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/miru-zero/zero-brain/ssrf-server-side-request-forgerynpx skills add miru-zero/zero-brain --skill ssrf-server-side-request-forgerygit clone --depth 1 https://github.com/miru-zero/zero-brainWrote 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/miru-zero/zero-brain/ssrf-server-side-request-forgery)<a href="https://agentmods.dev/skills/miru-zero/zero-brain/ssrf-server-side-request-forgery"><img src="https://agentmods.dev/badge/skills/miru-zero/zero-brain/ssrf-server-side-request-forgery.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 | $0.03593 |
| Opus 5 | $0.00023 | $0.01796 |
| Sonnet 5 | $0.00009 | $0.00719 |
| Haiku 4.5 | $0.00005 | $0.00359 |
Grade E, and why
ssrf-server-side-request-forgery scanned grade E 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 2d 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.
Reaches for credential fileshighPrivilege escalation
SSH keys, cloud credentials, git-credentials, .npmrc, /etc/shadow: reading these is how a config file becomes a credential leak.
{"Image":"alpine","Cmd":["cat","/etc/shadow"],"HostConfig":{"Binds":["/:/host"]}} Cloud metadata endpointhighServer-side request forgery
One request to 169.254.169.254 can return temporary IAM credentials.
> **AI LOAD INSTRUCTION**: Expert SSRF techniques. Covers URL filter bypass, cloud metadata endpoints, protocol exploitation, blind SSRF detection, and chaining to RCE. Base models know basic 169.254.169.254 — this file Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- URL parser differential table: Python urllib vs requests vs Java URL vs PHP parse_url vs Node url.parse vs Go net/url This is a copy
91% identical to ssrf-server-side-request-forgery — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 324 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SKILL: Server-Side Request Forgery (SSRF) — Expert Attack Playbook
AI LOAD INSTRUCTION: Expert SSRF techniques. Covers URL filter bypass, cloud metadata endpoints, protocol exploitation, blind SSRF detection, and chaining to RCE. Base models know basic 169.254.169.254 — this file covers what they miss. For real-world CVE chains, DNS Rebinding deep dives, K8s SSRF, and SSRF → Redis → RCE full exploitation, load the companion SCENARIOS.md.
0. QUICK START
Extended Scenarios
Also load SCENARIOS.md when you need:
- WebLogic SSRF (CVE-2014-4210) —
uddiexplorer/SearchPublicRegistries.jsp+operatorparameter +%0D%0ACRLF to inject Redis commands - SSRF → internal Redis → write crontab reverse shell complete payload chain
- DNS Rebinding deep dive — TTL=0 trick, initial-legit→second-internal resolution,
rbndr.usservice - Kubernetes SSRF (CVE-2020-8555) and bypass (CVE-2020-8562) via DNS rebinding
- SSRF through PDF/screenshot generators —
<iframe>and<img>in HTML-to-PDF - Gopher protocol full TCP injection — Redis, MySQL, FastCGI payloads via Gopherus
- URL parser confusion for filter bypass —
#@,\@,%00@, IPv6-mapped IPv4
Advanced Reference
Also load URL_PARSER_TRICKS.md when you need:
- URL parser differential table: Python urllib vs requests vs Java URL vs PHP parse_url vs Node url.parse vs Go net/url
- Full cloud metadata endpoint catalog (AWS IMDSv1/v2, GCP, Azure, DigitalOcean, Alibaba Cloud, Oracle Cloud, Kubernetes, Hetzner, OpenStack)
- gopher:// payload recipes for Redis, MySQL, SMTP, FastCGI, Memcached (with encoding rules)
- DNS Rebinding detailed attack flow with TTL manipulation and TOCTOU analysis
- PDF/wkhtmltopdf/WeasyPrint/Chrome headless/PhantomJS SSRF patterns and exfiltration techniques
If you just found a parameter that fetches a URL, perform first-pass confirmation here directly.
First-pass payloads
http://127.0.0.1/
http://localhost/
http://169.254.169.254/latest/meta-data/
http://[::1]/
http://127.1/
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 324 lines · 45 tokens per session scan E 3ed4bcba415d
ssrf-server-side-request-forgery is a skill published in the GitHub repository miru-zero/zero-brain (0 stars, last pushed 18d ago), licensed MIT. It adds 45 tokens to every session and 3,593 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it E with 3 findings (reaches for credential files, cloud metadata endpoint, makes network calls). It is 91% identical to ssrf-server-side-request-forgery, differing in 4 lines, and is treated as a copy.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…