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

Nature of the Vulnerability (Not Really About AI)

• Many see this as “2010-era” web security failure: subdomain guessing, unauthenticated HTTP endpoint, high-privilege Box token exposed to the frontend, and no proper isolation.
• Commenters stress that the only AI-related aspect is that “AI features” drove centralization of huge document sets, massively increasing the blast radius.
• Several note that any SaaS integration could have made the same mistake; the AI branding is mostly hype layered over bad basics.

Compliance, Security Theater, and SOC 2

• SOC 2, HIPAA, and similar frameworks are widely described as checkbox exercises: forms, screenshots, and paid audits that often miss elementary flaws like this.
• Some argue they still provide marginal value (forcing some process and tightening a few weak spots) and are better than “trust me” alone.
• Others say auditors rarely dig deep; “pentests” are often just automated scans; certifications don’t meaningfully measure real security posture.

Disclosure, Triage, and Organizational Dysfunction

• Many are surprised it took weeks from initial report to confirmed fix for such a trivial but catastrophic bug.
• Explanations offered: overloaded security@ inboxes full of low-quality or AI-generated “reports,” opaque ownership of legacy code, rigid roadmaps, and risk-accepting executives prioritizing features over fixes.
• Debate over “responsible disclosure”: some advocate harsher deadlines or even forcing services offline; others warn that threatening publication can cross into illegality and harm critical services (e.g., medical).

Accountability, Incentives, and Bug Bounties

• Strong sentiment that executives should face real consequences (including potential criminal liability) when negligence exposes sensitive client data.
• Multiple commenters argue the researcher deserved substantial compensation (5–6 figures), noting they could have sold the vuln to ransomware groups instead.
• Concern that weak or non-existent bounties push talented finders toward gray/black markets.

Legal Profession, SaaS, and AI Adoption

• Lawyers’ ethical confidentiality duties are highlighted as poorly understood in practice, especially with cloud and AI vendors.
• Tension noted between “move fast and duct-tape APIs” startup culture and “if this leaks we ruin lives” legal/medical confidentiality.
• Some question why firms trust conventional SaaS but balk at AI SaaS, given both often lack serious security diligence.