Fuzzing and Crash Analysis

Fuzzing and Crash Analysis

Systematic fuzzing identifies buffer overflow vulnerabilities through controlled input testing. Start with valid program inputs, progressively increasing sizes until crashes occur. Python scripts generating patterns of increasing length automate this process. Monitor application behavior through debuggers, noting crash points and exception types. Access violation exceptions writing to invalid addresses often indicate exploitable overflows.

Crash analysis reveals vulnerability characteristics essential for exploitation. Attach debuggers like Immunity Debugger or x64dbg before triggering crashes. Examine register states, particularly EIP values after crashes. If EIP contains values from your input (like 0x41414141 from 'AAAA'), direct control exists. ESP pointing to input portions indicates payload accessibility. Stack examination shows overflow extent and available space.

Pattern generation tools create unique strings enabling precise offset calculation. Metasploit's pattern_create.rb generates non-repeating patterns, while pattern_offset.rb calculates exact positions. Send pattern strings to vulnerable applications, note values overwriting EIP, then calculate offsets. This precision eliminates guesswork from exploit development. Manual pattern creation using unique character sequences provides alternatives when tools aren't available.

Reliable crash reproduction ensures exploit stability. Vary fuzzing inputs to confirm consistent behavior. Test across different payload sizes to understand application tolerances. Some applications crash inconsistently due to threading, requiring multiple attempts or timing adjustments. Document exact steps reproducing crashes, as exam stress can impair memory of successful techniques.