
solve-challenge
Solves CTF challenges by performing first-pass triage, identifying the dominant category, and routing execution to the right specialized ctf- skill. Use when the user gives you a challenge bundle, a remote service, a suspicious file, or only a vague challenge description and you must determine where to start. Do not use it when the category is already clear and a specialized skill can be invoked directly; this is the dispatcher and recon entrypoint, not the deepest reference for category-specific techniques.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/ljagiello/ctf-skills --skill solve-challenge- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads solve-challenge automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
Security audits
Independent scans of the skill's instructions and bundled files.
SKILL.md
The instructions your agent reads when the skill is triggered.
CTF Challenge Solver
You're a skilled CTF player. Your goal is to solve the challenge and find the flag.
Environment Setup
Two setup strategies depending on your workflow:
Pre-install (recommended before competitions)
Use the central installer entrypoint:
bash scripts/install_ctf_tools.sh all
Run a narrower mode when you only want one tool group:
bash scripts/install_ctf_tools.sh python
bash scripts/install_ctf_tools.sh apt
bash scripts/install_ctf_tools.sh brew
bash scripts/install_ctf_tools.sh gems
bash scripts/install_ctf_tools.sh go
bash scripts/install_ctf_tools.sh manual
The full package lists now live in scripts/install_ctf_tools.sh.
On-demand (during challenges)
Each category skill's SKILL.md has a Prerequisites section listing only the tools needed for that category. Install as you go.
Workflow
Before selecting or escalating a model, read difficulty-routing.md. Use its evidence-based scoring, stop-loss rules, and tier gates throughout the workflow.
Step 0: CTFd Platform Detection
If the CTF platform URL is known, check if it runs CTFd and switch to API-driven navigation:
# Detect CTFd (look for /api/v1/ and /themes/core/)
curl -s "$CTF_URL/api/v1/" | head -5
curl -s "$CTF_URL" | grep -oE '/themes/core/'
If CTFd is detected, ask the user for their API token (generated from CTFd Settings > Access Tokens). The token is not provided by default — the user must create one in the CTFd web UI first. Once provided, set the environment variables and proceed via API:
export CTF_URL="https://ctf.example.com"
export CTF_TOKEN="ctfd_..." # Ask user for this
Invoke /ctf-misc and load its ctfd-navigation.md for the full API reference and Python client class.
CTF Platform Interaction via Playwright MCP
When the platform is not CTFd, has no usable API, or gates challenges behind a
JS-rendered UI / login, drive the platform in a real browser with Playwright
MCP (https://github.com/microsoft/playwright-mcp). This lets the agent read
challenge text, download attachments, keep a login session, and submit flags
directly through the site.
browser_navigate "https://ctf.example.com/challenges"
browser_snapshot # list challenges, points, categories (rendered)
browser_click <challenge ref> # open a challenge card
browser_snapshot # read description, hints, attachment links
browser_click <attachment ref> # download the challenge file (saved by the browser)
# ... solve the challenge ...
browser_type <flag input ref> "flag{...}"
browser_click <submit ref>
browser_find text="Correct" # cheaper than a full snapshot to check the verdict
browser_find (text or regex over the accessibility tree) is the right tool
whenever you only need to confirm one value — reserve full browser_snapshot
for when you need element refs to click or type into.
Login sessions (cookies/localStorage) persist across tool calls, so authenticate once and every later navigation is authorized. For general browser-automation tooling see ../ctf-web/tools-mcp.md.
Prefer a native API when one exists (CTFd token flow above is faster and more reliable); use Playwright MCP for platforms without an API or when the challenge list only renders client-side.
Step 1: Recon
- Explore files -- List the challenge directory, run
file *on everything - Triage binaries --
strings,xxd | head,binwalk,checksecon binaries - Fetch links -- If the challenge mentions URLs, fetch them FIRST for context
- Connect -- Try remote services (
nc) to understand what they expect - Read hints -- Challenge descriptions, filenames, and comments often contain clues
Step 2: Categorize
Determine the primary category, then invoke the matching skill.
By file type:
.pcap,.pcapng,.evtx,.raw,.dd,.E01-> forensics.elf,.exe,.so,.dll, binary with no extension -> reverse or pwn (check if remote service provided -- if yes, likely pwn).py,.sage,.txtwith numbers -> crypto.apk,.wasm,.pyc-> reverse.safetensors,.pt,.pth,.bin,.onnx-> ai-ml- Web URL or source code with HTML/JS/PHP/templates -> web
- Images, audio, PDFs with no obvious content -> forensics (steganography)
By challenge description keywords:
- "buffer overflow", "ROP", "shellcode", "libc", "heap" -> pwn
- "RSA", "AES", "cipher", "encrypt", "prime", "modulus", "lattice", "LWE", "GCM" -> crypto
- "XSS", "SQL", "injection", "cookie", "JWT", "SSRF" -> web
- "disk image", "memory dump", "packet capture", "registry", "power trace", "side-channel", "spectrogram", "audio tracks", "MKV" -> forensics
- "find", "locate", "identify", "who", "where" -> osint
- "obfuscated", "packed", "C2", "malware", "beacon" -> malware
- "prompt injection", "LoRA", "adversarial", "model weights", "embedding" -> ai-ml
- "jail", "sandbox", "escape", "encoding", "signal", "game", "Nim", "commitment", "Gray code" -> misc
By service behavior:
- Port with interactive prompt, crash on long input -> pwn
- HTTP service -> web
- netcat with math/crypto puzzles -> crypto
- netcat with restricted shell or eval -> misc (jail)
Step 3: Invoke the Category Skill
Once you identify the category, invoke the matching skill to get specialized techniques:
| Category | Invoke | When to Use |
|---|---|---|
| Web | /ctf-web | XSS, SQLi, SSTI, SSRF, JWT, file uploads, prototype pollution |
| Pwn | /ctf-pwn | Buffer overflow, format string, heap, ROP, sandbox escape |
| Crypto | /ctf-crypto | RSA, AES, ECC, PRNG, ZKP, classical ciphers |
| Reverse | /ctf-reverse | Binary analysis, game clients, VMs, obfuscated code |
| Forensics | /ctf-forensics | Disk images, memory dumps, event logs, stego, network captures |
| OSINT | /ctf-osint | Social media, geolocation, DNS, public records |
| Malware | /ctf-malware | Obfuscated scripts, C2 traffic, PE/.NET analysis |
| AI/ML | /ctf-ai-ml | Model weights (.safetensors, .pt, .pth, .bin, .onnx), prompt injection, LoRA adapters, adversarial examples |
| Misc | /ctf-misc | Jails, encodings, RF/SDR, esoteric languages, constraint solving |
You can also invoke /ctf-<category> to load the full skill instructions with detailed techniques.
Step 4: Pivot When Stuck
If your first approach doesn't work:
- Re-examine assumptions -- Is this really the category you think? A "web" challenge might need crypto for JWT forgery. A "forensics" PCAP might contain a pwn exploit to replay.
- Try a different category skill -- Many challenges span multiple categories. Invoke a second skill for the cross-cutting technique.
- Look for what you missed -- Hidden files, alternate ports, response headers, comments in source, metadata in images.
- Simplify -- If an exploit is too complex, check if there's a simpler path (default creds, known CVE, logic bug).
- Check edge cases -- Off-by-one, race conditions, integer overflow, encoding mismatches.
Common multi-category patterns:
- Forensics + Crypto: encrypted data in PCAP/disk image, need crypto to decrypt
- Web + Reverse: WASM or obfuscated JS in web challenge
- Web + Crypto: JWT forgery, custom MAC/signature schemes
- Reverse + Pwn: reverse the binary first, then exploit the vulnerability
- Forensics + OSINT: recover data from dump, then trace it via public sources
- Misc + Crypto: jail escape requires building crypto primitives under constraints
- OSINT + Stego: social media posts with unicode homoglyph steganography (Cyrillic lookalikes encode bits)
- Web + Forensics: paywall bypass (curl reveals content hidden by CSS overlays)
- Misc + Crypto + Game Theory: multi-phase interactive challenges with AES decryption → HMAC commitment → combinatorial game solving (GF(256) Nim)
- Crypto + Geometry + Lattice: multi-layer challenges progressing from spatial reconstruction → subspace recovery → LWE solving → AES-GCM decryption
- Forensics + Signal Processing: power traces / side-channel analysis requiring statistical analysis of measurement data
- Forensics + Network + Encoding: timing-based encoding in PCAP (inter-packet intervals encode binary data)
Step 5: Generate Write-up
After solving the challenge, invoke /ctf-writeup to generate a standardized submission-style writeup — concise, reproducible, and ready for competition organizers or teammates to validate.
Flag Formats
Flags vary by CTF. Common formats:
flag{...},FLAG{...},CTF{...},TEAM{...}- Custom prefixes: check the challenge description or CTF rules for the format (e.g.,
ENO{...},HTB{...},picoCTF{...}) - Sometimes just a plaintext string with no wrapper
Validation rule (important):
- If you find multiple flag-like strings, treat them as candidates and validate before finalizing.
- Prefer the token tied to the intended artifact/workflow (not random metadata noise or obvious decoys).
- Do a corpus-wide uniqueness check and include the source file/path when reporting.
# Search for common flag patterns in files
grep -rniE '(flag|ctf|eno|htb|pico)\{' .
# Search in binary/memory output
strings output.bin | grep -iE '\{.*\}'
Quick Reference
# Recon
file * # Identify file types
strings binary | grep -i flag # Quick string search
xxd binary | head -20 # Hex dump header
binwalk -e firmware.bin # Extract embedded files
checksec --file=binary # Check binary protections
# Connect
nc host port # Connect to challenge
echo -e "answer1\nanswer2" | nc host port # Scripted input
curl -v http://host:port/ # HTTP recon
# Python exploit template
python3 -c "
from pwn import *
r = remote('host', port)
r.interactive()
"
Challenge
$ARGUMENTS
FAQ
What does the solve-challenge skill do?
Solves CTF challenges by performing first-pass triage, identifying the dominant category, and routing execution to the right specialized ctf- skill. Use when the user gives you a challenge bundle, a remote service, a suspicious file, or only a vague challenge description and you must determine where to start. Do not use it when the category is already clear and a specialized skill can be invoked directly; this is the dispatcher and recon entrypoint, not the deepest reference for category-specific techniques.
How do I install solve-challenge?
Run npx skills add https://github.com/ljagiello/ctf-skills --skill solve-challenge in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/solve-challenge/ (personal) or .claude/skills/solve-challenge/ (project).
Which AI agents can use solve-challenge?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is solve-challenge safe to install?
Security partners have reviewed it: Gen Agent Trust Hub passed; Socket flagged items to review; Snyk flagged items to review; Runlayer flagged items to review; ZeroLeaks passed. As with any skill, read the SKILL.md and bundled scripts before installing.
Who maintains solve-challenge?
It is published by ljagiello in ljagiello/ctf-skills. It has 8,956 recorded installs.
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