
The episode discusses the shift in AI security focus from the model to the harness surrounding it.
In this episode of BHIS Presents: AI Security Ops, the team tackles a foundational question in modern AI security: Is the real risk in the model… or in the harness around it? For years, most conversations have focused on model behavior — prompt injection, refusals, alignment, and safety controls. But as AI systems evolve into full agents with tools, memory, and execution capabilities, the focus is shifting. Increasingly, the real security boundary isn’t the model itself — it’s the harness: the code, integrations, permissions, and workflows that give AI systems real-world power. And that shift has massive implications for how we think about AI risk. We dig into: • What “model vs. harness” actually means in practical terms • Why defenders often blame the model for issues caused by the harness • How agent architectures expand the attack surface beyond prompts • The role of tools, memory, and execution in modern AI systems • Why prompt injection is often a harness design failure • How real-world AI exploits increasingly target integrations, not models • The limits of model-level safety and refusal behavior • Why harness design is becoming the new security perimeter • How AI agents…
Host: Black Hills Information Security
Organizations: AI Security Ops
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