Reverse engineers binaries using Ghidra's headless analyzer. Use when decompiling executables, extracting functions, strings, symbols, or analyzing call graphs from compiled binaries without the Ghidra GUI.
日本語の概要は準備中です。原文の説明を表示しています。
Expert guidance for ffuf web fuzzing during authorized penetration testing. Covers directory discovery, subdomain enumeration, parameter fuzzing, authenticated fuzzing with raw requests, auto-calibration, and result analysis. Use when running ffuf scans, analyzing ffuf output, or building fuzzing strategies for web targets.
日本語の概要は準備中です。原文の説明を表示しています。
実行スコア 未検証
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
Guidance for using ffuf (Fuzz Faster U Fool) effectively during authorized penetration testing.
ffuf must be installed: brew install ffuf (macOS) or go install github.com/ffuf/ffuf/v2@latest
-ac is mandatory. Without it, results are buried in false positives and analysis is wasted effort.-t 200 triggers WAFs, gets you blocked, and may crash staging environments. Start with -t 10 -rate 2 for production targets.--request req.txt is simpler and more reliable than chaining -H and -b flags. Capture once, fuzz many times.-ac (auto-calibration) unless you have a specific, documented reason not to-o results.json for later analysis-rate and -t flags--request for auth -- raw request files beat command-line header chains# In URL path
ffuf -w wordlist.txt -u https://target.com/FUZZ -ac
# In headers
ffuf -w wordlist.txt -u https://target.com -H "Host: FUZZ.target.com" -ac
# In POST body
ffuf -w wordlist.txt -X POST -d "user=admin&pass=FUZZ" -u https://target.com/login -ac
# Multiple positions with custom keywords
ffuf -w endpoints.txt:EP -w ids.txt:ID -u https://target.com/EP/ID -mode pitchfork -ac
-ac automatically detects and filters repetitive false-positive responses. It adapts to the target's specific behavior and removes noise from dynamic content.
ffuf -w wordlist.txt -u https://target.com/FUZZ -ac # Standard
ffuf -w wordlist.txt -u https://target.com/FUZZ -ach # Per-host (multi-host scans)
ffuf -w wordlist.txt -u https://target.com/FUZZ -acc "404" # Custom calibration string
ffuf -w /opt/SecLists/Discovery/Web-Content/raft-large-directories.txt \
-u https://target.com/FUZZ -e .php,.html,.txt,.bak \
-ac -c -v -o results.json
ffuf -w /opt/SecLists/Discovery/DNS/subdomains-top1million-5000.txt \
-u https://FUZZ.target.com -ac -c -v -o results.json
ffuf -w /opt/SecLists/Discovery/Web-Content/api/api-endpoints.txt \
-u https://api.target.com/v1/FUZZ \
-H "Authorization: Bearer YOUR_TOKEN_HERE" -mc 200,201 -ac -c
Capture a full authenticated request, save to req.txt, insert FUZZ:
POST /api/v1/users/FUZZ HTTP/1.1
Host: target.com
Authorization: Bearer YOUR_TOKEN_HERE
Cookie: session=YOUR_SESSION_ID
Content-Type: application/json
{"action":"view","id":"1"}
ffuf --request req.txt -w wordlist.txt -ac -o results.json
See references/request-templates.md for pre-built templates covering bearer tokens, session cookies, API keys, and GraphQL.
Authenticated fuzzing requires real credentials that the agent cannot obtain independently. When the user asks for authenticated fuzzing:
req.txt) with auth headers already includedreq.txt format)req.txtffuf --request req.txt -w <(seq 1 10000) -ac -mc 200 -o idor_results.json
| Environment | Flags | Notes |
|---|---|---|
| Production (stealth) | -rate 2 -t 10 | Avoid WAF triggers |
| Production (normal) | -rate 10 -t 20 | Balanced |
| Staging/Dev | -rate 50 -t 40 | Faster |
| Local/Lab | No limit, -t 100 | Maximum speed |
Save output as JSON (-o results.json), then read the file and focus on:
Use -fs to filter by response size and -fc to filter by status code when auto-calibration isn't sufficient. Run ffuf -h for the full list of match/filter flags.
まだレビューはありません。使ってみた感想をお寄せください。
ログインなしで書き込めます。使ってみた感想、質問、動かなかった環境などを気軽にどうぞ。
まだコメントはありません。最初のコメントを書いてみませんか。
Reverse engineers binaries using Ghidra's headless analyzer. Use when decompiling executables, extracting functions, strings, symbols, or analyzing call graphs from compiled binaries without the Ghidra GUI.
日本語の概要は準備中です。原文の説明を表示しています。
Interviews the user relentlessly about a plan, decision, or idea until every branch of the decision tree is resolved. Use when the user wants to stress-test their thinking, sharpen a plan or design before acting, or uses any 'grill' trigger phrase (e.g. "grill me on this").
日本語の概要は準備中です。原文の説明を表示しています。
Compacts the current conversation into a handoff document so a fresh agent can continue the work in a new session.
日本語の概要は準備中です。原文の説明を表示しています。
Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases. 30c5c8d (Update humanizer plugin to upstream v2.2.0)
日本語の概要は準備中です。原文の説明を表示しています。
Researches a topic from the last 30 days on Reddit, X, and the web. Surfaces real community discussions with engagement metrics and synthesizes findings into actionable insights. Use when the user wants to know what people are saying about a topic right now.
日本語の概要は準備中です。原文の説明を表示しています。
Deploy applications and infrastructure to Cloudflare using Workers, Pages, and related platform services. Use when the user asks to deploy, host, publish, or set up a project on Cloudflare. Originally from OpenAI's curated skills catalog.
日本語の概要は準備中です。原文の説明を表示しています。