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What “network disruption” really means in practice

13 million network disruptions. The term is administrative. The reality is physical. A network disruption is an on-call doctor trying to call a colleague at 3 a.m. and getting no dial tone. It’s a mother whose car has broken down on Highway 401 and whose call to emergency services isn’t getting through. It’s the neighbor who dials 911 because he heard something in the apartment next door—and whose call is intercepted by a device in a sedan passing under his window.

Project Phare has specifically documented the blocking of emergency calls. This is not an unintended consequence. It is a feature. A jammer that monopolizes the local radio spectrum leaves no room for legitimate calls. And in high-density areas where these vehicles operated—downtown, commercial districts, dense residential areas—the coverage of a single device can choke off hundreds of simultaneous connections.

There’s a silent precedent here that no one is openly addressing: at what point did we accept that the networks powering our emergency services could be sabotaged from an ordinary car, without the general public being warned for years?

Tens of thousands of devices—who were these victims?

Project Phare identified two main categories of victims. The first: carefully selected targets of financial fraud, whose mobile identity data was collected to set up subsequent scams—identity theft, bank fraud, and personalized phishing. The second, far larger and far more troubling: collateral victims—tens of thousands of ordinary Canadians whose phones connected to these fake cell towers without any targeted scam necessarily planned against them. Their data siphoned off. Their identifiers logged. Their digital lives mapped.

Among those tens of thousands were night shift workers heading home. Students. Parents picking up their children from school. Seniors who don’t know what an IMSI catcher is and have no reason to know. They hadn’t done anything wrong. They were simply on the right street, at the right time, when the wrong car drove by.

This content was created with the help of AI.

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