solve-challenge
Orchestrates category-specific CTF skills to solve challenges across pwn, crypto, web, reverse engineering, forensics, OSINT, malware, and misc.
- Performs initial reconnaissance by exploring files, analyzing binaries with
strings/binwalk/checksec, fetching remote URLs, and connecting to services to understand challenge context - Categorizes challenges by file type, keywords, and service behavior, then invokes the matching specialized skill (
/ctf-web,/ctf-pwn,/ctf-crypto, etc.) - Handles multi-category challenges by pivoting between skills when initial approaches fail, recognizing patterns like forensics+crypto (encrypted PCAP data) or web+reverse (obfuscated JS)
- Requires filesystem-based agent with bash, Python 3, internet access, and orchestrates other
ctf-*skills for domain-specific exploitation techniques
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:
More from ljagiello/ctf-skills
ctf-reverse
Provides reverse engineering techniques for CTF challenges. Use when the main job is to understand how a compiled, obfuscated, packed, or virtualized target works before exploiting or solving it, including binaries, APKs, WASM, firmware, custom VMs, bytecode, game clients, malware-like loaders, and anti-debug or anti-analysis logic. Do not use it when the vulnerability is already understood and the remaining task is exploitation; use pwn instead. Do not use it for pure web workflows, log or disk forensics, or standalone crypto problems unless reversing the implementation is the real blocker.
3.7Kctf-web
Provides web exploitation techniques for CTF challenges. Use when the target is primarily an HTTP application, API, browser client, template engine, identity flow, or smart-contract frontend/backend surface, including XSS, SQLi, SSTI, SSRF, XXE, JWT, auth bypass, file upload, request smuggling, OAuth/OIDC, SAML, prototype pollution, and similar web bugs. Do not use it for native binary memory corruption, reverse engineering of standalone executables, disk or memory forensics, or pure cryptanalysis unless the web flaw is still the main path to the flag.
3.5Kctf-pwn
Provides binary exploitation techniques for CTF challenges. Use when you already have a vulnerable native target or service and need to turn memory corruption or low-level primitives into code execution or privilege escalation, such as buffer overflows, format strings, heap bugs, ROP, ret2libc, shellcode, kernel exploitation, seccomp bypass, sandbox escape, or Windows/Linux exploit chains. Do not use it when the main blocker is understanding what the binary does; use reverse engineering first. Do not use it for pure web bugs, disk or packet forensics, or standalone crypto/math challenges.
3.4Kctf-crypto
Provides cryptography attack techniques for CTF challenges. Use when attacking encryption, hashing, signatures, ZKP, PRNG, or mathematical crypto problems involving RSA, AES, ECC, lattices, LWE, CVP, number theory, Coppersmith, Pollard, Wiener, padding oracle, GCM, key derivation, or stream/block cipher weaknesses.
3.3Kctf-osint
Provides open source intelligence techniques for CTF challenges. Use when gathering information from public sources, social media, geolocation, DNS records, username enumeration, reverse image search, Google dorking, Wayback Machine, Tor relays, FEC filings, or identifying unknown data like hashes and coordinates.
3.3Kctf-forensics
Provides digital forensics and signal analysis techniques for CTF challenges. Use when analyzing disk images, memory dumps, event logs, network captures, cryptocurrency transactions, steganography, PDF analysis, Windows registry, Volatility, PCAP, Docker images, coredumps, side-channel power traces, DTMF audio spectrograms, packet timing analysis, CD audio disc images, or recovering deleted files and credentials.
3.3K