05-19-2021, 12:11 PM
The post office’s law enforcement arm has faced intense congressional scrutiny in recent weeks over its Internet Covert Operations Program (iCOP), which tracks social media posts of Americans and shares that information with other law enforcement agencies. Yet the program is much broader in scope than previously known and includes analysts who assume fake identities online, use sophisticated intelligence tools and employ facial recognition software, according to interviews and documents.
Among the tools used by the analysts is Clearview AI, a facial recognition software that scrapes images off public websites, a practice that has raised the ire of privacy advocates. The U.S. Postal Inspection Service uses Clearview’s facial recognition database of over 3 billion images from arrest photos collected from across social media “to help identify unknown targets in an investigation or locate additional social media accounts for known individuals,”
Other tools employed by the Inspection Service include Zignal Labs’ software, which it uses to run keyword searches on social media event pages to identify potential threats from upcoming scheduled protests, according to Inspection Service documents. It also uses Nfusion, another software program, to create and maintain anonymous, untraceable email and social media accounts.
The Inspection Service’s expansive surveillance program has raised concerns among lawmakers and privacy and civil liberties experts, and the use of sophisticated software tools raises even more questions.
“The U.S. Postal Inspection Service appears to be putting significant resources into covert monitoring of social media and the creation and use of undercover accounts. If these efforts are directed toward surveilling lawful protesters, the public and Congress need to know why this is happening, under what authority and subject to what kinds of oversight and protections,” said Rachel Levinson-Waldman, deputy director of the Liberty & National Security Program of the Brennan Center for Justice.
In response to queries, the Inspection Service defended the iCOP program. “This review of publicly available open source information, including news reports and social media, is one piece of a comprehensive security and threat analysis, and the information obtained is the same information anyone can access as a private citizen,” wrote a spokesperson for the inspection service. “News report and social media listening activity helps protect the 644,000 men and women who work for the Postal Service by ensuring they are able to avoid potentially volatile situations while working to process and deliver the nation’s mail every day.”
The spokesperson referred to the software used by iCOP as “standard law enforcement techniques and tools, which are strictly controlled relative to the investigation of criminal suspects and criminal activities.”
In a statement, Clearview AI, the facial recognition company, said it is “honored to work with over 3,100 law enforcement agencies around the United States to help them identify countless criminals, from pedophiles, serial fraudsters, and murderers. Clearview AI is not a real-time surveillance system, but an after-the-fact investigative tool, and only collects publicly available information from the internet.”
According to the interviews and new documents, the genesis of iCOP appears to date back to 2018, when the U.S. Postal Inspection Service expanded and rebranded its “cybercrime dark web” program into a broader covert operation.
“As the criminal use of the ‘Dark Web’ marketplaces has grown and affected investigative assignments across the agency, we are re-branding the program to encompass all online covert operations beyond ‘Dark Web’ marketplaces to include publicly accessible web sites and private sites,” says an internal description of the change.
The U.S. Postal Inspection Service is part of a Homeland Security intelligence-sharing network that includes, among others, the National Security Agency.
The Department of Homeland Security did not respond to a request for comment.
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