external/anthropic-cybersecurity-skills/skills/performing-fuzzing-with-aflplusplus/SKILL.md
Performs coverage-guided fuzzing of compiled binaries with AFL++, instrumenting targets via afl-cc/afl-clang-fast, minimizing corpora with afl-cmin and afl-tmin, running parallel campaigns with afl-fuzz, and triaging crashes with CASR or GDB scripts. Use for binary fuzzing, crash and memory-corruption discovery, coverage-guided testing, or running AFL++ fuzzing campaigns.
npx skillsauth add seikaikyo/dash-skills performing-fuzzing-with-aflplusplusInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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AFL++ is a community-maintained fork of American Fuzzy Lop (AFL) that provides coverage-guided fuzzing for compiled binaries. It instruments targets at compile time or via QEMU/Unicorn mode for binary-only fuzzing, then mutates input corpora to discover new code paths. AFL++ includes advanced scheduling (MOpt, rare), custom mutators, CMPLOG for input-to-state comparison solving, and persistent mode for high-throughput fuzzing.
apt install afl++ or build from source)afl-cc or afl-clang-fastafl-cmin to remove redundant seedsafl-fuzz with appropriate flags (-i input -o output)afl-tmin minimization and CASR/GDB analysis+++ Findings +++
unique crashes: 12
unique hangs: 3
last crash: 00:02:15 ago
+++ Coverage +++
map density: 4.23% / 8.41%
paths found: 1847
exec speed: 2145/sec
tools
Conduct comprehensive GDPR compliance assessments by evaluating data processing activities against EU Regulation 2016/679, including Article 30 records of processing, lawful basis validation, data subject rights implementation, Data Protection Impact Assessments (DPIAs) under Article 35, breach notification procedures, international transfer safeguards (SCCs, adequacy decisions), and technical/organizational measures under Article 32. Use when processing personal data of EU residents, preparing for supervisory authority audits, implementing privacy-by-design for new systems, scoping compliance gaps for M&A due diligence, assessing third-party processors, or responding to data subject access requests at scale. Incorporates 2026 guidance from ICO, EDPB, and post-Data (Use and Access) Act 2025 UK-GDPR considerations. Do not use for implementing specific Article 32 controls — use implementing-gdpr-data-protection-controls; or for DSAR automation — use implementing-gdpr-data-subject-access-request.
tools
Parse Windows forensic artifacts—$MFT/$J (MFTECmd), Prefetch (PECmd), registry hives (RECmd), shellbags, and Amcache—into normalized CSV/JSON with Eric Zimmerman's EZ Tools, then load results into Timeline Explorer for analysis. Use during DFIR/incident-response investigations, after triage collection (e.g. with KAPE), to establish program execution, file/folder access, and persistence evidence from acquired forensic images.
development
Build automated multi-turn adversarial attacks against conversational LLM targets using Microsoft PyRIT's RedTeamingOrchestrator, CrescendoOrchestrator (gradual escalation), and TreeOfAttacksWithPruningOrchestrator (adaptive branching), with scorer feedback loops and persisted conversation memory. Use when single-shot LLM scanning is insufficient and you need multi-turn, scorer-driven AI red-team campaigns against a chatbot or agent.
testing
Stand up MISP, enable and cache curated threat feeds (CIRCL, abuse.ch, Feodo Tracker), apply warninglists to suppress false positives, query indicators with PyMISP, and export attributes as auto-generated Suricata/Sigma/Wazuh detection rules. Use when maturing a MISP instance to actively drive detection, curating threat feeds with quality controls, or automating IOC-to-detection pipelines for the SIEM/IDS.