ctf-malware 是做什么的？
提供针对 CTF 挑战的恶意软件分析与网络流量技术。适用于分析混淆脚本、恶意软件包、自定义加密协议、C2 流量、PE/.NET 二进制文件、RC4/AES 加密通信、YARA 规则、Shellcode 分析、内存取证（Volatility malfind、进程注入检测）、反分析技术（VM/沙箱检测、定时逃避、API 哈希、进程注入、环境检查）以及提取恶意软件配置和入侵指标。
提供针对 CTF 挑战的恶意软件分析与网络流量技术。适用于分析混淆脚本、恶意软件包、自定义加密协议、C2 流量、PE/.NET 二进制文件、RC4/AES 加密通信、YARA 规则、Shellcode 分析、内存取证（Volatility malfind、进程注入检测）、反分析技术（VM/沙箱检测、定时逃避、API 哈希、进程注入、环境检查）以及提取恶意软件配置和入侵指标。
该技能专为 CTF 挑战中的恶意软件分析设计，提供一套全面的技术来应对各类恶意软件问题。它支持分析混淆脚本、恶意软件包、自定义加密协议、C2（命令与控制）流量、PE 和 .NET 二进制文件以及 RC4/AES 加密通信。技能涵盖从静态分析（如 YARA 规则编写和 Shellcode 分析）到动态分析（如基于 Volatility 的 malfind 内存取证和进程注入检测）的全流程。此外，还专注于反分析技术，包括 VM/沙箱检测、定时逃避、API 哈希、进程注入和环境检查，并能够提取恶意软件配置和入侵指标（IOC）。该技能适用于 Cursor、Claude Code 等 AI 代理平台，通过对恶意样本的系统分析，帮助用户识别威胁、理解恶意行为并构建有效防御。
npx skills add https://github.com/ljagiello/ctf-skills/tree/main/skills/ctf-malwareInstalled? 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 挑战的恶意软件分析与网络流量技术。适用于分析混淆脚本、恶意软件包、自定义加密协议、C2 流量、PE/.NET 二进制文件、RC4/AES 加密通信、YARA 规则、Shellcode 分析、内存取证（Volatility malfind、进程注入检测）、反分析技术（VM/沙箱检测、定时逃避、API 哈希、进程注入、环境检查）以及提取恶意软件配置和入侵指标。
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 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.