🎯Skills12
OSINT skills for CTF challenges covering social media investigation, geolocation, DNS reconnaissance, Google dorking, Wayback Machine, hash identification, and more.
A comprehensive web exploitation reference for CTF challenges, covering SQL injection, XSS, SSTI, SSRF, JWT attacks, prototype pollution, command injection, Web3/blockchain exploits, and CVE-specific techniques with ready-to-use payloads.
A ctf pwn skill from CTF (Capture The Flag) cybersecurity challenge skills.
A ctf crypto skill from CTF (Capture The Flag) cybersecurity challenge skills.
OSINT skills for CTF challenges covering social media investigation, geolocation, DNS reconnaissance, Google dorking, Wayback Machine, hash identification, and more.
OSINT skills for CTF challenges covering social media investigation, geolocation, DNS reconnaissance, Google dorking, Wayback Machine, hash identification, and more.
Solves miscellaneous Capture The Flag (CTF) challenges by providing utility functions and techniques for solving non-standard problems.
CTF challenge solver skill that orchestrates category-specific skills for pwn, crypto, web, reverse engineering, forensics, OSINT, malware analysis, and miscellaneous challenges. Analyzes files, connects to services, and applies exploitation techniques.
Malware analysis and network traffic skill for CTF challenges. Covers obfuscated scripts, malicious packages, custom crypto protocols, C2 traffic, PE/.NET binaries, and encrypted communications analysis.
Generates a single standardized submission-style CTF writeup optimized for in-competition speed, clarity, and reproducibility, with one complete solve script from challenge data to final flag. Auto-collects metadata, solution artifacts, and timeline, then enforces a quality checklist (metadata complete, runnable code, no sensitive data) before finalizing `writeup.md`.
Quick-reference cheat sheet for AI/ML CTF challenges covering model weight perturbation negation, model inversion, encoder collisions, LoRA adapter merging/exploitation, model extraction and membership inference, adversarial examples (FGSM/PGD/C&W), adversarial patches, data poisoning, and LLM attacks (prompt injection, jailbreaking, token smuggling, tool-use exploitation). Bundles ready-to-run inspection commands for `.pt`/`safetensors`/HuggingFace/LoRA models and points to detail files (`model-attacks.md`, `adversarial-ml.md`, `llm-attacks.md`) for each technique.
Skill