The sql injection analogy is actually pretty apt. we had parameterized queries as a systematic defense -- the question is whats the equivalent for prompt injection. right now the answer is layered: input validation, output filtering, least-privilege scoping, and critically actually testing your prompts against known attack patterns before deployment. you can run your system prompt through aiunbreakable.com/scanner for free -- it will flag which injection categories you're vulnerable to....

The 30% that didnt tag themselves is the scarier number imo. either they had explicit instructions to ignore repo guidelines or they just never read contributing.md at all. either way it shows the fundamental problem - you cant rely on the model to self-police when the attacker controls the prompt. the real defense has to be at the permission/execution layer not the reasoning layer

The 30% that didn't tag themselves is the scarier number imo. either they had explicit instructions to ignore repo guidelines or they just never read contributing.md at all. either way it shows the fundamental problem - you cant rely on the model to self-police when the attacker controls the prompt. the real defense has to be at the permission/execution layer not the reasoning layer