Entries Tagged "cameras"

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Zoom Vulnerability

The Zoom conferencing app has a vulnerability that allows someone to remotely take over the computer’s camera.

It’s a bad vulnerability, made worse by the fact that it remains even if you uninstall the Zoom app:

This vulnerability allows any website to forcibly join a user to a Zoom call, with their video camera activated, without the user’s permission.

On top of this, this vulnerability would have allowed any webpage to DOS (Denial of Service) a Mac by repeatedly joining a user to an invalid call.

Additionally, if you’ve ever installed the Zoom client and then uninstalled it, you still have a localhost web server on your machine that will happily re-install the Zoom client for you, without requiring any user interaction on your behalf besides visiting a webpage. This re-install ‘feature’ continues to work to this day.

Zoom didn’t take the vulnerability seriously:

This vulnerability was originally responsibly disclosed on March 26, 2019. This initial report included a proposed description of a ‘quick fix’ Zoom could have implemented by simply changing their server logic. It took Zoom 10 days to confirm the vulnerability. The first actual meeting about how the vulnerability would be patched occurred on June 11th, 2019, only 18 days before the end of the 90-day public disclosure deadline. During this meeting, the details of the vulnerability were confirmed and Zoom’s planned solution was discussed. However, I was very easily able to spot and describe bypasses in their planned fix. At this point, Zoom was left with 18 days to resolve the vulnerability. On June 24th after 90 days of waiting, the last day before the public disclosure deadline, I discovered that Zoom had only implemented the ‘quick fix’ solution originally suggested.

This is why we disclose vulnerabilities. Now, finally, Zoom is taking this seriously and fixing it for real.

EDITED TO ADD (8/8): Apple silently released a macOS update that removes the Zoom webserver if the app is not present.

Posted on July 16, 2019 at 12:54 PMView Comments

Computers and Video Surveillance

It used to be that surveillance cameras were passive. Maybe they just recorded, and no one looked at the video unless they needed to. Maybe a bored guard watched a dozen different screens, scanning for something interesting. In either case, the video was only stored for a few days because storage was expensive.

Increasingly, none of that is true. Recent developments in video analytics—fueled by artificial intelligence techniques like machine learning—enable computers to watch and understand surveillance videos with human-like discernment. Identification technologies make it easier to automatically figure out who is in the videos. And finally, the cameras themselves have become cheaper, more ubiquitous, and much better; cameras mounted on drones can effectively watch an entire city. Computers can watch all the video without human issues like distraction, fatigue, training, or needing to be paid. The result is a level of surveillance that was impossible just a few years ago.

An ACLU report published Thursday called “the Dawn of Robot Surveillance” says AI-aided video surveillance “won’t just record us, but will also make judgments about us based on their understanding of our actions, emotions, skin color, clothing, voice, and more. These automated ‘video analytics’ technologies threaten to fundamentally change the nature of surveillance.”

Let’s take the technologies one at a time. First: video analytics. Computers are getting better at recognizing what’s going on in a video. Detecting when a person or vehicle enters a forbidden area is easy. Modern systems can alarm when someone is walking in the wrong direction—going in through an exit-only corridor, for example. They can count people or cars. They can detect when luggage is left unattended, or when previously unattended luggage is picked up and removed. They can detect when someone is loitering in an area, is lying down, or is running. Increasingly, they can detect particular actions by people. Amazon’s cashier-less stores rely on video analytics to figure out when someone picks an item off a shelf and doesn’t put it back.

More than identifying actions, video analytics allow computers to understand what’s going on in a video: They can flag people based on their clothing or behavior, identify people’s emotions through body language and behavior, and find people who are acting “unusual” based on everyone else around them. Those same Amazon in-store cameras can analyze customer sentiment. Other systems can describe what’s happening in a video scene.

Computers can also identify people. AIs are getting better at identifying people in those videos. Facial recognition technology is improving all the time, made easier by the enormous stockpile of tagged photographs we give to Facebook and other social media sites, and the photos governments collect in the process of issuing ID cards and drivers licenses. The technology already exists to automatically identify everyone a camera “sees” in real time. Even without video identification, we can be identified by the unique information continuously broadcasted by the smartphones we carry with us everywhere, or by our laptops or Bluetooth-connected devices. Police have been tracking phones for years, and this practice can now be combined with video analytics.

Once a monitoring system identifies people, their data can be combined with other data, either collected or purchased: from cell phone records, GPS surveillance history, purchasing data, and so on. Social media companies like Facebook have spent years learning about our personalities and beliefs by what we post, comment on, and “like.” This is “data inference,” and when combined with video it offers a powerful window into people’s behaviors and motivations.

Camera resolution is also improving. Gigapixel cameras as so good that they can capture individual faces and identify license places in photos taken miles away. “Wide-area surveillance” cameras can be mounted on airplanes and drones, and can operate continuously. On the ground, cameras can be hidden in street lights and other regular objects. In space, satellite cameras have also dramatically improved.

Data storage has become incredibly cheap, and cloud storage makes it all so easy. Video data can easily be saved for years, allowing computers to conduct all of this surveillance backwards in time.

In democratic countries, such surveillance is marketed as crime prevention—or counterterrorism. In countries like China, it is blatantly used to suppress political activity and for social control. In all instances, it’s being implemented without a lot of public debate by law-enforcement agencies and by corporations in public spaces they control.

This is bad, because ubiquitous surveillance will drastically change our relationship to society. We’ve never lived in this sort of world, even those of us who have lived through previous totalitarian regimes. The effects will be felt in many different areas. False positives­—when the surveillance system gets it wrong­—will lead to harassment and worse. Discrimination will become automated. Those who fall outside norms will be marginalized. And most importantly, the inability to live anonymously will have an enormous chilling effect on speech and behavior, which in turn will hobble society’s ability to experiment and change. A recent ACLU report discusses these harms in more depth. While it’s possible that some of this surveillance is worth the trade-offs, we as society need to deliberately and intelligently make decisions about it.

Some jurisdictions are starting to notice. Last month, San Francisco became the first city to ban facial recognition technology by police and other government agencies. A similar ban is being considered in Somerville, MA, and Oakland, CA. These are exceptions, and limited to the more liberal areas of the country.

We often believe that technological change is inevitable, and that there’s nothing we can do to stop it—or even to steer it. That’s simply not true. We’re led to believe this because we don’t often see it, understand it, or have a say in how or when it is deployed. The problem is that technologies of cameras, resolution, machine learning, and artificial intelligence are complex and specialized.

Laws like what was just passed in San Francisco won’t stop the development of these technologies, but they’re not intended to. They’re intended as pauses, so our policy making can catch up with technology. As a general rule, the US government tends to ignore technologies as they’re being developed and deployed, so as not to stifle innovation. But as the rate of technological change increases, so does the unanticipated effects on our lives. Just as we’ve been surprised by the threats to democracy caused by surveillance capitalism, AI-enabled video surveillance will have similar surprising effects. Maybe a pause in our headlong deployment of these technologies will allow us the time to discuss what kind of society we want to live in, and then enact rules to bring that kind of society about.

This essay previously appeared on Vice Motherboard.

Posted on June 14, 2019 at 12:04 PMView Comments

iOS Shortcut for Recording the Police

Hey Siri; I’m getting pulled over” can be a shortcut:

Once the shortcut is installed and configured, you just have to say, for example, “Hey Siri, I’m getting pulled over.” Then the program pauses music you may be playing, turns down the brightness on the iPhone, and turns on “do not disturb” mode.

It also sends a quick text to a predetermined contact to tell them you’ve been pulled over, and it starts recording using the iPhone’s front-facing camera. Once you’ve stopped recording, it can text or email the video to a different predetermined contact and save it to Dropbox.

Posted on June 7, 2019 at 6:24 AMView Comments

Hidden Cameras in Streetlights

Both the US Drug Enforcement Administration (DEA) and Immigration and Customs Enforcement (ICE) are hiding surveillance cameras in streetlights.

According to government procurement data, the DEA has paid a Houston, Texas company called Cowboy Streetlight Concealments LLC roughly $22,000 since June 2018 for “video recording and reproducing equipment.” ICE paid out about $28,000 to Cowboy Streetlight Concealments over the same period of time.

It’s unclear where the DEA and ICE streetlight cameras have been installed, or where the next deployments will take place. ICE offices in Dallas, Houston, and San Antonio have provided funding for recent acquisitions from Cowboy Streetlight Concealments; the DEA’s most recent purchases were funded by the agency’s Office of Investigative Technology, which is located in Lorton, Virginia.

Fifty thousand dollars doesn’t buy a lot of streetlight surveillance cameras, so either this is a pilot program or there are a lot more procurements elsewhere that we don’t know about.

Posted on November 16, 2018 at 6:02 AMView Comments

Consumer Reports Reviews Wireless Home-Security Cameras

Consumer Reports is starting to evaluate the security of IoT devices. As part of that, it’s reviewing wireless home-security cameras.

It found significant security vulnerabilities in D-Link cameras:

In contrast, D-Link doesn’t store video from the DCS-2630L in the cloud. Instead, the camera has its own, onboard web server, which can deliver video to the user in different ways.

Users can view the video using an app, mydlink Lite. The video is encrypted, and it travels from the camera through D-Link’s corporate servers, and ultimately to the user’s phone. Users can also access the same encrypted video feed through a company web page, mydlink.com. Those are both secure methods of accessing the video.

But the D-Link camera also lets you bypass the D-Link corporate servers and access the video directly through a web browser on a laptop or other device. If you do this, the web server on the camera doesn’t encrypt the video.

If you set up this kind of remote access, the camera and unencrypted video is open to the web. They could be discovered by anyone who finds or guesses the camera’s IP address­—and if you haven’t set a strong password, a hacker might find it easy to gain access.

The real news is that Consumer Reports is able to put pressure on device manufacturers:

In response to a Consumer Reports query, D-Link said that security would be tightened through updates this fall. Consumer Reports will evaluate those updates once they are available.

This is the sort of sustained pressure we need on IoT device manufacturers.

Boing Boing link.

EDITED TO ADD (11/13): In related news, the US Federal Trade Commission is suing D-Link because their routers are so insecure. The lawsuit was filed in January 2017.

Posted on November 7, 2018 at 6:39 AMView Comments

Lifting a Fingerprint from a Photo

Police in the UK were able to read a fingerprint from a photo of a hand:

Staff from the unit’s specialist imaging team were able to enhance a picture of a hand holding a number of tablets, which was taken from a mobile phone, before fingerprint experts were able to positively identify that the hand was that of Elliott Morris.

[…]

Speaking about the pioneering techniques used in the case, Dave Thomas, forensic operations manager at the Scientific Support Unit, added: “Specialist staff within the JSIU fully utilised their expert image-enhancing skills which enabled them to provide something that the unit’s fingerprint identification experts could work. Despite being provided with only a very small section of the fingerprint which was visible in the photograph, the team were able to successfully identify the individual.”

Posted on April 19, 2018 at 6:51 AMView Comments

Sidebar photo of Bruce Schneier by Joe MacInnis.