Defending Against Hidden Risks of AI Tools in the Workplace

Shawn Hayward, a ThreatLocker solutions engineer based in Toronto, argues that generative AI has collapsed the skill needed to write malware: a request reframed as a legitimate professional task gets a chatbot to produce a working exploit or reverse-shell in seconds, and because each output is unique code, it can slip past signature-based defenses as an undetected zero-day, which he demonstrates by comparing a known reverse-shell snippet (blocked by Windows Defender) against a functionally identical AI-generated one (not blocked). He names a third risk category beyond bad code and open ports: AI tools that misbehave by mistake, since they cannot determine a user's intent, deleting files or sending data to the wrong recipient while running with the user's own trusted permissions. He shows prompt injection working both ways, hidden text making an AI bio generator surface a private joke as fact, and malicious emails instructing AI scanners to mark them benign, and debunks the idea that removing local admin rights alone stops ransomware, citing an unpatched Windows privilege-escalation zero-day. His prescription, shown with ThreatLocker's own product, is default-deny application allowlisting plus ring-fencing, restricting what approved applications and AI tools can do laterally, rather than relying on detection alone.