OpenAI says Daybreak reduced one SentinelOne malware reverse-engineering workflow from four to six weeks to about eight hours, with human oversight.
SentinelOne is using OpenAI Daybreak to accelerate malware reverse engineering, according to OpenAI. In the use case described, work that previously took a top security researcher four to six weeks can be completed in approximately eight hours. This is a result reported by the companies for a specific deployment, not an independent benchmark.
Daybreak gives defenders access to OpenAI models for cybersecurity tasks. SentinelOne characterizes the system’s output in this use case as being at a human level. However, the published account does not specify the evaluation method, describe the malware sample set or quantify how often researchers had to correct the system’s findings.
OpenAI says the time savings allow SentinelOne researchers to conduct deep analysis on more malware samples instead of reserving that work for a small number of especially important threats. The additional capacity also lets them compare findings across a broader collection and search for shared components in malware that initially appears unrelated.
Gregor Stewart, SentinelOne’s chief AI officer, says this wider view can reveal connections between threats and show how those relationships change. Such findings may provide leads for customer investigations and support more proactive defenses. OpenAI also says its cyber capabilities enable a broader group of SentinelOne employees to undertake investigations without relying exclusively on a small pool of specialists.
SentinelOne plans to extend these capabilities into software development so developers can address security issues while writing code. The proposed automation remains bounded by the consequences of a decision: lower-level fixes may be automated, while choices that fundamentally change software architecture should continue to receive human review. OpenAI emphasizes that SentinelOne’s team remains accountable for outcomes.
The broader significance is not merely a faster investigation, but the possibility of examining more samples and testing more links between threats. The reported timeline should not be assumed to apply to every malware family or security team because the account does not break down task complexity or measurement conditions. Human verification therefore remains especially important when findings affect product architecture or customer protection.
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Originally published by AI Feed: SentinelOne Uses Daybreak to Cut Malware Analysis Time.
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