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https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git
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mukul975
cb8d79e068
- Add validated mitre_attack frontmatter to all 754 skills (286 distinct techniques), verified against MITRE ATT&CK v19.1 via the official mitreattack-python library: 0 revoked, deprecated, or invalid IDs - Curate precise per-skill technique IDs for forensics, malware-analysis, threat-intel, and red-team skills (e.g. DCSync -> T1003.006, Kerberoasting -> T1558.003, Pass-the-Ticket -> T1550.003) - Reconcile v19.1 tactic restructuring: Defense Evasion split into Stealth (TA0005) and Defense Impairment (TA0112); revoked T1562.* family and T1070.001/.002 remapped to active equivalents (T1685.*) - Normalize word-split tags across 35 skills (remove filename-derived stopword tags, add semantic cybersecurity tags) - Add api-reference.md for 3 skills that were missing it - Update README ATT&CK section with accurate v19.1 tactic distribution
89 lines
2.6 KiB
Markdown
89 lines
2.6 KiB
Markdown
---
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name: performing-fuzzing-with-aflplusplus
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description: 'Perform coverage-guided fuzzing of compiled binaries using AFL++ (American
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Fuzzy Lop Plus Plus) to discover memory corruption, crashes, and security vulnerabilities.
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The tester instruments target binaries with afl-cc/afl-clang-fast, manages input
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corpora with afl-cmin and afl-tmin, runs parallel fuzzing campaigns with afl-fuzz,
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and triages crashes using CASR or GDB scripts. Activates for requests involving
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binary fuzzing, crash discovery, coverage-guided testing, or AFL++ fuzzing campaigns.
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'
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domain: cybersecurity
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subdomain: application-security
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tags:
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- fuzzing
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- aflplusplus
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- coverage-guided
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- crash-triage
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- binary-analysis
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- security-testing
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version: '1.0'
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author: mahipal
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license: Apache-2.0
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nist_ai_rmf:
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- MEASURE-2.7
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- MAP-5.1
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- MANAGE-2.4
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atlas_techniques:
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- AML.T0070
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- AML.T0066
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- AML.T0082
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nist_csf:
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- PR.PS-01
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- PR.PS-04
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- ID.RA-01
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- PR.DS-10
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mitre_attack:
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- T1078
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- T1190
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- T1059
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- T1005
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---
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# Performing Fuzzing with AFL++
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## Overview
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AFL++ is a community-maintained fork of American Fuzzy Lop (AFL) that provides coverage-guided
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fuzzing for compiled binaries. It instruments targets at compile time or via QEMU/Unicorn mode
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for binary-only fuzzing, then mutates input corpora to discover new code paths. AFL++ includes
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advanced scheduling (MOpt, rare), custom mutators, CMPLOG for input-to-state comparison solving,
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and persistent mode for high-throughput fuzzing.
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## When to Use
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- When conducting security assessments that involve performing fuzzing with aflplusplus
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- When following incident response procedures for related security events
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- When performing scheduled security testing or auditing activities
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- When validating security controls through hands-on testing
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## Prerequisites
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- AFL++ installed (`apt install afl++` or build from source)
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- Target binary source code (for compile-time instrumentation) or QEMU mode for binary-only
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- Initial seed corpus of valid inputs for the target format
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- Linux system with /proc/sys/kernel/core_pattern configured
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## Steps
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1. Instrument the target binary with `afl-cc` or `afl-clang-fast`
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2. Prepare seed corpus directory with minimal valid inputs
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3. Minimize corpus with `afl-cmin` to remove redundant seeds
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4. Run `afl-fuzz` with appropriate flags (-i input -o output)
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5. Monitor fuzzing progress via afl-whatsup and UI stats
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6. Triage crashes with `afl-tmin` minimization and CASR/GDB analysis
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7. Report unique crashes with reproduction steps
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## Expected Output
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```
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+++ Findings +++
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unique crashes: 12
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unique hangs: 3
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last crash: 00:02:15 ago
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+++ Coverage +++
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map density: 4.23% / 8.41%
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paths found: 1847
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exec speed: 2145/sec
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```
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