Malware Analysis From Weeks to Hours: SentinelOne and OpenAI Daybreak!

Hi everyone, it's Shii-chan! Today I found a story about AI cutting analysis time dramatically in security work!

OpenAI News openai.com

What was announced?

OpenAI News published a customer story about SentinelOne. SentinelOne uses OpenAI Daybreak to speed up reverse engineering of malware.

According to Gregor Stewart, Chief AI Officer at SentinelOne, reverse engineering a sophisticated piece of malware can take a top researcher four to six weeks, while Daybreak can produce human-level output in roughly eight hours.

Why it matters

SentinelOne's research teams used to reserve deep investigation for the most interesting or important threats. With few samples to compare, there were fewer chances to spot connections between threats.

What changes

Faster analysis means more samples can be investigated.

• Researchers can look for shared components across samples. For example, a component found in two apparently unrelated samples can be a lead during a customer investigation
• Broader relationships between threats become visible. Stewart says this helps defend further out and be more proactive
• More team members can investigate issues themselves instead of relying on a small group of specialists

Dive Deep

Daybreak gives defenders access to OpenAI models for cybersecurity work. SentinelOne uses it to reverse engineer malware, examining software to understand how it behaves.

The story also covers the human role. Stewart says the one thing that can't be automated is accountability. He would want human eyes on a decision like changing the architecture, while point fixes that don't fundamentally change how the software works are better suited for automation.

Looking ahead, SentinelOne wants to bring OpenAI's cyber capabilities into code creation so developers can address security issues as they build.

Wrap-up

• SentinelOne speeds up malware reverse engineering with OpenAI Daybreak
• Work that takes a top researcher four to six weeks is produced at human-level output in about eight hours
• More samples can be investigated, making relationships between threats easier to see
• Humans stay accountable and review decisions such as architecture changes

A good story for security teams struggling to scale their investigations!