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sidechannelattacks

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Another Spectre-Like CPU Vulnerability

Google and Microsoft researchers have disclosed another Spectre-like CPU side-channel vulnerability, called “Speculative Store Bypass.” Like the others, the fix will slow the CPU down.

The German tech site Heise reports that more are coming.

I’m not surprised. Writing about Spectre and Meltdown in January, I predicted that we’ll be seeing a lot more of these sorts of vulnerabilities.

Spectre and Meltdown are pretty catastrophic vulnerabilities, but they only affect the confidentiality of data. Now that they — and the research into the Intel ME vulnerability — have shown researchers where to look, more is coming — and what they’ll find will be worse than either Spectre or Meltdown.

I still predict that we’ll be seeing lots more of these in the coming months and years, as we learn more about this class of vulnerabilities.

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Another Branch Prediction Attack

When Spectre and Meltdown were first announced earlier this year, pretty much everyone predicted that there would be many more attacks targeting branch prediction in microprocessors. Here’s another one:

In the new attack, an attacker primes the PHT and running branch instructions so that the PHT will always assume a particular branch is taken or not taken. The victim code then runs and makes a branch, which is potentially disturbing the PHT. The attacker then runs more branch instructions of its own to detect that disturbance to the PHT; the attacker knows that some branches should be predicted in a particular direction and tests to see if the victim’s code has changed that prediction.

The researchers looked only at Intel processors, using the attacks to leak information protected using Intel’s SGX (Software Guard Extensions), a feature found on certain chips to carve out small sections of encrypted code and data such that even the operating system (or virtualization software) cannot access it. They also described ways the attack could be used against address space layout randomization and to infer data in encryption and image libraries.

Research paper.

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Jumping Air Gaps

Nice profile of Mordechai Guri, who researches a variety of clever ways to steal data over air-gapped computers.

Guri and his fellow Ben-Gurion researchers have shown, for instance, that it’s possible to trick a fully offline computer into leaking data to another nearby device via the noise its internal fan generates, by changing air temperatures in patterns that the receiving computer can detect with thermal sensors, or even by blinking out a stream of information from a computer hard drive LED to the camera on a quadcopter drone hovering outside a nearby window. In new research published today, the Ben-Gurion team has even shown that they can pull data off a computer protected by not only an air gap, but also a Faraday cage designed to block all radio signals.

Here’s a page with all the research results.

BoingBoing post.

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Spectre and Meltdown Attacks

After a week or so of rumors, everyone is now reporting about the Spectre and Meltdown attacks against pretty much every modern processor out there.

These are side-channel attacks where one process can spy on other processes. They affect computers where an untrusted browser window can execute code, phones that have multiple apps running at the same time, and cloud computing networks that run lots of different processes at once. Fixing them either requires a patch that results in a major performance hit, or is impossible and requires a re-architecture of conditional execution in future CPU chips.

I’ll be writing something for publication over the next few days. This post is basically just a link repository.

EDITED TO ADD: Good technical explanation. And a Slashdot thread.

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Stealing Browsing History Using Your Phone’s Ambient Light Sensor

There has been a flurry of research into using the various sensors on your phone to steal data in surprising ways. Here’s another: using the phone’s ambient light sensor to detect what’s on the screen. It’s a proof of concept, but the paper’s general conclusions are correct:

There is a lesson here that designing specifications and systems from a privacy engineering perspective is a complex process: decisions about exposing sensitive APIs to the web without any protections should not be taken lightly. One danger is that specification authors and browser vendors will base decisions on overly general principles and research results which don’t apply to a particular new feature (similarly to how protections on gyroscope readings might not be sufficient for light sensor data).

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Jumping Air Gaps with Blinking Lights and Drones

Researchers have demonstrated how a malicious piece of software in an air-gapped computer can communicate with a nearby drone using a blinking LED on the computer.

I have mixed feelings about research like this. On the one hand, it’s pretty cool. On the other hand, there’s not really anything new or novel, and it’s kind of a movie-plot threat.

Research paper.

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Twofish Power Analysis Attack

New paper: “A Simple Power Analysis Attack on the Twofish Key Schedule.” This shouldn’t be a surprise; these attacks are devastating if you don’t take steps to mitigate them.

The general issue is if an attacker has physical control of the computer performing the encryption, it is very hard to secure the encryption inside the computer. I wrote a paper about this back in 1999.

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Using Wi-Fi to Detect Hand Motions and Steal Passwords

This is impressive research: “When CSI Meets Public WiFi: Inferring Your Mobile Phone Password via WiFi Signals“:

Abstract: In this study, we present WindTalker, a novel and practical keystroke inference framework that allows an attacker to infer the sensitive keystrokes on a mobile device through WiFi-based side-channel information. WindTalker is motivated from the observation that keystrokes on mobile devices will lead to different hand coverage and the finger motions, which will introduce a unique interference to the multi-path signals and can be reflected by the channel state information (CSI). The adversary can exploit the strong correlation between the CSI fluctuation and the keystrokes to infer the user’s number input. WindTalker presents a novel approach to collect the target’s CSI data by deploying a public WiFi hotspot. Compared with the previous keystroke inference approach, WindTalker neither deploys external devices close to the target device nor compromises the target device. Instead, it utilizes the public WiFi to collect user’s CSI data, which is easy-to-deploy and difficult-to-detect. In addition, it jointly analyzes the traffic and the CSI to launch the keystroke inference only for the sensitive period where password entering occurs. WindTalker can be launched without the requirement of visually seeing the smart phone user’s input process, backside motion, or installing any malware on the tablet. We implemented Windtalker on several mobile phones and performed a detailed case study to evaluate the practicality of the password inference towards Alipay, the largest mobile payment platform in the world. The evaluation results show that the attacker can recover the key with a high successful rate.

That “high successful rate” is 81.7%.

News article.

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