Security teams are being urged to adopt AI copilots for threat modeling, phishing simulations, and SOC workflows. Yet many of the most widely deployed, enterprise-approved AI systems struggle to support realistic defensive scenarios once prompts resemble real-world attack behavior.
This is not because such activity is inherently malicious, but because mainstream AI safety models are designed to prevent broad misuse at scale, rather than distinguish authorized security work from abuse.
Meanwhile, attackers are unconstrained by procurement rules, compliance obligations, or centralized safety enforcement, whether they rely on open-source models, fine-tuned tools, or simply no AI at all.
