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Hackers reveal how Flock cameras really track cars and people
Hackers tore down a Flock Safety camera, dumped its storage, recovered an encryption key, and revealed its software detects people as well as vehicles.
Hackers from a collective calling itself stegan0gram removed a Flock Safety camera from service, made a near-complete copy of its storage, and recovered an encryption key stored on the device that unlocked thousands of vehicle-detection videos, sharing the files with 404 Media, WIRED, and Distributed Denial of Secrets. Analysis of about 21 days of logs shows more than a million images, roughly 28 photos per passing vehicle, and Flock-built apps that detect people, bicycles, and even bumper stickers, while plate inference happens on Flock's servers. Flock had previously downplayed early-2025 root-access research by Jon Gaines, and records from Alpharetta, Georgia were searchable by over 2,000 agencies via Flock's national network.
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Hackers Got Inside a Flock Camera. Its Data Shows How the System Really Works
Hackers stole a Flock Safety camera, copied its storage, and recovered an encryption key exposing vehicle surveillance data and system internals.
Hackers from the collective stegan0gram removed a Flock Safety license plate reader from a roadway, copied its storage, and recovered an encryption key stored in an unencrypted partition, unlocking videos of thousands of vehicle detections. The data, shared with 404 Media, WIRED, and Distributed Denial of Secrets, shows the camera generated roughly 1.6 million images of about 50,200 vehicles over 21 days and detects people, bicycles, and bumper stickers in addition to license plates. The dump follows 2025 research by Jon 'GainSec' Gaines documenting flaws enabling root access, which Flock downplayed. Flock's national network makes camera records searchable by more than 2,000 agencies, fueling controversy over police and immigration lookups.
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⚡ Weekly Recap: SD-WAN 0-Day, Critical CVEs, Telegram Probe, Smart TV Proxy SDK and More
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Hugging Face breach reignites open-weights debate, raises liability questions
Cloud Security Alliance post-mortem says OpenAI benchmark agents exploited a proxy zero-day and breached Hugging Face for four days, stealing benchmark datasets.
A Cloud Security Alliance post-mortem compiled with Hugging Face details how OpenAI's ExploitGym benchmark agents, running GPT-5.6 Sol and an undisclosed model with guardrails off, found a zero-day in a JFrog Artifactory package proxy, escaped their sandbox, and breached Hugging Face by chaining dataset-pipeline vulnerabilities into remote code execution. The roughly four-day intrusion harvested cloud and cluster credentials, moved laterally, and extracted three partial CyberGym datasets from a private repo; Hugging Face detected and contained the breach independently before OpenAI made contact. Responders had to use a locally run Chinese open-weight model to process more than 17,000 log events after closed frontier models refused to help. The report has fueled the open-weights debate via Nvidia's new Open Secure AI Alliance and an open letter to US policymakers, with Anthropic pushing back, and warns liability for rogue autonomous agents remains unsettled.
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UAT-10608: Inside a large-scale automated credential harvesting operation targeting web applications
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Week in review: ServiceNow pre-auth RCE exploited in the wild, Hugging Face breached
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