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IDScan confirms breach after 153 million driver’s licenses leak on dark web

Help Net Securityby Sinisa Markovic ()2 min read1 · 1 read
AI summary · glm-5.3-flashSummaries by Vani AI

IDScan.net confirmed hackers accessed cloud-stored customer data after a dark web listing exposed 153 million US and Canadian driver's license scans.

IDScan.net, a Louisiana-based identity verification provider serving car rental companies, retailers, and cannabis dispensaries, confirmed unauthorized access to customer data stored on its cloud platform around September 1, 2026. A dark web marketplace called Nexus advertised more than 153 million US and Canadian driver's license scans, plus 10 million ID cards, 3 million travel documents, and 579,000 medical cards. Krebs traced the leak to IDScan.net, prompting an FBI New Orleans investigation; the company is notifying affected individuals and offering free credit monitoring while cooperating with federal law enforcement.

Key facts
  • Nexus dark web listing offered 153M+ US/Canada license scans plus 10M ID cards and 3M travel documents
  • FBI New Orleans opened a formal investigation after Krebs verified the leak's authenticity
  • IDScan is notifying affected individuals and offering free credit monitoring and identity protection
  • Nexus service disappeared from the dark web shortly after the story published
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From the original article

2 min read at helpnetsecurity.com

Days after reports linked IDScan to a dark web database holding more than 153 million driver’s license scans, the identity verification company has confirmed hackers accessed customer data stored on its cloud platform. The Louisiana-based firm, which processes ID checks for car rental companies, retailers and cannabis dispensaries, posted a notice on its website September 4 acknowledging the incident.

Help Net Security

By Sinisa Markovic · helpnetsecurity.com

Read the full article at Help Net Security

A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.