Entries Tagged "spoofing"

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Finding the Location of Telegram Users

Security researcher Ahmed Hassan has shown that spoofing the Android’s “People Nearby” feature allows him to pinpoint the physical location of Telegram users:

Using readily available software and a rooted Android device, he’s able to spoof the location his device reports to Telegram servers. By using just three different locations and measuring the corresponding distance reported by People Nearby, he is able to pinpoint a user’s precise location.


A proof-of-concept video the researcher sent to Telegram showed how he could discern the address of a People Nearby user when he used a free GPS spoofing app to make his phone report just three different locations. He then drew a circle around each of the three locations with a radius of the distance reported by Telegram. The user’s precise location was where all three intersected.


Fixing the problem — or at least making it much harder to exploit it — wouldn’t be hard from a technical perspective. Rounding locations to the nearest mile and adding some random bits generally suffices. When the Tinder app had a similar disclosure vulnerability, developers used this kind of technique to fix it.

Posted on January 14, 2021 at 6:08 AMView Comments

Split-Second Phantom Images Fool Autopilots

Researchers are tricking autopilots by inserting split-second images into roadside billboards.

Researchers at Israel’s Ben Gurion University of the Negev … previously revealed that they could use split-second light projections on roads to successfully trick Tesla’s driver-assistance systems into automatically stopping without warning when its camera sees spoofed images of road signs or pedestrians. In new research, they’ve found they can pull off the same trick with just a few frames of a road sign injected on a billboard’s video. And they warn that if hackers hijacked an internet-connected billboard to carry out the trick, it could be used to cause traffic jams or even road accidents while leaving little evidence behind.


In this latest set of experiments, the researchers injected frames of a phantom stop sign on digital billboards, simulating what they describe as a scenario in which someone hacked into a roadside billboard to alter its video. They also upgraded to Tesla’s most recent version of Autopilot known as HW3. They found that they could again trick a Tesla or cause the same Mobileye device to give the driver mistaken alerts with just a few frames of altered video.

The researchers found that an image that appeared for 0.42 seconds would reliably trick the Tesla, while one that appeared for just an eighth of a second would fool the Mobileye device. They also experimented with finding spots in a video frame that would attract the least notice from a human eye, going so far as to develop their own algorithm for identifying key blocks of pixels in an image so that a half-second phantom road sign could be slipped into the “uninteresting” portions.

The paper:

Abstract: In this paper, we investigate “split-second phantom attacks,” a scientific gap that causes two commercial advanced driver-assistance systems (ADASs), Telsa Model X (HW 2.5 and HW 3) and Mobileye 630, to treat a depthless object that appears for a few milliseconds as a real obstacle/object. We discuss the challenge that split-second phantom attacks create for ADASs. We demonstrate how attackers can apply split-second phantom attacks remotely by embedding phantom road signs into an advertisement presented on a digital billboard which causes Tesla’s autopilot to suddenly stop the car in the middle of a road and Mobileye 630 to issue false notifications. We also demonstrate how attackers can use a projector in order to cause Tesla’s autopilot to apply the brakes in response to a phantom of a pedestrian that was projected on the road and Mobileye 630 to issue false notifications in response to a projected road sign. To counter this threat, we propose a countermeasure which can determine whether a detected object is a phantom or real using just the camera sensor. The countermeasure (GhostBusters) uses a “committee of experts” approach and combines the results obtained from four lightweight deep convolutional neural networks that assess the authenticity of an object based on the object’s light, context, surface, and depth. We demonstrate our countermeasure’s effectiveness (it obtains a TPR of 0.994 with an FPR of zero) and test its robustness to adversarial machine learning attacks.

Posted on October 19, 2020 at 6:28 AMView Comments

Security Vulnerability in Internet-Connected Construction Cranes

This seems bad:

The F25 software was found to contain a capture replay vulnerability — basically an attacker would be able to eavesdrop on radio transmissions between the crane and the controller, and then send their own spoofed commands over the air to seize control of the crane.

“These devices use fixed codes that are reproducible by sniffing and re-transmission,” US-CERT explained.

“This can lead to unauthorized replay of a command, spoofing of an arbitrary message, or keeping the controlled load in a permanent ‘stop’ state.”

Here’s the CERT advisory.

Posted on October 29, 2018 at 6:18 AMView Comments

Detecting Phishing Sites with Machine Learning

Really interesting article:

A trained eye (or even a not-so-trained one) can discern when something phishy is going on with a domain or subdomain name. There are search tools, such as Censys.io, that allow humans to specifically search through the massive pile of certificate log entries for sites that spoof certain brands or functions common to identity-processing sites. But it’s not something humans can do in real time very well — which is where machine learning steps in.

StreamingPhish and the other tools apply a set of rules against the names within certificate log entries. In StreamingPhish’s case, these rules are the result of guided learning — a corpus of known good and bad domain names is processed and turned into a “classifier,” which (based on my anecdotal experience) can then fairly reliably identify potentially evil websites.

Posted on August 9, 2018 at 6:17 AMView Comments

Impersonating iOS Password Prompts

This is an interesting security vulnerability: because it is so easy to impersonate iOS password prompts, a malicious app can steal your password just by asking.

Why does this work?

iOS asks the user for their iTunes password for many reasons, the most common ones are recently installed iOS operating system updates, or iOS apps that are stuck during installation.

As a result, users are trained to just enter their Apple ID password whenever iOS prompts you to do so. However, those popups are not only shown on the lock screen, and the home screen, but also inside random apps, e.g. when they want to access iCloud, GameCenter or In-App-Purchases.

This could easily be abused by any app, just by showing an UIAlertController, that looks exactly like the system dialog.

Even users who know a lot about technology have a hard time detecting that those alerts are phishing attacks.

The essay proposes some solutions, but I’m not sure they’ll work. We’re all trained to trust our computers and the applications running on them.

Posted on October 12, 2017 at 6:43 AMView Comments

GPS Spoofing Attacks

Wired has a story about a possible GPS spoofing attack by Russia:

After trawling through AIS data from recent years, evidence of spoofing becomes clear. Goward says GPS data has placed ships at three different airports and there have been other interesting anomalies. “We would find very large oil tankers who could travel at the maximum speed at 15 knots,” says Goward, who was formerly director for Marine Transportation Systems at the US Coast Guard. “Their AIS, which is powered by GPS, would be saying they had sped up to 60 to 65 knots for an hour and then suddenly stopped. They had done that several times.”

All of the evidence from the Black Sea points towards a co-ordinated attempt to disrupt GPS. A recently published report from NRK found that 24 vessels appeared at Gelendzhik airport around the same time as the Atria. When contacted, a US Coast Guard representative refused to comment on the incident, saying any GPS disruption that warranted further investigation would be passed onto the Department of Defence.

“It looks like a sophisticated attack, by somebody who knew what they were doing and were just testing the system,” Bonenberg says. Humphreys told NRK it “strongly” looks like a spoofing incident. Fire Eye’s Brubaker, agreed, saying the activity looked intentional. Goward is also confident that GPS were purposely disrupted. “What this case shows us is there are entities out there that are willing and eager to disrupt satellite navigation systems for whatever reason and they can do it over a fairly large area and in a sophisticated way,” he says. “They’re not just broadcasting a stronger signal and denying service this is worse they’re providing hazardously misleading information.”

Posted on September 25, 2017 at 8:23 AMView Comments

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Sidebar photo of Bruce Schneier by Joe MacInnis.