Slide 11 of 28
Part 2 — How It WorksSlide 11
Slide 11 · Direct — Real Example
The McKinsey "Lilli" red team exercise
A controlled test that demonstrated full platform compromise through direct agent manipulation — in under two hours.
Real Incident · 2025
McKinsey internal AI platform "Lilli" — red team exercise

McKinsey's internal AI assistant, Lilli, was deployed to help consultants research, synthesize documents, and access internal knowledge. In a controlled red team exercise conducted in 2025, security researchers tested what would happen if an attacker could interact with the agent directly.

Using direct manipulation techniques — feeding the agent crafted instructions that reframed its role and expanded its perceived permissions — the red team achieved broad system access across multiple connected services in under two hours. The agent, operating within its normal interface, followed the redirected goal without triggering automated alerts.

The exercise demonstrated that even an enterprise-grade internal AI platform, designed with security in mind, could be steered away from its intended purpose by an actor with nothing more than access to the chat interface.

Lesson: Direct access to an agent's interface is sufficient to attempt goal hijack. Role reframing and authority claims — without any technical exploit — can redirect a capable agent toward full platform compromise. The speed of the attack (under two hours) underscores how fast agentic threats escalate once a foothold is established.
What made this possible

Lilli had broad access to internal knowledge and connected services — by design, because that's what made it useful. The same connectivity that enabled its value enabled the blast radius of the hijack. Reducing access would have reduced usefulness. This is the core tension every agent deployment must navigate.

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