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Canadian online critic of Trump sues U.S. Homeland Security for trying to unmask him
The ACLU says the summons seeks broad records on a Canadian critic, including his name, address and browsing history, after he posted anti-Trump comments online.
- The American Civil Liberties Union filed a lawsuit in the District Court of Northern California to block the Department of Homeland Security from forcing Google to disclose private information about a Canadian critic identified as John Doe.
- On Feb. 14, 2026, Secretary Markwayne Mullin's DHS issued an administrative summons to Google requesting "vast swaths of information" about the plaintiff's online activity over a five-month period between Sept. 1, 2025 and Feb. 4, 2026.
- The complaint alleges the summons unlawfully uses import and export codes to target the Canadian citizen, who has not entered the United States in more than a decade and conducts no business there.
- DHS previously used similar customs enforcement laws to unmask social media users, a practice the Inspector General once concluded was improper and led to withdrawn subpoenas during earlier administrations.
- Although Google has not released the data, the company has indicated it cannot "hold out forever," prompting the ACLU to seek urgent court intervention to protect the critic's identity and family.
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The Toronto Star+2 Reposted by 2 other sources
Canadian online critic of Trump sues U.S. Homeland Security for trying to unmask him
A Canadian citizen who posts anonymous online criticism of U.S. President Donald Trump has launched a lawsuit against the Department of Homeland Security, saying it is wrongfully trying to compel
·Toronto, Canada
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A Canadian citizen who posted anonymous criticisms of US President Donald Trump online filed a lawsuit against the U.S. Department of Homeland Security, claiming that the U.S. Department of Homeland Security is wrongly trying to force Google to reveal its identity.
·Montreal, Canada
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Total News Sources6
Leaning Left3Leaning Right1Center2Last UpdatedBias Distribution50% Left
Bias Distribution
- 50% of the sources lean Left
50% Left
L 50%
C 33%
R 17%
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