Slovakia warns that vulnerable speed cameras could expose vehicle data, enable remote access and provide attackers with a foothold into public networks. Slovakia’s National Security Authority, NBÚ, recently issued a warning about several road speed cameras, calling them a significant cyber threat. The alert is not about someone deleting a speeding ticket. It is about connected devices that collect vehicle data, communicate with other systems, and may contain remote-access functions that the operator cannot fully control. The Slovak authority examined a sample of the NERO R-ONE camera system at the request of the Interior Ministry. It named three product lines in its warning: NERO R-ONE devices sold by Cyprus-based SODASUS, Cordon-series speed cameras made by Russia’s Simicon, and Cordon-series products sold by Croatia’s NEROline. “The National Security Authority warns of a significant cyber threat associated with the use of several types of road speed cameras.” reads the alert. “A security analysis has identified several risks and recommends that affected entities identify the products in question in their infrastructure.” The problems went beyond a simple configuration issue. NBÚ found differences between the documented and actual communication settings, uncertainty about where the hardware and software came from, software that did not match the declared version, and weak security protections. “The security analysis identified several risks, including the true origin of the camera hardware and software, inconsistency between the documented and detected configuration of the product’s communication interfaces, and pre-configured remote access and product management mechanisms.” the agency wrote on LinkedIn. That last point deserves attention. A road camera should be managed by the organisation that owns it, under controls that it can inspect, configure and audit. If a device includes pre-set remote-access or management mechanisms outside the customer’s full control, it creates a blind spot in a system that may sit on a public-sector network or communicate with other operational services. Speed cameras do much more than take pictures and measure speed. They photograph vehicles, record timestamps, process licence-plate data, store evidence and send information to backend systems used by authorities. Depending on the setup, they may also connect to mobile networks, roadside equipment, police systems, municipal platforms or third-party maintenance services. If attackers compromise a camera, they could access data, change or delete records, manipulate how it measures or reports violations, or shut it down. If the network lacks proper segmentation, they could also use the camera as a foothold to reach other systems. The camera may not be the real target. It could simply be the unlocked door. The warning aims to alert essential-service operators and other organisations that these road cameras could pose a serious cybersecurity risk. In the wrong circumstances, attackers could use them to disrupt networks, systems or services. The Slovak Interior Ministry reportedly took the equipment out of its pilot deployment while the matter was investigated. Public reporting also says the ministry asked the supplier to remove the units and replace them with equipment meeting Slovak and EU legal, technical and security requirements. The Russian connection adds an obvious geopolitical dimension, but it should not become a substitute for technical analysis. NBÚ did not say that every device was actively spying on users or that the equipment contained a proven backdoor. Its warning is about identified security risks, limited operator control, uncertainty over hardware and software provenance, and remote-management mechanisms that could not be fully accounted for. That is enough reason to take action. Security checks for connected public devices cannot rely only on the brand, the country listed on the invoice or the vendor’s claims. Operators should know exactly what software and firmware the device runs, how remote access works and who controls it. They should also use independent security testing, secure updates and network segmentation. The same lesson applies beyond Slovakia. Smart cameras, licence-plate readers, parking sensors, environmental monitors, traffic lights and roadside communication systems are becoming part of public infrastructure. They are often cheap, easy to overlook and managed by public agencies, contractors and manufacturers. That makes them just as important to secure as other critical systems. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, Speed Cameras)
A package gets installed. A login prompt opens. A box sits exposed to the internet. Nothing looks unusual yet. That’s roughly the mood this week. Trusted tools turn hostile, old weak spots get fresh attention, AI makes exploit work cheaper, and researchers keep finding attacks that sound harder than they actually are. Plenty to clean up. Here’s the short version. ⚡ Threat of the Week U.S.
Toronto's Hospital for Sick Children (SickKids) says a cybersecurity incident exposed the personal information of some current and former employees and job applicants, stemming from a flaw in third-party software. Clinical systems and patient records were not affected. (264)
U.S. cybersecurity agencies warn that threat actors are using AI-generated scripts to exploit Siemens S7 Series programmable logic controllers (PLCs) in U.S. critical infrastructure. PLCs are industrial computers used to automate and control machinery and physical processes in factories and other critical infrastructure. The NSA, CISA, FBI, Department of Energy, and Environmental Protection Agency issued the joint advisory Wednesday, saying the attacks are ongoing. "This advisory relates to an active threat to Siemens S7 Series programmable logic controllers (PLCs)," reads the advisory. "However, ongoing PLC targeting activity is broader than Siemens PLCs. All PLC owners and operators should apply relevant mitigations to reduce the risk to their devices and systems." The critical infrastructure sectors most targeted include Critical Manufacturing, Energy, Water and Wastewater Systems, Chemical, Food and Agriculture, and Commercial Facilities. The agencies also note that Siemens S7 PLCs are used in the Defense Industrial Base, which could also be targeted.
Most email defenses still do the job they did a decade ago. Scan the message, look for something malicious, block it. That worked when the danger sat in the payload, a bad link or an attachment. It stopped working when the danger moved into the message's intent, and it is failing now that the sender is no longer a person. From Bad Content to Bad Intent to AI on Both Sides Phishing 1.0 was bad
Researchers tested 31 million patterns to disrupt surveillance AI, with promising results but significant gaps between simulation and real-world use. The Kansas City-based cybersecurity researcher Bill Swearingen spent the past year doing something that sounds almost too simple to work: printing patterns, watching cameras fail to detect them, and repeating. TechCrunch reports that after roughly 31 million tests, he can now generate patterns on demand that block license plate readers and surveillance cameras from recognizing whatever the pattern covers, whether that’s a person or a vehicle. The project is called noRecognition, and the core idea isn’t stealth in the traditional sense. The camera still records everything just fine. What breaks is the detection layer sitting on top of the footage, the software that flags license plates, tracks faces, or spots “activity of interest” across thousands of hours of video. Swearingen’s patterns don’t hide you from the lens; they make the algorithm looking through that lens shrug and move on. Swearingen, co-founder of the SecKC meetup, said his project started for personal reasons. He became concerned about the growing number of surveillance cameras in his town and the possibility of being tracked while attending a protest. What started as a simple experiment later became a reinforcement learning system. He taught the model to create patterns, learn from failures and keep improving. Over time, it learned how to avoid detection by several camera systems. Every time a pattern failed and got detected, the system adjusted and tried again, eventually learning to defeat multiple detection algorithms simultaneously rather than just one at a time. The research dashboard behind the project, published at sandbox.norecognition.org, goes considerably deeper into the numbers than the headline claim suggests, and it’s refreshingly upfront about what’s proven versus what isn’t. The team states its overall objective plainly as “one pattern that defeats every detector,” and by their own account that goal remains only partially met. Their strongest validated result against a detector extracted directly from a real deployed surveillance camera sits at 61.7% non-detection across held-out test subjects, a solid number, but nowhere near total, and still a digital simulation rather than a real-world fabric test. That distinction matters more than it might seem. Most of the dashboard’s headline figures are explicitly labeled as digital, simulated results, meaning the pattern was tested against a virtual camera and printed ink model rather than an actual garment photographed by an actual camera in the field. The gap between “works in simulation” and “works when Donut Media wraps a real 2009 Toyota Yaris in it,” which is the physical test Swearingen ran live at DEF CON, is exactly the gap this kind of research has to close before anyone should treat it as a reliable, everyday privacy tool. “On Friday at the Def Con cybersecurity conference in Las Vegas, Swearingen ran his first real-world test. With help from Donut Media, the test involved covering a 2009 Toyota Yaris with one of Swearingen’s newest patterns to see if the car would be invisible to detection by a Flock camera.” reports TechCrunch. “We proved it was effective,” said Swearingen, though the wheels were a challenge. The video of the demo will be out in the next few weeks, said Donut Media.” That DEF CON demo is where things got concrete. Swearingen covered a car in one of his newest patterns and tested it against a Flock Safety camera, the kind widely deployed for automated license plate reading across the US. He said the test proved effective, though the vehicle’s wheels turned out to be a persistent weak point, curved surfaces apparently don’t cooperate with flat printed patterns the way a car door does. Source Tech Crunch – A photo of a 2009 Toyota Yaris at the Def Con conference in Las Vegas, covered in a pattern made by Bill Swearingen, as part of a test to see if it can defeat surveillance camera detection. Image Credits:Bill Swearingen / Donut Media Swearingen is not publishing his best patterns because he does not want camera makers to easily find and block them. Instead, he is using crowdfunding to develop and sell printed products such as T-shirts and hoodies, with vehicle wraps possibly coming later. It is still unclear whether the project will become a practical privacy tool for everyday users or remain mainly a DEF CON demonstration. Its real effectiveness will depend on how well the patterns work on real clothing, in different weather and camera conditions. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, Surveillance camera)
Two critical vulnerabilities impacting MLflow, an open-source artificial intelligence (AI) platform, and FUXA, an open-source, web-based SCADA / HMI software built for operational technology (OT) and industrial automation, are witnessing malicious scanning and exploitation efforts. According to independent reports from watchTowr and VulnCheck, the vulnerabilities in question are as follows -
Pokémon Center is notifying customers in the United Kingdom and Germany that it suffered a third-party data breach after hackers stole customer personal and order information from third-party logistics provider CEVA Logistics. While CEVA's systems were compromised in the cyberattack, the exposed records belonged to Pokémon Center customers who submitted orders on the site. The company then shared this information with the logistics provider to fulfill and ship PokemonCenter.com orders. CEVA Logistics is a subsidiary of the CMA CGM Group, the world's third-largest shipping company. The logistics provider operates 1,000 warehouses, handled 15 million shipments last year, and reported $18.3 billion in revenue in 2025. The company recently suffered a cyberattack in which attackers breached its servers between July 29 and August 1, affecting multiple retailers in Europe.
The French Ministry of the Economy and Finance has disclosed a data breach after an attacker accessed the General Directorate of Public Finances (DGFiP) systems and stole data belonging to 678,000 individuals. This incident was discovered after a threat actor using the "ZeroBytes" handle claimed the attack and listed a stolen database for sale on August 12 on the PwnForums hacking forum. "The in-depth investigations conducted since August 12, 2026, have established that, prior to their interruption, these access points had been used to consult and extract data concerning a total of 678,000 individuals and professionals, including tax data such as reference tax income, family quotient, and withholding tax rate, and, for businesses, data such as their company name and SIREN number," the French Finance Ministry said.
Cryptocurrency hardware wallet provider SafePal is warning of a data breach affecting about 39,798 customers after a flaw was exploited to steal customer order information, and a threat actor is now claiming to be selling the stolen data. SafePal says the breach impacts customers who placed orders between March 2, 2025, and April 11, 2026, exposing their names, email addresses, shipping addresses, phone numbers, and purchase information. The company says the breach did not expose customers' wallet seed phrases, private keys, passwords, bank account information, payment card numbers, government-issued identification numbers, or other credentials. "No evidence has been found that the incident itself compromised access to SafePal wallets or funds," SafePal said in a security advisory published Sunday.
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