AI cybersecurity is not proof of work
6 hours ago
- #Cybersecurity
- #Bug Detection
- #LLM Limitations
- Bugs are not like proof of work: resources alone don't guarantee finding bugs because code and LLM sampling saturate.
- Finding bugs depends on the model's intelligence level, not just the number of executions; weak models may hallucinate but not truly understand.
- Stronger models hallucinate less and may not claim bugs exist if they lack true understanding, unlike both weak models and highly capable ones.
- Cybersecurity will prioritize better models and faster access over raw computational power, as demonstrated by the OpenBSD SACK bug example.
- Testing shows weak models pattern-match bug classes without grasping exploit creation, while stronger models avoid false positives but may miss real issues.