ctf-forensics 是做什么的？
提供 CTF 挑战中的数字取证和信号分析技术。用于分析磁盘镜像、内存转储、事件日志、网络抓包、加密货币交易、隐写术、PDF 分析、Windows 注册表、Volatility、PCAP、Docker 镜像、核心转储、侧信道功率迹线、DTMF 音频频谱图、数据包时序分析、CD 音频光盘映像，或恢复已删除的文件和凭据。
提供 CTF 挑战中的数字取证和信号分析技术。用于分析磁盘镜像、内存转储、事件日志、网络抓包、加密货币交易、隐写术、PDF 分析、Windows 注册表、Volatility、PCAP、Docker 镜像、核心转储、侧信道功率迹线、DTMF 音频频谱图、数据包时序分析、CD 音频光盘映像，或恢复已删除的文件和凭据。
该技能专为 CTF 竞赛中的数字取证和信号分析任务设计。它涵盖了广泛的取证场景，包括磁盘镜像、内存转储、事件日志、网络抓包、加密货币交易、隐写术、PDF 分析、Windows 注册表分析、Volatility 内存分析、PCAP 网络流量分析、Docker 镜像分析、核心转储分析、侧信道功率迹线分析、DTMF 音频频谱图分析、数据包时序分析、CD 音频光盘映像分析，以及恢复已删除的文件和凭据。支持 Volatility、PCAP 等主流工具和分析方法，适用于需要深入挖掘隐藏信息或恢复被破坏数据的 CTF 挑战场景。通过整合这些技术，用户可以高效地应对复杂取证问题，识别攻击路径和关键线索。
npx skills add https://github.com/ljagiello/ctf-skills/tree/main/skills/ctf-forensicsInstalled? 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 CTF 挑战中的数字取证和信号分析技术。用于分析磁盘镜像、内存转储、事件日志、网络抓包、加密货币交易、隐写术、PDF 分析、Windows 注册表、Volatility、PCAP、Docker 镜像、核心转储、侧信道功率迹线、DTMF 音频频谱图、数据包时序分析、CD 音频光盘映像，或恢复已删除的文件和凭据。
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 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 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.
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.