German newspaper Handelsblatt: a Tesla whistleblower leaked 100GB of customer FSD complaint data from 2015 to 2022, including 2,400+ self-acceleration issues
and Vice Versa Fred Lambert / Electrek : Tesla Files: Insider dropped 100 Gb of data on German media outlet Tweets: @marxistrealism : Tesla whistle-blower revealing that the company hides accident reports from their autopilot, endangering the drivers and every other unwilling participant sharing the roads with this untested product - the same day Musk's other company is approved to experiment on your brain! [image] Kara Swisher / @karaswisher : Not uncommon for car companies, I assume, but this company did not suffer from such leaks before: Huge Tesla leak reveals thousands of safety concerns, privacy problems | Ars Technica https://arstechnica.com/... Paris Marx / @parismarx : The Tesla Files contain more than 2,400 self-acceleration complaints, 1,500 braking function problems, and 1,000 crashes. The leaked files show Tesla instructs employees to only communicate verbally about complaints so there's no written documentation. https://jalopnik.com/... Ned Resnikoff / @resnikoff : Running Twitter into the ground is small potatoes compared to the fraud and recklessness at Tesla, which in a more just world would have already landed Elon in prison https://www.theverge.com/... Andrew Orlowski / @andreworlowski : “I really would consider autonomous driving to be basically a solved problem. I think we're basically less than two years away from complete autonomy.” Musk in 2016. https://twitter.com/... Gary Marcus / @garymarcus : major Tesla FSD whistleblower scoop - “2,400 self-acceleration issues and 1,500 braking problems, including 139 reports of “unintentional emergency braking” and 383 reports of “phantom stops” from false collision warnings.” https://www.theverge.com/... Ben K / @benshooter : Hm, you don't say? 2400 incidents of cars accelerating on their own? 1500 phantom braking incidents where the car slams on the brakes in the middle of a freeway? Oh gosh oh golly if only people had been warning about this for years... https://twitter.com/...
Context & Ripple Effects
The reported leak turns a long-running debate over verification of automated-driving safety claims into a dataset of internal customer complaints. Earlier coverage had already highlighted how limited public data made such claims difficult to independently assess; the files add alleged evidence about both complaint handling and the types of incidents reported.
It also sits alongside concerns about Tesla's control of vehicle data after crashes, including its selective release of logs to media. The later account of a Tesla whistleblower whose material drew regulators' attention suggests the disclosure was not simply a reputational episode but part of a widening accountability trail.
First-order effects
- Tesla faces immediate scrutiny over the leak's alleged complaint records, instructions to avoid written communications, and exposure of customer information. Customers whose data may be included face a privacy risk alongside questions about how their safety reports were handled.
- The reported volume and categories of FSD-related complaints give journalists, safety advocates, and regulators a more concrete basis to test Tesla's public safety narrative, rather than relying only on company-selected data.
Second-order effects
- Tesla may have to devote more resources to preserving, producing, and explaining complaint and incident records. That pressure is amplified by the later NHTSA investigation into FSD in low-visibility crashes, which shows regulators can turn reported operating failures into formal review.
- Other automated-driving developers face a clearer incentive to strengthen complaint documentation and privacy controls: opaque internal reporting can become both a safety-governance and data-protection liability when disclosures occur.
Third-order effects
- If regulators and the public increasingly treat internal complaint logs as essential safety evidence, automated-driving oversight could shift from company performance claims toward auditable incident reporting and data-retention practices.
- The durable issue is governance of safety-critical AI: credibility will depend not only on system behavior but on whether affected users, investigators, and regulators can access reliable evidence when failures are alleged.
The trend: Automated-driving systems are moving toward a public-safety governance model in which incident data, disclosure practices, and privacy safeguards matter as much as technical capability.