agent security skill risk: medium
AFL++ Coverage-Guided Fuzzing Procedure
The prompt provides an overview, prerequisites, and numbered steps for instrumenting binaries and running AFL++ to discover crashes and new execution paths.
- Policy sensitive
- Human review
- External action: low
SKILL 4 files · 2 folders
SKILL.md
--- name: performing-fuzzing-with-aflplusplus description: "Perform coverage-guided fuzzing of compiled binaries using AFL++ (American Fuzzy Lop Plus Plus) to discover" --- # Performing Fuzzing with AFL++ ## Overview 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. ## When to Use - When conducting security assessments that involve performing fuzzing with aflplusplus - When following incident response procedures for related security events - When performing scheduled security testing or auditing activities - When validating security controls through hands-on testing ## Prerequisites - AFL++ installed (`apt install afl++` or build from source) - Target binary source code (for compile-time instrumentation) or QEMU mode for binary-only - Initial seed corpus of valid inputs for the target format - Linux system with /proc/sys/kernel/core_pattern configured ## Steps 1. Instrument the target binary with `afl-cc` or `afl-clang-fast` 2. Prepare seed corpus directory with minimal valid inputs 3. Minimize corpus with `afl-cmin` to remove redundant seeds 4. Run `afl-fuzz` with appropriate flags (-i input -o output) 5. Monitor fuzzing progress via afl-whatsup and UI stats 6. Triage crashes with `afl-tmin` minimization and CASR/GDB analysis 7. Report unique crashes with reproduction steps ## Expected Output ``` +++ 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 ```
REQUIRED CONTEXT
- target binary
- seed corpus
- AFL++ installation
EXPECTED OUTPUT
- Format
- markdown
- Schema
- text_block · Findings, Coverage
- Constraints
- include overview, when-to-use, prerequisites, numbered steps, and sample findings output
EXAMPLES
Includes one example of expected fuzzing output showing findings and coverage statistics.
QUALITY
- OVERALL
- 0.72
- CLARITY
- 0.90
- SPECIFICITY
- 0.75
- REUSABILITY
- 0.55
- COMPLETENESS
- 0.80
USAGE
Copy the prompt above and paste it into your AI of choice — Claude, ChatGPT, Gemini, or anywhere else you're working. Replace any placeholder sections with your own context, then ask for the output.
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