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Man Covers Car in Special Wrap That Breaks Flock Cameras’ Electronic Brains

11 August 2026 at 20:21

In light of plummeting public support for its widespread automatic license plate readers, surveillance company Flock has lost dozens of contracts with cities across the US.

The company even drew up plans to use the dashcams installed in Uber and Lyft drivers’ cars to spy on other vehicles, as 404 Media reported this week.

Citizens are increasingly disgusted by the company’s presence on public streets, opting to hack down the cameras, blind them, or sabotage them in other creative ways.

“His project, which he calls noRecognition, allows people to escape the automatic detection and algorithmic surveillance used across the U.S. and beyond.” https://t.co/OIQNOt9B0a @TechCrunch

— Christina Ayiotis, Esq., CRM, CIPP/E, AIGP (@christinayiotis) August 10, 2026

And according to cybersecurity researcher Bill Swearingen, there may be other creative ways to befuddle Flock’s spy cams. He devised with a special computer-generated pattern which, once stretched out across the vehicle in the form of a wrap, will result it in not being flagged as a car by Flock’s cameras.

During this year’s Def Con cybersecurity conference in Las Vegas, Swearingen showed off a 2009 Toyota Yaris wrapped in vinyl featuring the logo of automotive publication Donut Media (which is owned by Futurism‘s parent company Recurrent Ventures.)

Despite the car looking a bit chaotic — albeit still very much like a small passenger vehicle to the human eye — “we proved it was effective,” Swearingen told TechCrunch. The Yaris successfully defeated surveillance detection at Def Con during the pattern’s first public test.

“Privacy is a fundamental right,” he added, aiming to give people a way to “opt out of being tracked.”

To come up with the pattern, he used a reinforcement learning model that trained itself on patterns that evade detection. The model got to the point of being able to confuse all 11 open source detection algorithms he tested, per TechCrunch, in addition to Flock’s license plate readers and even Axon’s body-worn cameras used by police departments.

As part of his noRecognition crowdsourcing campaign, Swearingen has also come up with T-shirts and hoodies that feature algorithmic detection-busting patterns. He hopes to eventually put pattern-printed skins for entire cars on sale as well.

The effort is part of a much broader trend of companies offering up garments that incorporate “adversarial patterns,” which can exploit weaknesses in computer vision systems.

One thing is clear: as outrage over Flock’s heavy presence across the country grows, people are looking for any way to foil the tech — especially if it looks cool.

More on Flock: Flock’s Secret Surveillance Plan Will Make You Gasp

The post Man Covers Car in Special Wrap That Breaks Flock Cameras’ Electronic Brains appeared first on Futurism.

Japanese authorities use new tool to identify initial torrent uploaders — anti-piracy group says it identified seeder on popular anime torrenting website without torrent swarm monitoring

Recently, the Kyoto Prefectural Police caught one of the initial-seeders of the well-known Japanese torrent website Nyaa. Masakazu Ono, 56, from Sagamihara in the Kamigawa Prefecture, was arrested after a multi-year investigation. While this news is straightforward by itself, the interesting bit is that CODA, the Japanese anti-piracy entity that performed the initial cyber-investigation, identified Ono allegedly without joining or monitoring BitTorrent swarm traffic, with the help of the Japan Hacker Association (JHA).

CODA's description of only having "[analyzed] how data moves through torrent sites, such as index sites and tracker sites" is vague and can be parsed in a number of ways. The distinction between indexer and tracker is relevant: while an indexer is a user-visible list of torrents (usually a website), the tracker is the background service that software like qBittorrent actually connects to, and it lists everyone who's currently active in that torrent, whether sharing, downloading, or both.

Our hypothesis is that CODA kept close tabs on the Nyaa trackers to see which IP address (in this case, Ono's) consistently appeared as the first person to offer up a 100% complete set of data for a show, a theory that would fit with how long the operation took. JHA's founder, Takayuki Sugiura, was the first to decrypt the Winny P2P protocol in 2004 to find original uploader sources, and the methods used weren't too different from the aforementioned theory. It's also possible that Ono wasn't using a VPN but was logged into Nyaa, or activity at another website's cookies or CDN logs was used to establish a link to his activity at Nyaa, and from thereon, to the tracker.

An initial-seeder is someone who is the first to offer up data for others to download — in this case, shows and movies. The show that reportedly got Ono nailed was Midnight Taxi, a 2026 Japanese drama produced by NHK and WOWOW. However, the police apparently had been tracking him for quite a while and claimed that he had uploaded close to a thousand NHK recordings over the investigation's span.

The process started in 2021 when CODA first launched its Cross-Border Enforcement Project, aiming to identify Nyaa's uploaders. During three years, with the help of JHA, CODA seemingly collected enough information to get the Kyoto police involved in 2024. Three "secondary uploaders" from "reach sites" were charged in 2025, likely meaning regular users participating in the torrents, who got there through link aggregator sites. Fast-forward to a couple of weeks ago, and Masakazu Ono was formally arrested with specific charges.

The most common techniques used by law enforcement agencies are creating a tracker honeypot or participating in the torrent swarm themselves in a bid to identify who's sharing files. However, Nyaa's list of trackers is small and comprises well-known, trusted servers, so together with CODA's wording, it's unlikely this was the method used. Furthermore, Japanese law generally frowns on non-targeted data monitoring, meaning that techniques like Deep Packet Inspection (DPI) and traffic volume monitoring likely weren't used, at least until such time as Ono was identified.

Australia, Singapore Deepen AI and Cybersecurity Cooperation

10 August 2026 at 17:00
Australia and Singapore are expanding cooperation on AI safety, cybersecurity, digital infrastructure, and subsea-cable resilience through their first Cyber and Digital Senior Officials Dialogue.

Steam hardware distributor hit by cyberattack, 'expect fake messages,' Valve warns — Europe vendor has personal information and hardware purchase details stolen

10 August 2026 at 12:49

Steam hardware customers in Europe should “expect fake messages - email, SMS or phone,” says Valve in an email bulletin circulating today. The problem is that its European hardware distributor, CEVA Logistics, has fallen prey to a cyberattack where personal information and hardware purchase details were compromised. The most sensitive data, such as payment information, passwords, and/or Steam Guard codes, was not pilfered during the attack.

Valve EU shipping partner hit by cyberattack.

— @joel.zone (@joel.zone.bsky.social) 2026-08-10T11:42:07.084Z

According to the official communication from Valve, CEVA was hit by a cyberattack between July 29 and August 1, 2026. The PC gaming company says that it learned that hackers had successfully swiped a range of information about Steam hardware customers on August 7.

As this data was in the hands of CEVA, it was strictly limited to delivery-related information. That means the cyberattackers now likely have a database of hardware customer information that will include fields like names, addresses, phone numbers, email addresses, and the type and price of the product(s) ordered. CEVA holds this type of information for 90 days to cover fulfillment of the hardware order. It is worth repeating that the attacked distributor won’t have spilled data such as payment information, passwords, and/or Steam Guard codes.

The likely fallout customers should be wary of

Valve candidly warns those who have purchased Steam hardware like a Steam Deck or Steam Machine in Europe over recent months to “expect fake messages - email, SMS or phone - that mention your hardware order and appear to come from Steam, Valve or a delivery company.” Likely angles used by swindlers will be to ask for extra customs or delivery fees. They may also ask you to sign into some fake web portal or other. However, you should ignore such requests, of course, and changing your Steam password or anything to do with your account settings is not necessary, insists Valve.

If you are in any doubt about a communication that comes from Steam / Valve or a distributor, please check the URLs carefully. For example, Steam Support only handles account issues at help.steampowered.com, and only store.steampowered.com, www.steampowered.com, steamcommunity.com, or help.steampowered.com are ever used for Steam account logins. You are advised to type these into a browser yourself and not click any email-embedded links. We assume poking around the official Steam App on your PC will also be fine, and many of you will have that auto-running when your PC starts up. Lastly, you are reminded that “Steam Support will never ask you for your password or a Steam Guard code. Neither will a courier.”

CEVA isolated the affected systems and notified data protection authorities after discovering the hack. It has brought in outside investigators.

Scammers Tremble as AI Comes for Their Jobs

9 August 2026 at 20:01

Turns out there’s one thing AI chatbots are definitively better at than humans: scamming innocent people.

A new piece of research flagged by Wired found that large language models are significantly better than humans at pulling off “pig butchering” scams, a form of online investment fraud where criminals pursue fake, long-term relationships with targets in order to build trust before cleaning them out financially.

To pull off the study, researchers at Northeastern and a grab bag of international institutions pitted 22 test subjects against two forms of scammers: one an AI chatbot, the other a random human. After a seven-day courtship period, the “scammers” asked their “victims” to either download an app or play an online game, a stand-in for a financially-manipulative request (asks that, in the real world, could be used to hack a victim’s device).

Overall, just 18 percent of the human scammers acquiesced, while the AI chatbots were much more successful, courting nearly half of the participants.

While the results are troubling enough, the ease with which researchers were able to build the scammy LLMs is arguably more frightening. The study primarily used a Claude model, which was instructed not to admit under any circumstance that is was an AI chatbot.

The Claude bot obeyed with remarkable dedication, denying that it was an AI chatbot when asked, and even coming up with cover stories when challenged.

“With relatively little effort, we’re able to make an agent that can outperform a human at building this exploitable emotional trust,” Yisroel Mirsky, computer science professor at Ben Gurion University and one of the study’s co-authors, told Wired.

Equally alarming was the response from participants after the experiment was over. Though 20 out of the 22 victims were able to identify which of the two scammers was an AI chatbot, the researchers told Wired there was plenty of shock, and even denial.

“Some people were just blown away,” said University Amrita Vishwa Vidyapeetham professor Gilad Gressel. “They just had absolutely no idea.”

More on AI: US Government Displays AI-Mangled Map of Africa That Gets Every Single Country Wrong

The post Scammers Tremble as AI Comes for Their Jobs appeared first on Futurism.

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