Results for “api-fuzzing”

Fuzz Python code and C extensions with coverage guidance and AddressSanitizer support using a libFuzzer-based fuzzer.

Fuzz C/C++ projects with multi-core support using AFL++, a fork of AFL with better performance and advanced features.

Write effective fuzzing harnesses across languages to improve code coverage and find bugs in your system under test.

Patch code to bypass checksums, global state, and validation checks that block fuzzer progress, using conditional compilation for C/C++ and Rust.

Coverage-guided fuzzing for Ruby code and C extensions using libFuzzer and sanitizers.

Guides setting up and using Atheris for coverage-guided fuzzing of Python code and C extensions, including Docker setup, harness writing, and corpus management.

AFL++ is a fork of AFL with better fuzzing performance and advanced features. Use for multi-core fuzzing of C/C++ projects.

Build and run custom fuzzers with LibAFL, a modular Rust fuzzing library, including drop-in libFuzzer replacement and custom component configuration.

Atheris is a coverage-guided Python fuzzer based on libFuzzer. Use for fuzzing pure Python code and Python C extensions.

Set up continuous fuzzing infrastructure for open-source projects using Google's OSS-Fuzz platform, including building and running fuzz harnesses locally and enrolling new projects.

Deploys Python web apps (Flask, Django, FastAPI) to Azure App Service Linux with automatic resource creation and framework detection.

Fuzz Rust projects with libFuzzer using cargo-fuzz, including harness writing, sanitizer integration, and coverage analysis.

Build custom fuzzers with a modular Rust library, supporting advanced mutation strategies, custom feedback mechanisms, and non-standard target architectures.

Coverage-guided fuzzer built into LLVM for C/C++ projects. Use for fuzzing C/C++ code that can be compiled with Clang.

Detect memory errors like buffer overflows and use-after-free bugs in C/C++ code during fuzzing and testing using AddressSanitizer.

Detects AI-generated deepfake audio used in voice phishing (vishing) attacks by extracting spectral features and classifying samples with machine learning models.

Generates OpenAPI 3.1 documentation from an API codebase, auto-detecting frameworks, extracting routes and schemas, and setting up interactive docs.

Implements secure API design patterns including authentication, authorization, input validation, rate limiting, and protection against common vulnerabilities.

Ruzzy is a coverage-guided Ruby fuzzer by Trail of Bits. Use for fuzzing pure Ruby code and Ruby C extensions.