Cybersecurity is the True Frontier for Generative AI Success or Failure
Cybersecurity is a real-life test-bed for many machine learning problems at once, especially when considering modern strides in using Large Language Models (LLMs) to automate processes as ``agents.'' Cybersecurity workflows require orchestrating hundreds of standard and bespoke tools through various formats. The scale of cybersecurity data is enormous; for example, a single malware sample can be viewed as a sequence of billions of tokens. The cost of labeling any file by experts is enormous and labor-intensive, in part because an adversary (possibly a well-funded nation state actor) is attempting to subvert your detection methods. Even skilled experts may disagree on the correct label, cr...
| Authors | Edward Raff, Maor Ashkenazi, Sagar Samtani et al. |
|---|---|
| Primary category | cs.CR |
| Published | 27 June 2026 |
| Last updated at source | 27 June 2026 |
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