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AI made the exploit much easier
Interestingly, Brizinov relied on AI to do a lot of routine tasks in the exploit. For instance, a small platform to view and analyze file directory changes in a git repository was built using AI to visualize what objects are created, changed, and deleted.
“Obviously this was an overkill for this project, but with vibe-coding, it took me less than 5 minutes, so why not?” Brizinov said. Additionally, AI was used to find public GitHub accounts associated with the list of companies Briznov chose to target.
Leaked secrets often came from binary files like .pyc or .pdb, accidentally committed during development. These compiler-generated fields can expose sensitive data if not properly excluded.
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