Aflpp

Trail of BitsOfficialPublished by Trail of Bits

Skill
Tool integration
Security
CC-BY-SA-4.0
Low risk

From the author

Sets up and runs AFL++ for multi-core fuzzing of C/C++ projects built with afl-clang-fast or afl-gcc-fast. Covers instrumentation modes, parallel main and secondary campaigns, persistent mode, corpus minimization, and crash triage. Use when scaling fuzzing across cores, fuzzing a mature C/C++ codebase, reading the afl-fuzz status screen, or moving on after libFuzzer has plateaued.

— the description by Trail of Bits

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

AFL++ is a fuzzer for C and C++ codebases that supports multi-core execution, persistent mode, and various instrumentation modes. This skill provides instructions for configuring the environment, compiling targets with afl-clang-fast or afl-gcc-fast, managing seed corpora, and triaging crashes. It covers the setup of wrapper scripts for Docker or host-based execution and details how to interpret fuzzer statistics and manage parallel fuzzing campaigns.

What it does

Configures AFL++ for multi-core fuzzing campaigns
Provides compilation steps for C/C++ projects using specialized compilers
Explains how to manage and minimize seed corpora
Details the setup of persistent mode for increased execution throughput
Offers guidance on crash triage and coverage analysis
Includes instructions for integrating sanitizers like ASan and UBSan

When to use it

When scaling fuzzing efforts across multiple CPU cores
When fuzzing mature C/C++ codebases
When libFuzzer is no longer providing sufficient coverage
When you need to perform crash triage on discovered inputs

Advantages

Supports parallel execution across multiple cores
Compatible with diverse mutation strategies
Provides mature tooling for corpus management and crash analysis
Offers flexible instrumentation modes for different project requirements

Usage examples

“How do I start a primary fuzzer instance for a multi-core campaign?”: The skill provides a command to run afl-fuzz with the -M flag to designate a primary instance, including necessary backgrounding and output redirection.
“How can I compile my C++ project for use with AFL++?”: The skill outlines using afl-clang-fast++ with specific flags like -DNO_MAIN=1 and -fsanitize=fuzzer to prepare the target for fuzzing.

Install

Download the skill as a ZIP:
https://autogineer.com/agent-skills/trailofbits/aflpp/download
Unzip it into the cross-client skills folder of your project:
```
mkdir -p .agents/skills && unzip aflpp.zip -d .agents/skills
```

Documentation by Trail of Bits

AFL++

AFL++ is a fork of the original AFL fuzzer that offers better fuzzing performance and more advanced features while maintaining stability. A major benefit over libFuzzer is that AFL++ has stable support for running fuzzing campaigns on multiple cores, making it ideal for large-scale fuzzing efforts.

When to Use

Fuzzer	Best For	Complexity
AFL++	Multi-core fuzzing, diverse mutations, mature projects	Medium
libFuzzer	Quick setup, single-threaded, simple harnesses	Low
LibAFL	Custom fuzzers, research, advanced use cases	High

Choose AFL++ when:

You need multi-core fuzzing to maximize throughput
Your project can be compiled with Clang or GCC
You want diverse mutation strategies and mature tooling
libFuzzer has plateaued and you need more coverage
You're fuzzing production codebases that benefit from parallel execution

Quick Start

extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {
    // Call your code with fuzzer-provided data
    check_buf((char*)data, size);
    return 0;
}

Compile and run:

# Setup AFL++ wrapper script first (see Installation)
./afl++ docker afl-clang-fast++ -DNO_MAIN=1 -O2 -fsanitize=fuzzer harness.cc main.cc -o fuzz
mkdir seeds && echo "aaaa" > seeds/minimal_seed
./afl++ docker afl-fuzz -i seeds -o out -- ./fuzz

Installation

AFL++ has many dependencies including LLVM, Python, and Rust. We recommend using a current Debian or Ubuntu distribution for fuzzing with AFL++.

Method	When to Use	Supported Compilers
Ubuntu/Debian repos	Recent Ubuntu, basic features only	Ubuntu 23.10: Clang 14 & GCC 13<br>Debian 12: Clang 14 & GCC 12
Docker (from Docker Hub)	Specific AFL++ version, Apple Silicon support	As of 4.35c: Clang 19 & GCC 11
Docker (from source)	Test unreleased features, apply patches	Configurable in Dockerfile
From source	Avoid Docker, need specific patches	Adjustable via `LLVM_CONFIG` env var

Ubuntu/Debian

Prior to installing afl++, check the clang version dependency of the packge with apt-cache show afl++, and install the matching lld version (e.g., lld-17).

apt install afl++ lld-17

Docker (from Docker Hub)

docker pull aflplusplus/aflplusplus:stable

Docker (from source)

git clone --depth 1 --branch stable https://github.com/AFLplusplus/AFLplusplus
cd AFLplusplus
docker build -t aflplusplus .

From source

Refer to the Dockerfile for Ubuntu version requirements and dependencies. Set LLVM_CONFIG to specify Clang version (e.g., llvm-config-18).

Wrapper Script Setup

Create a wrapper script to run AFL++ on host or Docker:

cat <<'EOF' > ./afl++
#!/bin/sh
AFL_VERSION="${AFL_VERSION:-"stable"}"
case "$1" in
   host)
        shift
        bash -c "$*"
        ;;
    docker)
        shift
        /usr/bin/env docker run -i \
            --privileged \
            -v ./:/src \
            --rm \
            --name "afl_fuzzing_$$" \
            "aflplusplus/aflplusplus:$AFL_VERSION" \
            bash -c "cd /src && bash -c \"$*\""
        ;;
    *)
        echo "Usage: $0 {host|docker}"
        exit 1
        ;;
esac
EOF
chmod +x ./afl++

The examples below use docker mode, apart from the system configuration commands that have to reach the host kernel. Swap in host to run any of them against an AFL++ installed on the machine itself. The wrapper joins everything after the mode argument into a single shell string, so quoting does not survive: an argument containing a space (-x "my dict.dict") arrives word-split. Rename such files without spaces, or edit the wrapper for that run.

The missing -t is deliberate. docker run -ti aborts with the input device is not a TTY whenever stdin is not a terminal, which covers CI jobs and anything an agent or script drives. afl-fuzz notices there is no terminal and prints plain status lines in place of the full-screen UI. A program that insists on a terminal, such as watch, has to run on the host side of the wrapper instead. $$ expands to the wrapper's PID, so parallel instances get distinct container names rather than colliding on a single afl_fuzzing. docker ps truncates the COMMAND column, so every row looks alike; use docker ps --no-trunc to tell the instances apart before stopping one.

Security Warning: The afl-system-config and afl-persistent-config scripts require root privileges and disable OS security features. Do not fuzz on production systems or your development environment. Use a dedicated VM instead.

System Configuration

Run after each reboot for up to 15% more executions per second:

./afl++ host afl-system-config

afl-system-config tunes the kernel it runs against, so run it on the machine that hosts the campaign. ./afl++ docker afl-system-config reaches the same settings through the wrapper's --privileged container, which is the only route when AFL++ is installed via Docker alone.

For maximum performance, disable kernel security mitigations (requires grub bootloader, not supported in Docker):

./afl++ host afl-persistent-config
update-grub
reboot
./afl++ host afl-system-config

Verify with cat /proc/cmdline - output should include mitigations=off.

Writing a Harness

Harness Structure

AFL++ supports libFuzzer-style harnesses:

#include <stdint.h>
#include <stddef.h>

extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {
    // 1. Validate input size if needed
    if (size < MIN_SIZE || size > MAX_SIZE) return 0;

    // 2. Call target function with fuzz data
    target_function(data, size);

    // 3. Return 0 (non-zero reserved for future use)
    return 0;
}

Harness Rules

Do	Don't
Reset global state between runs	Rely on state from previous runs
Handle edge cases gracefully	Exit on invalid input
Keep harness deterministic	Use random number generators
Free allocated memory	Create memory leaks
Validate input sizes	Process unbounded input

See Also: For detailed harness writing techniques, patterns for handling complex inputs, and advanced strategies, see the fuzz-harness-writing technique skill.

Compilation

AFL++ offers multiple compilation modes with different trade-offs.

Compilation Mode Decision Tree

Choose your compilation mode:

LTO mode (afl-clang-lto): Best performance and instrumentation. Try this first.
LLVM mode (afl-clang-fast): Fall back if LTO fails to compile.
GCC plugin (afl-gcc-fast): For projects requiring GCC.

Basic Compilation (LLVM mode)

./afl++ docker afl-clang-fast++ -DNO_MAIN=1 -O2 -fsanitize=fuzzer harness.cc main.cc -o fuzz

GCC Compilation

./afl++ docker afl-g++-fast -DNO_MAIN=1 -O2 -fsanitize=fuzzer harness.cc main.cc -o fuzz

Important: GCC version must match the version used to compile the AFL++ GCC plugin.

With Sanitizers

./afl++ docker AFL_USE_ASAN=1 afl-clang-fast++ -DNO_MAIN=1 -O2 -fsanitize=fuzzer harness.cc main.cc -o fuzz

See Also: For detailed sanitizer configuration, common issues, and advanced flags, see the address-sanitizer and undefined-behavior-sanitizer technique skills.

Build Flags

Note that -g is not necessary, it is added by default by the AFL++ compilers.

Flag	Purpose
`-DNO_MAIN=1`	Skip main function when using libFuzzer harness
`-O2`	Production optimization level (recommended for fuzzing)
`-fsanitize=fuzzer`	Enable libFuzzer compatibility mode and adds the fuzzer runtime when linking executable
`-fsanitize=fuzzer-no-link`	Instrument without linking fuzzer runtime (for static libraries and object files)

Corpus Management

Creating Initial Corpus

AFL++ requires at least one non-empty seed file:

mkdir seeds
echo "aaaa" > seeds/minimal_seed

For real projects, gather representative inputs:

Download example files for the format you're fuzzing
Extract test cases from the project's test suite
Use minimal valid inputs for your file format

Corpus Minimization

After a campaign, minimize the corpus to keep only unique coverage:

./afl++ docker afl-cmin -i out/default/queue -o minimized_corpus -- ./fuzz

See Also: For corpus creation strategies, dictionaries, and seed selection, see the fuzzing-corpus technique skill.

Running Campaigns

Basic Run

./afl++ docker afl-fuzz -i seeds -o out -- ./fuzz

Setting Environment Variables

./afl++ docker AFL_FAST_CAL=1 afl-fuzz -i seeds -o out -- ./fuzz

Interpreting Output

AFL++ reports these statistics either way, but how you read them depends on the mode. The wrapper's docker run -i gives the container no TTY, so afl-fuzz drops the full-screen UI and writes plain status lines to the log instead — the fields below appear there, and in state/<instance>/fuzzer_stats. To get the interactive UI, run host mode in a terminal, or add -t to the wrapper for a run you are watching by hand.

Output	Meaning
execs/sec	Execution speed - higher is better
cycles done	Number of queue passes completed
corpus count	Number of unique test cases in queue
saved crashes	Number of unique crashes found
stability	% of stable edges (should be near 100%)

Output Directory Structure

out/default/
├── cmdline          # How was the SUT invoked?
├── crashes/         # Inputs that crash the SUT
│   └── id:000000,sig:06,src:000002,time:286,execs:13105,op:havoc,rep:4
├── hangs/           # Inputs that hang the SUT
├── queue/           # Test cases reproducing final fuzzer state
│   ├── id:000000,time:0,execs:0,orig:minimal_seed
│   └── id:000001,src:000000,time:0,execs:8,op:havoc,rep:6,+cov
├── fuzzer_stats     # Campaign statistics
└── plot_data        # Data for plotting

Analyzing Results

View live campaign statistics:

./afl++ docker afl-whatsup out

Create coverage plots. The aflplusplus image already ships gnuplot-nox; in host mode, install gnuplot first with apt install gnuplot.

./afl++ docker afl-plot out/default out_graph/

Re-executing Test Cases

Pass one of the filenames from out/default/crashes/:

./afl++ docker ./fuzz out/default/crashes/id:000000,sig:06,src:000002,time:286,execs:13105,op:havoc,rep:4

Fuzzer Options

Option	Purpose
`-G 4000`	Maximum test input length (default: 1048576 bytes)
`-t 1000`	Timeout in milliseconds for each test case (default: 1000ms)
`-m 1000`	Memory limit in megabytes (default: 0 = unlimited)
`-x ./dict.dict`	Use dictionary file to guide mutations

Environment Variables That Matter

AFL++ has many environment variables, but most are niche. These are the ones that matter in practice.

Always Set These

# Every campaign should use tmpfs — SSDs will thank you, and it's faster
AFL_TMPDIR=/dev/shm

AFL_TMPDIR is a free performance win with no downsides — not setting it wears out your SSD and slows fuzzing.

Slow Targets

# Speeds up calibration ~2.5x — use when targets are slow (e.g., >10 ms/exec)
AFL_FAST_CAL=1

AFL_FAST_CAL reduces calibration time with negligible precision loss. Recommended specifically for slow targets where calibration would otherwise take a long time.

Multi-Core Campaigns

# On the primary (-M) instance only — needed for afl-cmin, not for fuzzing itself
AFL_FINAL_SYNC=1

# On all instances — cache test cases in memory (default: 50 MB, good range: 50-250 MB)
AFL_TESTCACHE_SIZE=100

AFL_FINAL_SYNC tells the primary instance to do a final import from all secondaries when stopping. This does not affect the fuzzing process itself — it only matters when you later run afl-cmin for corpus minimization, ensuring the primary's queue has the full combined corpus. AFL_TESTCACHE_SIZE caches test cases in memory to reduce disk I/O; the default is 50 MB and values between 50-250 MB work well for most campaigns.

CI/Automated Fuzzing

# Fail fast if fuzzing isn't finding anything
AFL_EXIT_ON_TIME=3600  # 1 hour with no new paths = stop

# Or run until "done" (all queue entries processed)
AFL_EXIT_WHEN_DONE=1

# Headless environments
AFL_NO_UI=1

Unbounded fuzzing in CI wastes resources. Set time limits or use exit conditions.

Variables to Avoid

Variable	Why Skip It
`AFL_NO_ARITH`	Can hurt coverage on binary formats, but may be useful for text-based targets
`AFL_SHUFFLE_QUEUE`	Only for exotic setups, usually harmful
`AFL_DISABLE_TRIM`	Trimming is valuable, don't disable without reason

Multi-Core Fuzzing

AFL++ excels at multi-core fuzzing with two major advantages:

More executions per second (scales linearly with physical cores)
Asymmetrical fuzzing (e.g., one ASan job, rest without sanitizers)

Starting a Campaign

Start the primary fuzzer (in background):

./afl++ docker afl-fuzz -M primary -i seeds -o state -- ./fuzz 1>primary.log 2>primary.error </dev/null &

Start secondary fuzzers (as many as you have cores):

./afl++ docker afl-fuzz -S secondary01 -i seeds -o state -- ./fuzz 1>secondary01.log 2>secondary01.error </dev/null &
./afl++ docker afl-fuzz -S secondary02 -i seeds -o state -- ./fuzz 1>secondary02.log 2>secondary02.error </dev/null &

The </dev/null is required, not decorative. docker run -i keeps the client reading its own stdin, and a backgrounded process that reads the terminal is sent SIGTTIN, whose default action stops it — so without the redirect these jobs show up as Stopped in jobs and never fuzz.

Monitoring Multi-Core Campaigns

List all running jobs:

jobs

View live statistics. watch needs a terminal that docker run -i does not give it, so wrap the whole invocation instead of running watch inside the container. Every tick starts a container, which is why the interval is 5 seconds rather than 1:

watch -n5 --color ./afl++ docker afl-whatsup state/

Stopping All Fuzzers

kill $(jobs -p)

Coverage Analysis

AFL++ automatically tracks coverage through edge instrumentation. Coverage information is stored in fuzzer_stats and plot_data.

Measuring Coverage

Use afl-plot to visualize coverage over time:

./afl++ docker afl-plot out/default out_graph/

Improving Coverage

Use dictionaries for format-aware fuzzing
Run longer campaigns (cycles_wo_finds indicates plateau)
Try different mutation strategies with multi-core fuzzing
Analyze coverage gaps and add targeted seed inputs

See Also: For detailed coverage analysis techniques, identifying coverage gaps, and systematic coverage improvement, see the coverage-analysis technique skill.

CMPLOG

CMPLOG/RedQueen is the best path constraint solving mechanism available in any fuzzer. To enable it, the fuzz target needs to be instrumented for it. Before building the fuzzing target set the environment variable:

./afl++ docker AFL_LLVM_CMPLOG=1 make

No special action is needed for compiling and linking the harness.

To run a fuzzer instance with a CMPLOG instrumented fuzzing target, add -c0 to the command like arguments:

./afl++ docker afl-fuzz -c0 -S cmplog -i seeds -o state -- ./fuzz 1>cmplog.log 2>cmplog.error </dev/null &

Sanitizer Integration

Sanitizers are essential for finding memory corruption bugs that don't cause immediate crashes.

AddressSanitizer (ASan)

./afl++ docker AFL_USE_ASAN=1 afl-clang-fast++ -DNO_MAIN=1 -O2 -fsanitize=fuzzer harness.cc main.cc -o fuzz

Note: Memory limit (-m) is not supported with ASan due to 20TB virtual memory reservation.

UndefinedBehaviorSanitizer (UBSan)

./afl++ docker AFL_USE_UBSAN=1 afl-clang-fast++ -DNO_MAIN=1 -O2 -fsanitize=fuzzer,undefined harness.cc main.cc -o fuzz

Common Sanitizer Issues

Issue	Solution
ASan slows fuzzing	Use only 1 ASan job in multi-core setup
Stack exhaustion	Increase stack with `ASAN_OPTIONS=stack_size=...`
GCC version mismatch	Ensure system GCC matches AFL++ plugin version

See Also: For comprehensive sanitizer configuration and troubleshooting, see the address-sanitizer technique skill.

Advanced Usage

Tips and Tricks

Tip	Why It Helps
Use LLVMFuzzerTestOneInput harnesses where possible	If a fuzzing campaign has at least 85% stability then this is the most efficient fuzzing style. If not then try standard input or file input fuzzing
Use dictionaries	Helps fuzzer discover format-specific keywords and magic bytes
Set realistic timeouts	Prevents false positives from system load
Limit input size	Larger inputs don't necessarily explore more space
Monitor stability	Low stability indicates non-deterministic behavior

Standard Input Fuzzing

AFL++ can fuzz programs reading from stdin without a libFuzzer harness:

./afl++ docker afl-clang-fast++ -O2 main_stdin.c -o fuzz_stdin
./afl++ docker afl-fuzz -i seeds -o out -- ./fuzz_stdin

This is slower than persistent mode but requires no harness code.

File Input Fuzzing

For programs that read files, use @@ placeholder:

./afl++ docker afl-clang-fast++ -O2 main_file.c -o fuzz_file
./afl++ docker afl-fuzz -i seeds -o out -- ./fuzz_file @@

For better performance, use fmemopen to create file descriptors from memory.

Argument Fuzzing

Fuzz command-line arguments using argv-fuzz-inl.h:

#include <stdio.h>
#include <stdlib.h>
#include <string.h>

#ifdef __AFL_COMPILER
#include "argv-fuzz-inl.h"
#endif

void check_buf(char *buf, size_t buf_len) {
    if(buf_len > 0 && buf[0] == 'a') {
        if(buf_len > 1 && buf[1] == 'b') {
            if(buf_len > 2 && buf[2] == 'c') {
                abort();
            }
        }
    }
}

int main(int argc, char *argv[]) {
#ifdef __AFL_COMPILER
    AFL_INIT_ARGV();
#endif

    if (argc < 2) {
        fprintf(stderr, "Usage: %s <input_string>\n", argv[0]);
        return 1;
    }

    char *input_buf = argv[1];
    size_t len = strlen(input_buf);
    check_buf(input_buf, len);
    return 0;
}

Download the header:

curl -O https://raw.githubusercontent.com/AFLplusplus/AFLplusplus/stable/utils/argv_fuzzing/argv-fuzz-inl.h

Compile and run:

./afl++ docker afl-clang-fast++ -O2 main_arg.c -o fuzz_arg
./afl++ docker afl-fuzz -i seeds -o out -- ./fuzz_arg

Performance Tuning

Setting	Impact
CPU core count	Linear scaling with physical cores
Persistent mode	10-20x faster than fork server
`-G` input size limit	Smaller = faster, but may miss bugs
ASan ratio	1 ASan job per 4-8 non-ASan jobs

Troubleshooting

Problem	Cause	Solution
Low exec/sec (<1k)	Not using persistent mode	Create a LLVMFuzzerTestOneInput style harness
Low stability (<85%)	Non-deterministic code	Fuzz a program via stdin or file inputs, or create such a harness
GCC plugin error	GCC version mismatch	Ensure system GCC matches AFL++ build and install gcc-$GCC_VERSION-plugin-dev
No crashes found	Need sanitizers	Recompile with `AFL_USE_ASAN=1`
Memory limit exceeded	ASan uses 20TB virtual	Remove `-m` flag when using ASan
Docker performance loss	Virtualization overhead	Use bare metal or VM for production fuzzing

Technique Skills

Skill	Use Case
fuzz-harness-writing	Detailed guidance on writing effective harnesses
address-sanitizer	Memory error detection during fuzzing
undefined-behavior-sanitizer	Detect undefined behavior bugs
fuzzing-corpus	Building and managing seed corpora
fuzzing-dictionaries	Creating dictionaries for format-aware fuzzing

Skill	When to Consider
libfuzzer	Quick prototyping, single-threaded fuzzing is sufficient
libafl	Need custom mutators or research-grade features

Resources

Key External Resources

AFL++ GitHub Repository Official repository with comprehensive documentation, examples, and issue tracker.

Fuzzing in Depth Advanced documentation by the AFL++ team covering instrumentation modes, optimization techniques, and advanced use cases.

AFL++ Under The Hood Technical deep-dive into AFL++ internals, mutation strategies, and coverage tracking mechanisms.

AFL++: Combining Incremental Steps of Fuzzing Research Research paper describing AFL++ architecture and performance improvements over original AFL.

Video Resources

Fuzzing cURL - Trail of Bits blog post on using AFL++ argument fuzzing for cURL
Sudo Vulnerability Walkthrough - LiveOverflow series on rediscovering CVE-2021-3156
Rediscovery of libpng bug - LiveOverflow video on finding CVE-2023-4863

Files

ATTRIBUTION.mdAdded by AutoGineer927 B
LICENSELicence file added by AutoGineer19.7 KiB
SKILL.md21.9 KiB
agents/openai.yaml220 B
assets/trail-of-bits-mark.svg3.0 KiB

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  m. You means the individual or entity exercising the Licensed Rights
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Section 2 -- Scope.

  a. License grant.

       1. Subject to the terms and conditions of this Public License,
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            b. produce, reproduce, and Share Adapted Material.

       2. Exceptions and Limitations. For the avoidance of doubt, where
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          its terms and conditions.

       3. Term. The term of this Public License is specified in Section
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       4. Media and formats; technical modifications allowed. The
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       5. Downstream recipients.

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  b. Other rights.

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            b. indicate if You modified the Licensed Material and
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       2. You may satisfy the conditions in Section 3(a)(1) in any
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  b. ShareAlike.

     In addition to the conditions in Section 3(a), if You Share
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Where the Licensed Rights include Sui Generis Database Rights that
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     including for purposes of Section 3(b); and
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For the avoidance of doubt, this Section 4 supplements and does not
replace Your obligations under this Public License where the Licensed
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Section 5 -- Disclaimer of Warranties and Limitation of Liability.

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Section 6 -- Term and Termination.

  a. This Public License applies for the term of the Copyright and
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  b. Where Your right to use the Licensed Material has terminated under
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       1. automatically as of the date the violation is cured, provided
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          violation; or

       2. upon express reinstatement by the Licensor.

     For the avoidance of doubt, this Section 6(b) does not affect any
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  c. For the avoidance of doubt, the Licensor may also offer the
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  d. Sections 1, 5, 6, 7, and 8 survive termination of this Public
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Section 7 -- Other Terms and Conditions.

  a. The Licensor shall not be bound by any additional or different
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  b. Any arrangements, understandings, or agreements regarding the
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Section 8 -- Interpretation.

  a. For the avoidance of doubt, this Public License does not, and
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  b. To the extent possible, if any provision of this Public License is
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  c. No term or condition of this Public License will be waived and no
     failure to comply consented to unless expressly agreed to by the
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  d. Nothing in this Public License constitutes or may be interpreted
     as a limitation upon, or waiver of, any privileges and immunities
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     processes of any jurisdiction or authority.


=======================================================================

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Creative Commons may be contacted at creativecommons.org.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs network access, Needs a command-line tool

Security

What our scanner noticed· Low risk

Instructions that use the network

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by

Trail of Bits

Publisher

Trail of Bits (Official)

Source

trailofbits/skills · plugins/testing-handbook-skills/skills/aflpp · commit e4dd0bb

Licence

Creative Commons Attribution-ShareAlike 4.0 International (redistribution allowed)

LICENSE (added by AutoGineer from LICENSE)
ATTRIBUTION.md (written by AutoGineer)

Synced

2026-11-09

AutoGineer is not affiliated with or endorsed by Trail of Bits or Trail of Bits.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download aflpp.zip