maxtac-dast-fuzzer

Coverage-guided fuzzing for binary applications uses AFL++ and ASan instrumentation to automatically discover vulnerabilities. It mutates inputs based on code coverage feedback to maximize edge discovery and expose memory corruption issues in local test environments.

Dynamic binary fuzzing is an automated vulnerability research technique that executes compiled binaries with malformed inputs to trigger crashes. It is needed when analyzing parsers, native libraries, or kernels without source code to uncover hidden memory corruption flaws.

Yes, this fuzzing approach integrates directly with AFL++ and AddressSanitizer. It leverages ASan for immediate crash detection and coverage-guided techniques to efficiently navigate complex code paths within authorized local or disposable testing environments.

To initialize a fuzzing campaign, run the provided Python script with parameters for your target binary, AFL++ tool version, instrumentation type, and seed corpus. This sets up the environment and command syntax for automated vulnerability discovery.

Yes, all fuzzing inputs, scripts, and generated artifacts are persisted during the campaign. This ensures that crash data and evidence are saved for later analysis, debugging, and vulnerability verification.

Fuzzing campaigns are restricted to authorized programs within local, isolated, or disposable environments. This rate-limits the scope to local test hosts to prevent unintended execution against unauthorized external targets.