Real stories. Real consequences. Provable prevention.

What Happened

In March 2022, a deepfake video depicting Ukrainian President Volodymyr Zelensky ordering Ukrainian troops to surrender circulated widely on social media and was briefly broadcast on a hacked Ukrainian news channel. The Ukrainian government had pre-emptively warned about deepfakes weeks earlier, and Zelensky himself quickly recorded a rebuttal — but the video still caused confusion and was used as propaganda.

The Provenance Gap

There was no technical mechanism to prove the rebuttal was authentic either. Both the fake and the real video were "just video files." Authenticity was established by context and trust in Zelensky himself — not by any verifiable proof in the footage.

With TrustEye

If official communications were captured through a TrustEye-enabled pipeline, the rebuttal would carry a stronger verification trail showing when it was recorded, which source produced it, and why it should be trusted immediately.

What Happened

During the 2022 Depp v. Heard defamation trial, both legal teams accused each other of submitting manipulated photo and audio evidence. Digital forensic experts found that injury photos had been processed through editing software, with metadata showing they were screen captures rather than original camera files. Meanwhile, audio recordings had metadata showing creation and modification dates years apart.

The Provenance Gap

Neither party could conclusively prove their evidence was unmodified since capture. The photos and recordings existed as ordinary files — copyable, editable, and with mutable metadata. Authentication relied entirely on forensic expert testimony, which the opposing side could always counter.

With TrustEye

Photos and video captured through a TrustEye-enabled camera app would be sealed at the moment of capture — hashed, device-signed, and time-anchored. Any subsequent editing would break the hash chain. The court could verify authenticity in seconds rather than debating forensic experts for days.

What Happened

In the 2025 Benavides v. Tesla case (the first US verdict holding Tesla liable for an Autopilot death), dashcam footage and vehicle telemetry data were central evidence. The jury placed 67% of fault on the driver and 33% on Tesla, awarding over $240M. But the evidence came from Tesla's own systems — dashcam footage stored in Tesla's proprietary format, telemetry logged by Tesla's software.

The Provenance Gap

When the entity being sued is also the entity that controls the recording, storage, and format of the evidence, there is an inherent trust problem. The dashcam footage had no independent proof of integrity. It was Tesla's word — backed by Tesla's data — about what Tesla's system did.

With TrustEye

An independent provenance layer on the vehicle's cameras would seal footage at capture time, signed by the vehicle's hardware security module, anchored to a public blockchain. Neither the manufacturer nor the owner could retroactively alter the record. Liability disputes would be resolved by mathematics, not by competing corporate narratives.

What Happened

In January 2024, a recording went viral appearing to show a Baltimore high school principal making racist and antisemitic remarks. The principal was placed on leave pending investigation. In April, police confirmed the recording was "not authentic" — it had been created using AI voice cloning by the school's athletic director, reportedly as retaliation.

The Provenance Gap

There was no way for the principal to instantly prove the recording was fake. The burden of proof fell on the victim. It took months of forensic investigation to establish what technology could have determined in seconds: this recording did not come from a legitimate capture device at the claimed time.

With TrustEye

Authentic recordings made through a TrustEye-enabled device carry a stronger provenance record. When a recording surfaces without that trail, the absence itself becomes a signal. And when someone challenges a verified recording, the proof is faster to review.

What Happened

In a 2024 California case, five people were arrested for staging an auto collision to file a fraudulent insurance claim. They were caught only because a home surveillance camera near the intersection captured one defendant exiting the vehicle in the middle of the road while another deliberately crashed into it. Without that accidental third-party footage, the staged collision would have been indistinguishable from a real accident.

The Provenance Gap

The insurance company had no way to verify whether the claimants' own footage — had they submitted any — was authentic. The fraud was only detected because of lucky external surveillance. In most cases, there is no neighbor with a camera.

With TrustEye

If claimants were required to submit incident documentation through a TrustEye-enabled app, each recording would be device-bound and time-anchored. Submitting pre-recorded or fabricated footage would fail verification. The technology replaces luck with proof.

What Happened

Missing and "malfunctioning" bodycam footage is a recurring pattern in police misconduct cases. When critical footage mysteriously disappears, defense attorneys file motions to suppress officer testimony and dismiss charges. In some cases, courts have ruled that the destruction of evidence warrants case dismissal.

The Provenance Gap

Bodycam footage is stored on department-controlled servers with no independent chain of custody. There is no durable verification record proving what was recorded, when it was recorded, or that nothing was deleted. The absence of footage is suspicious but unprovable.

With TrustEye

Every second of bodycam footage would be sealed at capture time with a hash chain. If segments are deleted, the chain breaks at the exact deletion point — pinpointing precisely which seconds were removed. The hash chain and blockchain anchor exist independently of the department's storage.