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Hackers Stole Flock’s Camera Software, Revealing How the Company Tracks Cars and People

Hackers who removed a Flock Safety license plate camera dumped its data, revealing person-detection capabilities and an encryption key stored unencrypted on the device.

A hacker collective calling itself stegan0gram physically removed a Flock Safety automatic license plate reader camera from a roadway, copied its storage, and shared the files with 404 Media, WIRED, and Distributed Denial of Secrets. Analysis found an encryption key in an unencrypted 'media' partition that unlocked videos of thousands of vehicle detections, with logs showing more than a million images generated in weeks. The software explicitly detects people, bicycles, and even bumper stickers, and records from one Georgia city were searchable by more than 2,000 agencies nationwide. The findings follow 2025 research by Jon Gaines documenting flaws enabling root-level access to Flock cameras.

404 Mediaupdated · 9h agofirst · 20h agoResearch in the wild 3 sources

Automobile Camouflage to Hide from Flock Cameras

Schneier on Security highlights a printed vehicle-camouflage pattern tested to defeat Flock surveillance cameras and Axon body cameras.

The post discusses covering cars with printed patterns designed to fool Flock automated license-plate recognition software, with testing reportedly done against Flock and Axon body cameras. Reader comments question effectiveness against other ALPR vendors, Flock's RF MAC-address upgrade, and whether such camouflage might become regulated. The page also contains off-topic comment threads about anti-bot over-blocking and privacy.

Schneier on Security · 9d agoResearch

Forgery of C2PA on a Pixel 10

Researcher forged a Google Pixel 10 C2PA content credential with genuine signatures, showing root-level attackers can fake photo provenance.

A Hacker Factor blog post demonstrates an AI-generated 'unicorn glitter milk' news photo carrying a valid, cryptographically signed C2PA manifest traceable to Google's Pixel camera certificate chain, passing validation in Adobe Inspect and the CAI Verify tool with a verified timestamp. The author, working with UMBC's PASAWG working group, reported to Google and C2PA in November 2025 that root access on a Pixel device could sign arbitrary images as camera captures; after 90 days without resolution, details were published. The finding undermines C2PA Assurance Level 2 claims made for Pixel 10 Content Credentials.

Lobsters · security · 18h agoResearch

Apple Reference Image: A New Approach for Verified Photography

Apple introduces Reference Image, hardware-backed verifiable photography on iPhone 18 Pro using sensor signing and Private Cloud Compute to counter AI-generated fakes.

Apple announced Reference Image, an opt-in camera mode debuting on the main sensor of iPhone 18 Pro and iPhone 18 Pro Max that produces securely timestamped, verifiable photographs. The design splits into two phases: a secure digital negative created by cryptographically signing pixel data at the sensor immediately after capture (preventing injection or tampering), then developing that negative into a reference image. Private Cloud Compute handles processing without exposing image contents to anyone, including Apple, and fraudulent reference images can be revoked without revealing the photographer's identity. Apple positions the system as stronger than C2PA-based approaches, which sign metadata after capture, are vulnerable to editing-chain compromise, and can tie images to a device or individual.

Researchers built a $7 gadget for anyone paranoid about hidden cameras in hotel rooms

KAIST-led researchers built SweepLED, a sub-$7 smartphone LED clip using AI to detect hidden cameras with 93.9-95.1% accuracy.

SweepLED, built by KAIST with the National University of Singapore and Singapore Management University, clips 15 LEDs to a smartphone camera and sweeps multi-angle light while the phone films reflections. A spatio-temporal AI model compares LED-on and LED-off frames to distinguish lens reflections from glossy surfaces across three viewpoints. Testing on 30 objects, 12 with hidden cameras, achieved 93.9% accuracy handheld and 95.1% static. Core components cost under $7, targeting privacy checks in hotels and short-term rentals.

Help Net Security · 14d agoResearch1

Illusion of Depth: Revealing Hidden Stereo Vision Vulnerabilities in Depth Estimation

Simple repeating patterns let attackers shift stereo-camera depth estimates by up to 20 meters, triggering emergency braking in autonomous driving frameworks at 40 km/h.

The paper reveals an intrinsic vulnerability in stereo cameras stemming from pixel sampling and calibration processes, letting attackers finely control estimated depth of real obstacles using simple repeating patterns without adversarial ML techniques. The attack was evaluated against BM and SGBM stereo matching algorithms, deep learning models PSMNet, MoCha-Stereo, and UniMatch, the stereo-LiDAR fusion model SGM-DDC, and commercial cameras ZED2 and Intel RealSense D435; on ZED2, obstacles can be displaced up to 20 meters farther or 12 meters closer. A 0.5-second attack triggered emergency braking in a popular autonomous driving framework, with feasibility confirmed at driving speeds up to 40 km/h using CARLA. State-of-the-art defenses proved ineffective, and the authors propose a similarity-score strategy to dynamically detect and suppress depth discrepancies.

arXiv cs.CR · 2d agoResearch

Risks in IoT Supply Chain

Unit 42 analyzes multilayer IoT supply chain risks across hardware, firmware, and software, citing counterfeit Cisco switches and OpenWrt attacks.

Unit 42 examines weaknesses in the IoT supply chain ecosystem across hardware, firmware, operation, and vulnerability layers, noting that 89% of IT decision-makers reported IoT device growth and IDC forecast 41.6 billion connected IoT devices by 2025. Examples include counterfeit Cisco Catalyst 2960-X switches with possible backdoor access (F-Secure, July 2020), a March 2020 OpenWrt flaw enabling malicious update impersonation, and threat actor interest in TeamViewer remote support software. The report stresses that untracked third-party components and missing device inventories make it hard to assess vulnerability impact across vendors.

Palo Alto Unit 42 · 28d agoResearch

New surveillance tech links your phone to your license plate

Researchers show roadside cameras plus Bluetooth signals can link phones to license plates, enabling richer tracking.

Ars Technica reports on new surveillance research showing that combining roadside camera license plate recognition with phone Bluetooth signals can associate specific devices with specific vehicles. The approach could turn existing traffic cameras into far richer tracking tools that follow both a car and its occupant's phone. The work raises significant privacy and civil liberties concerns.

Ars Technica · Security · Aug 11, 2026Research