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Apple AirTags Are Being Used to Track People and Cars

This development suprises no one who has been paying attention:

Researchers now believe AirTags, which are equipped with Bluetooth technology, could be revealing a more widespread problem of tech-enabled tracking. They emit a digital signal that can be detected by devices running Apple’s mobile operating system. Those devices then report where an AirTag has last been seen. Unlike similar tracking products from competitors such as Tile, Apple added features to prevent abuse, including notifications like the one Ms. Estrada received and automatic beeping. (Tile plans to release a feature to prevent the tracking of people next year, a spokeswoman for that company said.)

[…]

A person who doesn’t own an iPhone might have a harder time detecting an unwanted AirTag. AirTags aren’t compatible with Android smartphones. Earlier this month, Apple released an Android app that can scan for AirTags — but you have to be vigilant enough to download it and proactively use it.

Apple declined to say if it was working with Google on technology that would allow Android phones to automatically detect its trackers.

People who said they have been tracked have called Apple’s safeguards insufficient. Ms. Estrada said she was notified four hours after her phone first noticed the rogue gadget. Others said it took days before they were made aware of an unknown AirTag. According to Apple, the timing of the alerts can vary depending on the iPhone’s operating system and location settings.

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Thieves Using AirTags to “Follow” Cars

From Ontario and not surprising:

Since September 2021, officers have investigated five incidents where suspects have placed small tracking devices on high-end vehicles so they can later locate and steal them. Brand name “air tags” are placed in out-of-sight areas of the target vehicles when they are parked in public places like malls or parking lots. Thieves then track the targeted vehicles to the victim’s residence, where they are stolen from the driveway.

Thieves typically use tools like screwdrivers to enter the vehicles through the driver or passenger door, while ensuring not to set off alarms. Once inside, an electronic device, typically used by mechanics to reprogram the factory setting, is connected to the onboard diagnostics port below the dashboard and programs the vehicle to accept a key the thieves have brought with them. Once the new key is programmed, the vehicle will start and the thieves drive it away.

I’m not sure if there’s anything that can be done:

When Apple first released AirTags earlier this year, concerns immediately sprung up about nefarious use cases for the covert trackers. Apple responded with a slew of anti-stalking measures, but those are more intended for keeping people safe than cars. An AirTag away from its owner will sound an alarm, letting anyone nearby know that it’s been left behind, but it can take up to 24 hours for that alarm to go off — more than enough time to nab a car in the dead of night.

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Tesla Remotely Hacked from a Drone

This is an impressive hack:

Security researchers Ralf-Philipp Weinmann of Kunnamon, Inc. and Benedikt Schmotzle of Comsecuris GmbH have found remote zero-click security vulnerabilities in an open-source software component (ConnMan) used in Tesla automobiles that allowed them to compromise parked cars and control their infotainment systems over WiFi. It would be possible for an attacker to unlock the doors and trunk, change seat positions, both steering and acceleration modes — in short, pretty much what a driver pressing various buttons on the console can do. This attack does not yield drive control of the car though.

That last sentence is important.

News article.

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Used Tesla Components Contain Personal Information

Used Tesla components, sold on eBay, still contain personal information, even after a factory reset.

This is a decades-old problem. It’s a problem with used hard drives. It’s a problem with used photocopiers and printers. It will be a problem with IoT devices. It’ll be a problem with everything, until we decide that data deletion is a priority.

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Attacking Driverless Cars with Projected Images

Interesting research — “Phantom Attacks Against Advanced Driving Assistance Systems“:

Abstract: The absence of deployed vehicular communication systems, which prevents the advanced driving assistance systems (ADASs) and autopilots of semi/fully autonomous cars to validate their virtual perception regarding the physical environment surrounding the car with a third party, has been exploited in various attacks suggested by researchers. Since the application of these attacks comes with a cost (exposure of the attacker’s identity), the delicate exposure vs. application balance has held, and attacks of this kind have not yet been encountered in the wild. In this paper, we investigate a new perceptual challenge that causes the ADASs and autopilots of semi/fully autonomous to consider depthless objects (phantoms) as real. We show how attackers can exploit this perceptual challenge to apply phantom attacks and change the abovementioned balance, without the need to physically approach the attack scene, by projecting a phantom via a drone equipped with a portable projector or by presenting a phantom on a hacked digital billboard that faces the Internet and is located near roads. We show that the car industry has not considered this type of attack by demonstrating the attack on today’s most advanced ADAS and autopilot technologies: Mobileye 630 PRO and the Tesla Model X, HW 2.5; our experiments show that when presented with various phantoms, a car’s ADAS or autopilot considers the phantoms as real objects, causing these systems to trigger the brakes, steer into the lane of oncoming traffic, and issue notifications about fake road signs. In order to mitigate this attack, we present a model that analyzes a detected object’s context, surface, and reflected light, which is capable of detecting phantoms with 0.99 AUC. Finally, we explain why the deployment of vehicular communication systems might reduce attackers’ opportunities to apply phantom attacks but won’t eliminate them.

The paper will be presented at CyberTech at the end of the month.

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NTSB Investigation of Fatal Driverless Car Accident

Autonomous systems are going to have to do much better than this.

The Uber car that hit and killed Elaine Herzberg in Tempe, Ariz., in March 2018 could not recognize all pedestrians, and was being driven by an operator likely distracted by streaming video, according to documents released by the U.S. National Transportation Safety Board (NTSB) this week.

But while the technical failures and omissions in Uber’s self-driving car program are shocking, the NTSB investigation also highlights safety failures that include the vehicle operator’s lapses, lax corporate governance of the project, and limited public oversight.

The details of what happened in the seconds before the collision are worth reading. They describe a cascading series of issues that led to the collision and the fatality.

As computers continue to become part of things, and affect the world in a direct physical manner, this kind of thing will become even more important.

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License Plate “NULL”

There was a DefCon talk by someone with the vanity plate “NULL.” The California system assigned him every ticket with no license plate: $12,000.

Although the initial $12,000-worth of fines were removed, the private company that administers the database didn’t fix the issue and new NULL tickets are still showing up.

The unanswered question is: now that he has a way to get parking fines removed, can he park anywhere for free?

And this isn’t the first time this sort of thing has happened. Wired has a roundup of people whose license places read things like “NOPLATE,” “NO TAG,” and “XXXXXXX.”

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Modifying a Tesla to Become a Surveillance Platform

From DefCon:

At the Defcon hacker conference today, security researcher Truman Kain debuted what he calls the Surveillance Detection Scout. The DIY computer fits into the middle console of a Tesla Model S or Model 3, plugs into its dashboard USB port, and turns the car’s built-in cameras­ — the same dash and rearview cameras providing a 360-degree view used for Tesla’s Autopilot and Sentry features­ — into a system that spots, tracks, and stores license plates and faces over time. The tool uses open source image recognition software to automatically put an alert on the Tesla’s display and the user’s phone if it repeatedly sees the same license plate. When the car is parked, it can track nearby faces to see which ones repeatedly appear. Kain says the intent is to offer a warning that someone might be preparing to steal the car, tamper with it, or break into the driver’s nearby home.

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Another Attack Against Driverless Cars

In this piece of research, attackers successfully attack a driverless car system — Renault Captur’s “Level 0” autopilot (Level 0 systems advise human drivers but do not directly operate cars) — by following them with drones that project images of fake road signs in 100ms bursts. The time is too short for human perception, but long enough to fool the autopilot’s sensors.

Boing Boing post.

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