There's a researcher, Jiang Yuancheng, who's doing a great work finding CPython crashes and memory leaks: https://github.com/python/cpython/issues?q=is%3Aissue%20author%3AYuanchengJiang
They've come up with a very clever idea for a new way of fuzzing, made a fine tool out of it, and are reaping great results.
Fuzzing can be a diminishing returns endeavor: you only have so many bugs to find. Their approach has shown itself to cover different areas and kinds of issues well, as shown by their track record.

![Screen shot of an abridged log of lafleur running, displaying the new messages for the timing fuzzing mode:
[TIMING] Running timed trial with JIT=False.
[TIMING] Running timed trial with JIT=True.
[~] Timing slowdown ratio (JIT/non-JIT) is 0.881.
The screen shot has a dark gray background and the text is a mix of white, green, red, purple and yellow, in a mess of coloring because the text editor identified this content as a Python script.
Full text of the image is:
--- Fuzzing Session #226 ---
[+] Calculating corpus scores for parent selection...
[+] Selected parent for BREADTH session: 523.py (Score: 248.51)
[...]
[TIMING] Running timed trial with JIT=False.
[TIMING] Running timed trial with JIT=True.
[NEW RELATIVE EDGE] '('EXECUTING', '_START_OF_HARNESS_->_SET_IP')' in harness 'f1'
[~] Timing slowdown ratio (JIT/non-JIT) is 0.881.](https://files.mastodon.social/media_attachments/files/115/367/765/525/405/481/small/d552701462e9c291.png)