Hacker News ★ 82 4 min

Hackers Got Inside a Flock Camera

🔗 https://www.wired.com/story/hackers-flock-camera-data-shows-how-system-works/

📌 拆機取金鑰:駭客揭開 Flock 車牌辨識攝影機的真實運作方式

TL;DR:駭客實體拆下一臺 Flock 監控攝影機並破解其加密儲存,證實系統不只讀車牌,也會偵測畫面中的行人。

面對爭議不斷的監控攝影機,多數人選擇砸毀或拆除洩憤,但一群自稱 stegan0gram 的駭客做了另一件事:把攝影機整臺拆下來,逆向工程裡面的軟體,並把發現公開給媒體,讓其他人也能複製這套方法。

🤔 一臺號稱「裝置端加密」的攝影機

Flock Safety 的自動車牌辨識攝影機(ALPR)已經因為多起爭議登上新聞:404 Media 曾揭露地方警方替 ICE 移民執法單位進行跨州查詢,也曾有德州警員用 Flock 系統搜尋一名自行墮胎的女性,這些報導引發了社會對「社區是否該引進 Flock 攝影機」的全國性辯論。Flock 一直宣稱其裝置端資料受到加密保護;2025 年初,安全研究員 Jon “GainSec” Gaines 曾逆向工程出一臺 Flock 攝影機並找到可取得 root 權限的漏洞,Flock 當時承認了這項發現,但強調攻擊需要實體接觸裝置,且即便取得裝置存取權,也拿不到影像資料,因為影像只會在裝置上短暫留存後便上傳雲端。

🧩 從實體拆機到解密影像

這次 stegan0gram 從路邊拆下一臺攝影機,複製其儲存內容,在 Android 系統中找到兩個未加密的分區:一個叫「vendor」、一個叫「media」。「media」分區裡藏著一組加密金鑰,正好可以解開存放大部分影像與影片的另一個分區。駭客把資料交給去中心化透明組織 Distributed Denial of Secrets,再轉交給 404 Media 與 WIRED 做聯合分析。

分析顯示,這臺攝影機的處理器效能大約相當於中階智慧型手機,跑著約 20 個 Flock 自行開發的 App,負責偵測動作、拍照、物件分類、上傳資料與接收遠端更新。有物體進入畫面時,攝影機會快速連拍,一般車輛平均產生約 28 張影像,部分甚至超過 100 張,並用不同曝光值同時捕捉車牌細節與整體場景,篩選裁切出有用畫面後再透過行動網路上傳。根據分析,實際的車牌辨識,以及車輛品牌、型號、顏色的判讀,似乎是在 Flock 的伺服器端完成,而非攝影機本機端。

📊 21 天的紀錄裡藏了什麼

從可恢復的日誌來看,這臺攝影機在約 21 天的活動期間拍攝了約 50,200 輛車,產生約 160 萬張影像,單日偵測數量最高達 4,454 輛;更早期的紀錄則已被覆寫或無法從裝置中復原。WIRED 從攝影機檔案中萃取出物件偵測模型並實測,證實軟體確實會標記人物在畫面中的位置與偵測信心值,能辨識出包含記者自拍照在內的人臉輪廓;在攝影機儲存的 27,321 段 1 至 2 秒的短片中,有 11 段(皆為機車騎士)被模型偵測到人。車牌偵測器的判讀範圍也相當寬鬆,曾把保險桿貼紙、經銷商車牌框誤判為車牌並裁切下來,其中一段機車騎士的影片裡,甚至把行李袋上的美國國旗貼布當成車牌處理。WIRED 與 404 Media 表示,除了 Android 系統內建、且未被啟用的功能之外,沒有發現任何人臉辨識能力的證據。

⚠️ 樣本仍有侷限

由於這臺攝影機安裝在道路上方、鏡頭朝下拍攝車流,行人本就不太可能出現在畫面中,因此偵測到人的片段數量偏低,不代表所有安裝場景都會是如此;而 21 天之外的歷史紀錄已不可考,無法得知這臺裝置完整的運作歷史。

🎯 實務啟示

對開發或部署電腦視覺監控系統的工程師而言,這起事件是個具體案例:如果加密金鑰與被加密的資料存放在同一臺可被實體接觸的裝置上,「裝置端加密」本身並不足以抵禦有心人拆機分析的風險,威脅模型設計時需要把實體存取攻擊也納入考量,而不只是防範網路層面的入侵。

🔗 來源

#Surveillance #Privacy #ALPR #FlockSafety #ReverseEngineering #Cybersecurity #ComputerVision #DataPrivacy #InfoSec #DigitalRights

原始資料 Hacker News · 收集於 2026-09-16
來源原標題
Hackers Got Inside a Flock Camera
作者
driverdan
原始標籤
hackernews
來源訊號
HN points 370 HN 留言 182
原始連結
https://www.wired.com/story/hackers-flock-camera-data-shows-how-system-works/

摘要原文

Save Story Save this story Save Story Save this story Hackers ripped down a Flock camera above a roadway, made a near-complete copy of the data stored inside it, and shared the files with 404 Media and WIRED, revealing in new detail how exactly Flock Safety’s cameras track the movements of both vehicles and people . The hackers say they are also publishing details on how they managed to obtain the software, in the hopes that other people may copy them. The breach provides an unprecedented look inside a system that Flock has described as protected by on-device encryption . The hackers were able to copy the camera’s storage and recover an encryption key stored on the device, which unlocked videos of thousands of vehicle detections. The hackers shared the material with 404 Media and the transparency nonprofit Distributed Denial of Secrets , which shared the data with WIRED. 404 Media and WIRED then analyzed those files as part of a joint investigation. While much of the automatic license plate reader’s most sensitive storage remained encrypted and inaccessible, the joint analysis of the recovered data shows that software running on the device explicitly detects people as well as vehicles, license plates, and bicycles. The camera can produce dozens of images of a single passing vehicle and, according to several weeks of recovered logs, generated more than a million images. Its computer-vision software also sometimes isolated bumper stickers and other graphics, including, in one case, an American flag patch on a motorcyclist’s saddlebag. The act of removing the camera and dumping its software shows that some people are not content with just destroying or removing the cameras. Across the country, multiple people have been arrested for allegedly tampering with or otherwise sabotaging Flock’s cameras. In response, some towns have announced that they are going to stop using Flock’s cameras altogether, and in one case, a police department even made a fake, 3D-printed Flock camera case in order to bait potential vandals. “Why just destroy them when we can reverse engineer them and find the secrets of those spying on us?” one of the hackers, from a collective calling itself stegan0gram, said in an interview. “We liberated hardware in the field, disarmed them, and proceeded with reverse engineering of the cameras and associated solar equipment.” Flock’s cameras photograph passing vehicles and send the images and other data to the company’s servers. There, Flock’s system presumably reads the license plate and can identify characteristics such as the vehicle’s color, make, and model. Flock then makes these time-stamped records searchable by whichever local agency owns or has access to the cameras. But in many cases, Flock’s system also allows other police departments from all over the country to search those cameras too, as part of the company’s national network. In Alpharetta, Georgia, for example, WIRED found that records from the city’s Flock cameras were accessible to more than 2,000 agencies, including police departments, colleges, airports, and, inexplicably, the Office of Inspector General for the federal General Services Administration. This national network has been a selling point for Flock but also a deep source of controversy. 404 Media revealed that local cops were performing lookups in the national network on behalf of Immigration and Customs Enforcement, including in areas that banned working with immigration authorities or transferring license plate data out of state. 404 Media also revealed that a cop in Texas searched Flock cameras nationwide for a woman who self-administered an abortion. Those stories, among others, triggered a national conversation about whether people want Flock cameras, or automatic license plate readers more generally, in their communities. And in the case of stegan0gram, the answer is clearly no. The hackers said they were able to access the Android system on the camera and found two partitions—sections of its hard drive, essentially. A few of these were unencrypted, the hackers said, including one called “vendor” and another called “media.” The latter contained an encryption key that unlocked another part, which contained much of the media—the videos and stills—the camera took. In early 2025, security researcher Jon “GainSec” Gaines reverse engineered a Flock license-plate reader and documented flaws that could be used to gain root-level access. After Gaines disclosed his findings, the company acknowledged the findings but downplayed their severity, writing that the flaws required physical access to the device and that even someone who gained access to a camera “would still not be able to gain access to footage,” because images remained on the device only briefly after being transmitted to the cloud. 404 Media and WIRED analyzed the camera’s contents. The device’s processor is similar to those used in midrange smartphones, and it runs about 20 Flock-built apps that handle everything from detecting motion and taking pictures to classifying objects, uploading data, and receiving remote updates. According to the code, when something moves into view, the camera takes a rapid series of photos. A typical passing vehicle generated about 28 images, though some produced more than 100. The camera uses different exposures to capture both the license plate and the wider scene, then scans the images, selects and crops useful frames, and sends them with other data to Flock over the cellular network. The camera itself does not appear to read the plate or identify the vehicle’s make, model, and color. That appears to happen on Flock’s servers. According to our analysis, the camera’s logs recorded about 21 days of activity across several periods. During those windows, the device photographed roughly 50,200 vehicles and generated about 1.6 million images. On a typical day, it logged around 3,300 vehicles, with a high of 4,454. Those figures would vary considerably depending on where a camera is installed and how much traffic passes in front of it. The camera was almost certainly operating outside those periods, but older logs had been overwritten or were no longer recoverable from the device. The software running on the camera explicitly detects people, something which is typically overlooked in discussions around Flock cameras. When it spots a person, it records where they appear in the image and how confident it is in the detection. To test what the software could actually see, WIRED extracted the models from the camera’s files and ran them against test images and footage recovered from the device. The models readily detected people, including a selfie of a reporter. WIRED then ran them across 27,321 short videoclips stored on the camera. The clips were MP4 files, each about one to two seconds long, recorded at 1,024 by 768 pixels without audio. They were separate from the rapid bursts of higher-resolution still images the camera also takes as vehicles pass. The models detected people in 11 of the clips, all of them riding motorcycles. The small number is likely due to the camera’s position above a roadway, pointed down at passing traffic where pedestrians were unlikely to appear. The tests also showed how broadly the camera’s license plate detector could interpret what it saw. In some cases it mistook bumper stickers, dealership frames, and other graphics for license plates and cropped them out as if they were plates. In one video of a passing motorcycle, the detector cropped an American flag patch on the rider’s saddlebag as if it were a plate. Flock insists its cameras do not perform face recognition. WIRED and 404 Media found no evidence of any face-recognition capabilities in the camera’s software beyond ones included by default in the Android operating system. Those capabilities did not appear to be enabled or in active use. (370 points, 182 comments on Hacker News)

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