How an AI Agent Hacked McKinsey’s AI Platform
Understand how an AI agent hacked McKinsey’s internal AI platform ‘Lilli’, and the lessons organizations should take from this exercise.
Read moreComprehensive, expert-led penetration testing across AI and LLMs.
In-depth testing and actionable insights to help you uncover, prioritize, and eliminate AI and LLM risks faster.
Our experts use AI-specific attack techniques to identify vulnerabilities across the model and prompt layers, RAG pipelines, agent workflows, and supporting APIs giving you a detailed view of your exposure.
Performed by our certified penetration testers, we examine the critical components and behaviors of your AI and LLM applications in greater depth.
Access a single platform for findings mapped to the OWASP Top 10 for LLMs, with clear business impact to support effective prioritization without slowing your development cycle.
Generate on-demand reports to demonstrate AI security due diligence and support AI and LLM compliance efforts.
We test the model layer, prompt layer, RAG pipelines, agent workflows, and supporting APIs. Our focus is on how your AI system behaves in production and how it can be manipulated through real-world attack paths. We do not test the underlying model provider’s infrastructure or review training data and model weights.
Yes. Testing before launch helps identify vulnerabilities earlier, when they are typically faster and less costly to fix. It also gives your team more confidence before go-live and helps demonstrate security due diligence from day one.
Not fully. A web application pen test is important for application security, but it does not cover AI-specific risks such as prompt injection, RAG poisoning, system prompt leakage, or agent misuse. AI and LLM penetration testing is designed to assess those attack paths and complements a standard web app assessment.
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Understand how an AI agent hacked McKinsey’s internal AI platform ‘Lilli’, and the lessons organizations should take from this exercise.
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