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Cyber threat actors: AI-assisted intrusion research
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Cyber threat actors: AI-assisted intrusion research

This case study was originally published in OpenAI’s February 2025⁠(opens in a new window) report.

Actor

We banned accounts demonstrating activity potentially associated with publicly reported Democratic People’s Republic of Korea (DPRK)-affiliated threat actors. Some of these accounts engaged in activity involving TTPs consistent with a threat group known as VELVET CHOLLIMA (AKA Kimsuky, Emerald Sleet)⁠(opens in a new window), while other accounts were potentially related to an actor that was assessed by a credible source to be linked to STARDUST CHOLLIMA (AKA APT38, Sapphire Sleet)⁠(opens in a new window). We detected these accounts following a tip from a trusted industry partner.

Behaviour

The banned accounts primarily used our tools to pursue information likely related to cyber intrusion tools or operations. They also demonstrated interest in cryptocurrency-related topics, likely in relation to financially motivated activities. This blend of financial and cyber-related activity is typical for DPRK-associated threat groups.

Completions

The actors used our models for coding assistance and debugging, along with researching security-related open-source code. This included debugging and development assistance for publicly available tools and code that could be used for Remote Desktop Protocol (RDP) brute force attacks, as well as assistance on the use of open-source Remote Administration Tools (RAT).

While debugging auto-start extensibility point (ASEP) locations and techniques for MacOS, the actor revealed staging URLs for binaries (compiled executable files) that appeared to be unknown to security vendors at the time. We submitted the staging URLs to an online scanning service to facilitate sharing with the security community, and the binaries are now reliably detected by a number of vendors, providing protection for potential victims.

Original source

This story was published by OpenAI News. SyncAI.news shows a preview; the complete article is on the publisher's site.

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