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Actor usage of AI is exploding. By analyzing artifacts left behind, Talos has created a detailed analysis of how we are seeing adversaries leverage the technology to include development, force multiplication, and vulnerability research. Based on the evidence Talos gathered, guardrails did not provide much protection, with most actors able to convince the models to comply despite the lack of sophisticated techniques or encoding. The pre-existing skill of the actor has a large impact on what they can accomplish with AI. Talos observed novice users able to create malicious capabilities, albeit with limited capabilities and success. Advanced users were able to build astonishing capabilities, pushing the models to create sophisticated and complex outputs. Artificial intelligence (AI) and associated language models are now ubiquitous and heavily used in both personal and professional contexts to streamline tasks and expand capabilities. With AI being used everywhere and by almost everyone, one of the biggest questions is how malicious actors are taking advantage. Fortunately, actors make mistakes and chatbots leave artifacts. Leveraging cloud-based AI models leaves behind a variety of artifacts, most notably a prompt log. These logs can take on a variety of shapes and sizes, but they are left on endpoints that are running various applications, such as Claude Code, CodeX, Cursor, or Gemini. Over the course of our research, we’ve collected a significant corpus of these files and can start discussing the ways we see bad actors leveraging these technologies. In conducting the research, three categories of activity emerged. One was using AI as a malicious software engineer, leveraging AI to write (in some cases) very sophisticated code with clear malicious intentions. Another was actors leveraging AI to scale criminal operations and campaigns. Finally, there were a lot of actors leveraging it for bug bounty or vulnerability research, rapidly accelerating their capabilities of discovery and disclosure. Each category demonstrates how threat actors are currently leveraging AI. Within each category is a wide disparity in sophistication based on the knowledge level of the actors involved. We tried to include use cases to cover the breadth of what we found. Takeaways and high-level findings With the recent disclosures from Hugging Face and OpenAI , it's clear the era of agentic attackers has effectively arrived. In that incident, the models ...
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