ctf-reverse 是做什么的？
提供针对CTF挑战的逆向工程技术。适用于理解编译、混淆、加壳或虚拟化目标的工作原理，包括二进制文件、APK、WASM、固件、自定义虚拟机、字节码、游戏客户端、恶意软件类加载器以及反调试或反分析逻辑。当漏洞已被理解且剩余任务是利用时，请勿使用本技能；应改用 pwn。不适用于纯Web工作流、日志或磁盘取证、或独立的密码学问题，除非逆向实现是真正的瓶颈。
提供针对CTF挑战的逆向工程技术。适用于理解编译、混淆、加壳或虚拟化目标的工作原理，包括二进制文件、APK、WASM、固件、自定义虚拟机、字节码、游戏客户端、恶意软件类加载器以及反调试或反分析逻辑。
ljagiello/ctf-reverse 是一个专注于CTF（Capture The Flag）挑战中逆向工程的技能。它适用于需要深入理解编译、混淆、加壳或虚拟化目标（如二进制文件、APK、WASM、固件、自定义虚拟机、字节码、游戏客户端、恶意软件加载器以及反调试或反分析逻辑）工作机制的场景。该技能在漏洞已被理解且后续任务是利用时不应使用（应使用 pwn 技能），也不适用于纯Web工作流、日志或磁盘取证、或独立的密码学问题（除非逆向实现是真正的瓶颈）。它支持多种平台，包括二进制分析、APK逆向、WASM分析、固件逆向等，通过提供系统化的逆向工程技术帮助用户绕过混淆、分析自定义架构、识别反调试机制、解包加壳代码，最终理解目标内部逻辑。
npx skills add https://github.com/ljagiello/ctf-skills/tree/main/skills/ctf-reverseInstalled? Explore more 研究与数据分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
提供针对CTF挑战的逆向工程技术。适用于理解编译、混淆、加壳或虚拟化目标的工作原理，包括二进制文件、APK、WASM、固件、自定义虚拟机、字节码、游戏客户端、恶意软件类加载器以及反调试或反分析逻辑。当漏洞已被理解且剩余任务是利用时，请勿使用本技能；应改用 pwn。不适用于纯Web工作流、日志或磁盘取证、或独立的密码学问题，除非逆向实现是真正的瓶颈。
This repo contains 10 individual skills — each has its own dedicated page.
Provides AI and machine learning techniques for CTF challenges. Use when attacking ML models, crafting adversarial examples, performing model extraction, prompt injection, membership inference, training data poisoning, fine-tuning manipulation, neural network analysis, LoRA adapter exploitation, LLM jailbreaking, or solving AI-related puzzles.
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.
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.
Provides malware analysis and network traffic techniques for CTF challenges. Use when analyzing obfuscated scripts, malicious packages, custom crypto protocols, C2 traffic, PE/.NET binaries, RC4/AES encrypted communications, YARA rules, shellcode analysis, memory forensics for malware (Volatility malfind, process injection detection), anti-analysis techniques (VM/sandbox detection, timing evasion, API hashing, process injection, environment checks), or extracting malware configurations and indicators of compromise.
Provides miscellaneous CTF challenge techniques for problems that do not cleanly fit the main categories. Use for encoding puzzles, pyjails, bash jails, RF/SDR, DNS oddities, unicode tricks, esoteric languages, QR or audio puzzles, constraint solving, game theory, unusual sandbox escapes, and hybrid logic puzzles. Prefer a more specific skill first when the challenge is mainly web, pwn, reverse, forensics, malware, OSINT, or crypto. Treat this as the fallback skill for genuine cross-category or edge-case challenges, not the default starting point.
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.
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.
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.
Generates a single standardized submission-style CTF writeup for competition handoff and organizer review. Use after solving a CTF challenge to document the solution steps, tools used, and lessons learned in a structured format.
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.
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Agent skill repository discovered by 10x-chat research.
Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.