tl;dv Security Breach: 181,000+ Meeting Records Exposed via Firestore Misconfiguration

Executive Summary

A critical security vulnerability in the AI meeting recording platform tl;dv exposed metadata for 181,874 meeting records belonging to 84,312 unique users across 35,003 email domains. Due to a lack of tenant isolation in its Firestore database, any authenticated user could query the meetings collection to obtain conference IDs, creator emails, and recording statuses. This flaw allowed attackers to join live, active meetings in real-time, including sessions from government agencies in 23 countries and major universities.

The Technical Root Cause: Firestore Tenant Isolation Failure

The vulnerability stemmed from a failure to implement proper security rules for the meetings collection in tl;dv's Firestore database (projects/lmi-store/databases/(default)). While other collections—such as users, chats, and transcripts—were correctly protected with 403 Forbidden responses, the meetings collection remained wide open.

The Attack Vector

  1. Authentication: An attacker signs up for a tl;dv account, receiving a JWT which is exchanged for a Firebase token via gw.tldv.io/v1/users/firebase/token.
  2. Enumeration: Using this token, the attacker queries the meetings collection.
  3. Data Extraction: The database returns records containing the creator's email, provider, timestamps, and the conference ID (e.g., Google Meet or Teams room IDs).
  4. Live Intrusion: By filtering for meetings with status: recording, an attacker can identify active calls and use the exposed conference IDs to join the meetings uninvited.

Scope of Exposure

Meeting Metadata and Live Access

At the time of the research, approximately 1,000 meetings were in recording status at any given moment, providing a constant stream of live calls for unauthorized entry. The data leak spanned a massive variety of high-sensitivity domains:

  • Government: Entities from 23 countries, including the US, Ukraine, Malaysia, and Israel (all .gov domains).
  • Academic: Institutions such as Berkeley and the University of Tokyo (.edu and .ac domains).
  • Corporate: Large organizations including HubSpot, Confluent, and Mitsui-Soko.

Public Content Leak

Beyond metadata, the researcher scraped 27,334 meeting IDs to check for public visibility. Over 1,000 meetings were public, exposing 715 invitee emails across 228 domains, including sessions from Ukraine's Ministry of Digital Transformation and the Brazilian government.

Internal Employee Leak

An internal employee prediction game (worldcup.tldv.io) lacked authentication on its Player entity API (GET /api/entities/Player). This exposed the full names and corporate emails of 19 @tldv.io employees, including the co-founder and CEO.

Disclosure Timeline and Corporate Response

Despite the severity of the leak, the vulnerability remained unpatched for six months. The researcher reported the issue on January 28, 2026, but the company failed to remediate the flaw until July 2026.

Date Event
Jan 28, 2026 Vulnerability discovered and reported to Raphael Allstadt and the CTO.
Jan 29 - Feb 19, 2026 Multiple follow-ups; the company provided vague reassurances but no fix.
Mar - July 2026 Repeated follow-ups ignored; vulnerability remained active.
July 2026 Vulnerability eventually patched following public disclosure.

Community Insights and Analysis

Industry observers and security researchers on Hacker News highlighted several systemic issues surrounding this breach:

The "Firebase Footgun"

Multiple commentators noted that Firebase's architecture, which relies on client-side security rules, often leads to "skill issues" where developers forget to secure a single collection, leading to total tenant exposure.

SOC2 and Compliance Theater

Critics pointed out the irony of tl;dv being SOC2 and GDPR compliant while maintaining a critical data leak for six months.

"Interesting, they are SOC2 compliant, proving again that SOC2 is meaningless/useless."

Risks of AI Note-Takers

The breach underscored the inherent risk of funneling sensitive corporate and government audio into third-party AI clouds. Discussions centered on the need for local-first AI transcription and diarization to prevent centralized data honeypots.

Potential for Social Engineering

Security experts warned that leaked audio and meeting metadata provide a goldmine for deepfake voice phishing. By obtaining real audio clips of employees, attackers can more easily synthesize voices for high-fidelity social engineering attacks.

Sources

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