#llm-backdoors

#llm-backdoors

"I work in legal innovation. To be successful, you need to understand both the law and the technology behind it."

The first is Neural Execs, a known prompt injection attack that uses 'gibberish' inputs to trick the AI into executing arbitrary, attacker-defined tasks. These inputs act as universal triggers that do not need to be remade for different payloads.

On a clear night I set up my telescope in the yard and let the mount hum along while the camera gathers light from something distant and patient. The workflow is a ritual. Focus by eye until the airy disk tightens. Shoot test frames and watch the histogram. Capture darks, flats, and bias frames so the quirks of the sensor can be cleaned away later. That discipline is not fussy.

Sleeper agent-style backdoors in AI large language models pose a straight-out-of-sci-fi security threat. The threat sees an attacker embed a hidden backdoor into the model's weights - the importance assigned to the relationship between pieces of information - during its training. Attackers can activate the backdoor using a predefined phrase. Once the model receives the trigger phrase, it performs a malicious activity: And we've all seen enough movies to know that this probably means a homicidal AI and the end of civilization as we know it.