ChatGPT solved a multi-part cybersecurity task in about eight hours [2] that typically takes weeks to complete [1].
The result suggests a significant leap in the ability of large language models to handle complex, sequential technical problems. This efficiency could fundamentally alter how security firms approach vulnerability research and threat mitigation.
Gabriel Bernadett-Shapiro, a distinguished AI research scientist at SentinelOne, said the findings were based on work conducted in a SentinelOne research environment [1], [2]. The experiment aimed to demonstrate that AI models are becoming more proficient at solving multi-part cybersecurity problems [1], [2].
While the specific nature of the cybersecurity task was not detailed, the time reduction is substantial. The process usually requires weeks of manual effort [1], but the AI reduced that window to roughly eight hours [2].
This development highlights the evolving role of generative AI in specialized technical fields. By automating the tedious portions of cybersecurity analysis, researchers can potentially focus on higher-level strategy and oversight, rather than the manual execution of repetitive tasks.
Bernadett-Shapiro said the results indicate that AI is improving at navigating the intricacies of security workflows [1], [2].
“ChatGPT solved a multi-part cybersecurity task in about eight hours that typically takes weeks to complete.”
The ability of an AI to compress weeks of specialized labor into a single workday indicates that LLMs are moving beyond simple text generation into complex problem-solving. In a cybersecurity context, this acceleration could be a double-edged sword: it allows defenders to patch vulnerabilities faster, but it may also enable attackers to develop exploits with unprecedented speed.
