
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 · 383 lines · 31 tokens per session scan C 868522323df9
hunt-ssrf is a skill published in the GitHub repository adriannoes/awesome-agentic-ai (57 stars, last pushed 14d ago), licensed MIT. It adds 31 tokens to every session and 4,459 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it C with 2 findings (cloud metadata endpoint, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
importing-a-codebase
Use when the repo holds real source code but no specs: the existing-codebase branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for empty workspaces (starting-a-new-project) or feature work in a specced project (brainstorming).
starting-a-new-project
Use when the workspace is empty — no code yet — and the user brings a raw idea: the brand-new branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for features in an existing project — use brainstorming instead.
todos
This chat has a shared, live TODO plan — your tasks for the conversation, which the user also edits. Read this skill and reach for the todo tools whenever a request takes more than a couple of steps. It covers the plan model (group = task, items = its steps; loose items are the user's lane), how to work it: propose…
writing-workflow-skills
Use when adding a new workflow skill to pi-thinkrail-workflow, changing an existing workflow skill's role, trigger, handoff, or structure, or checking a workflow skill against the workflow system's rules. Not for authoring general-purpose skills outside this package.
brainstorming
Use this BEFORE any creative or feature work: building a new feature, adding functionality, changing behavior, or making a nontrivial design decision. Turns the user's request into a validated design — recorded as a spec-graph task-spec — before any implementation. Do not skip this because a change looks small.
reviewing-changes
Use when a review package asks you to review a plan step's change set (todo.startReview): you are the REVIEWER, not the author. How to judge an agent-written diff, file findings with addreviewcomment, and settle with exactly one reviewverdict.