OpenAI Daybreak is enabling a dramatic acceleration in SentinelOne’s deep malware analysis, shrinking what used to take weeks into a matter of hours. According to Gregor Stewart, SentinelOne’s Chief AI Officer, the company now achieves “human-level reverse-engineering output in roughly eight hours,” a change that lets researchers inspect more samples, draw connections across incidents, and concentrate human expertise where it matters most.
Malware reverse engineering of complex samples has traditionally been a slow, highly manual process performed by senior security researchers. SentinelOne says a top analyst might previously spend four to six weeks fully unpacking a sophisticated sample. By automating parts of that workflow with OpenAI Daybreak, the firm reports a dramatic reduction in turnaround time. The company frames this not as replacing experts but as offloading time-consuming tasks so researchers can pursue higher-value analysis.
The immediate operational effect is greater research capacity. Faster, repeatable outputs let the same team evaluate far more software within the existing staffing envelope. SentinelOne highlights that producing quicker reverse-engineering results allows analysts to compare a larger set of findings and search for shared components or reused code across samples—insights that were harder to obtain when deep investigation was reserved for only the most consequential threats.
Stewart emphasizes that automation changes the shape of work without removing human responsibility. “The only thing that can’t be automated is accountability,” he said, noting that architectural shifts or decisions that fundamentally change software still require human review. Routine fixes and repetitive tasks, by contrast, are the sorts of activities Daybreak can expedite, freeing experienced researchers to focus on interpretation, strategy and oversight.
A key benefit SentinelOne highlights is the improved ability to map relationships across the malware landscape. Historically, deep investigations produced a limited pool of analyzed samples, constraining the opportunity to detect patterns. With quicker reverse engineering, analysts can bring a broader sample set to bear, increasing the chance of spotting code reuse, shared components, or other indicators that link seemingly unrelated attacks. Stewart says faster analysis “enables us to map a much larger part of the malware landscape and keep pace with how it changes. That gives our researchers a clearer picture of how threats are connected and how those relationships evolve.” Such leads can directly aid customer investigations or inform defensive measures across environments.
SentinelOne also reports that making OpenAI’s cyber capabilities available internally has broadened access to expert-level tooling. Stewart observed that “almost everyone now has access to the kind of expertise that was in very short supply until maybe even a few months ago.” By distributing investigative capability beyond a small cadre of specialists, the company expects faster response times and a more even distribution of investigative workload across teams.
The firm is exploring ways to embed this capability earlier in development workflows as well. Stewart said he hopes to bring OpenAI-powered cyber capabilities into code creation so developers can address security issues during build time, shifting defensive advantages toward engineers working day-to-day on products and services. The goal is to make security more proactive and integrated, rather than reactive and concentrated in a few teams.
SentinelOne positions the shift as more than a time-savings improvement: faster reverse engineering can expand the scope of investigations, reveal patterns obscured by smaller sample sizes, and give defenders a more proactive view of how threats evolve. At the same time, the company maintains that human oversight remains central for decisions that materially affect software architecture or longer-term defensive posture.
SentinelOne’s experience with OpenAI Daybreak illustrates how advanced AI tools are being applied to accelerate specialist cybersecurity tasks while preserving human accountability. By cutting deep analysis from weeks to hours, the company says it can both scale research efforts and sharpen its ability to see connections across the evolving threat landscape. As the tool becomes more widely embedded, SentinelOne expects to broaden who can perform serious security work and to move security considerations earlier into the development lifecycle.
In short, SentinelOne reports that OpenAI Daybreak multiplies researcher capacity, surfaces links across samples that were previously difficult to detect, and enables a more distributed approach to security research—while keeping final decisions and architectural judgments in human hands.
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