Reverse engineering a $1B Legal AI tool exposed 100k+ confidential files

4.5

“Reverse engineering a $1B Legal AI tool exposed 100k+ confidential files” is an in-depth security case study and technical analysis of a critical vulnerability in a billion‑dollar legal AI and case‑management platform. By reverse engineering the platform’s public APIs and AI integration, the researcher uncovered misconfigured access controls that exposed over 100,000 confidential legal documents, including sensitive client information, internal case files, and privileged communications. This report walks readers step‑by‑step through the discovery process: mapping the API surface, analyzing authentication flows, identifying insecure endpoints, and demonstrating how automated enumeration could silently harvest protected data at scale. It also explains the broader implications for AI‑powered SaaS products in regulated industries, highlighting how rapid AI integrations can outpace mature security and privacy practices. Aimed at security engineers, AI builders, legal tech teams, and technical leaders, the article distills actionable lessons on secure API design, tenant isolation, least‑privilege access, and monitoring. It provides concrete remediation guidance and a framework for assessing similar risks in other AI tools that process sensitive or regulated data. If you build, buy, or rely on AI for legal or enterprise workflows, this case study offers a sobering and practical blueprint for preventing comparable data exposure incidents.