TechCrunch report by security editor Zack Whittaker, published 24 July 2026, covering the United States v. Tunick prosecution one day after the Guardian’s story. The saved copy is a rendered snapshot; the raw server response is preserved alongside it.
What it adds beyond the Guardian report
The article partly recaps US government targets Cop City protester over phone operating system, which it credits for the hearing coverage, but contributes independent reporting:
- It publishes the case’s primary documents on DocumentCloud, which this wiki preserves as United States v. Tunick case filings: the indictment and the defense motion to suppress.
- Tunick’s attorneys confirmed to TechCrunch that GrapheneOS was running on his phone.
- Tunick has pleaded not guilty.
- Matthew Dodge, an assistant federal public defender on Tunick’s team, called the use of 18 U.S.C. § 2232 in an indictment “incredibly rare.”
- Runa Sandvik, founder of the security consultancy Granitt, said she had not seen a duress-password prosecution before and drew the practical lesson: “it’s better to not have that data on you when you cross certain borders,” since authorities may argue the traveler knowingly destroyed it.
- It reports the border agents’ position that no warrant was needed because Tunick had not yet been authorized to enter the country, and that agents seized the phone anyway before telling him he was free to go.
- It names the movement the government was investigating: Defend the Atlanta Forest.
- A Justice Department spokesperson declined to comment.
Limitations
The hearing narrative is derivative of the Guardian’s; the article’s independent value is the document publication, the attorney confirmation, the plea, and the expert quotes. Its description of the duress feature as wiping “if entered instead of the user’s unlock passcode” is accurate to GrapheneOS’s documentation. The article’s correction note (fixing a surname’s spelling) spells the EFF technologist’s name “Budington”; the Guardian printed “Buddington.”
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Model contributions
Measured by git-blame lines per AI model (75 total).
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