Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/04/recovering_smar.html
Yet another side-channel attack on smartphones: “Hearing your touch: A new acoustic side channel on smartphones,” by Ilia Shumailov, Laurent Simon, Jeff Yan, and Ross Anderson.
Abstract: We present the first acoustic side-channel attack that recovers what users type on the virtual keyboard of their touch-screen smartphone or tablet. When a user taps the screen with a finger, the tap generates a sound wave that propagates on the screen surface and in the air. We found the device’s microphone(s) can recover this wave and “hear” the finger’s touch, and the wave’s distortions are characteristic of the tap’s location on the screen. Hence, by recording audio through the built-in microphone(s), a malicious app can infer text as the user enters it on their device. We evaluate the effectiveness of the attack with 45 participants in a real-world environment on an Android tablet and an Android smartphone. For the tablet, we recover 61% of 200 4-digit PIN-codes within 20 attempts, even if the model is not trained with the victim’s data. For the smartphone, we recover 9 words of size 7-13 letters with 50 attempts in a common side-channel attack benchmark. Our results suggest that it not always sufficient to rely on isolation mechanisms such as TrustZone to protect user input. We propose and discuss hardware, operating-system and application-level mechanisms to block this attack more effectively. Mobile devices may need a richer capability model, a more user-friendly notification system for sensor usage and a more thorough evaluation of the information leaked by the underlying hardware.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/02/usb_cable_with_.html
It’s only a prototype, but this USB cable has an embedded Wi-Fi controller. Whoever controls that Wi-Fi connection can remotely execute commands on the attached computer.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/09/using_a_smartph.html
It’s amazing that this is even possible: “SonarSnoop: Active Acoustic Side-Channel Attacks“:
Abstract: We report the first active acoustic side-channel attack. Speakers are used to emit human inaudible acoustic signals and the echo is recorded via microphones, turning the acoustic system of a smart phone into a sonar system. The echo signal can be used to profile user interaction with the device. For example, a victim’s finger movements can be inferred to steal Android phone unlock patterns. In our empirical study, the number of candidate unlock patterns that an attacker must try to authenticate herself to a Samsung S4 Android phone can be reduced by up to 70% using this novel acoustic side-channel. Our approach can be easily applied to other application scenarios and device types. Overall, our work highlights a new family of security threats.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/08/eavesdropping_o_7.html
Yet another way of eavesdropping on someone’s computer activity: using the webcam microphone to “listen” to the computer’s screen.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/08/speculation_att.html
Another speculative-execution attack against Intel’s SGX.
At a high level, SGX is a new feature in modern Intel CPUs which allows computers to protect users’ data even if the entire system falls under the attacker’s control. While it was previously believed that SGX is resilient to speculative execution attacks (such as Meltdown and Spectre), Foreshadow demonstrates how speculative execution can be exploited for reading the contents of SGX-protected memory as well as extracting the machine’s private attestation key. Making things worse, due to SGX’s privacy features, an attestation report cannot be linked to the identity of its signer. Thus, it only takes a single compromised SGX machine to erode trust in the entire SGX ecosystem.
The details of the Foreshadow attack are a little more complicated than those of Meltdown. In Meltdown, the attempt to perform an illegal read of kernel memory triggers the page fault mechanism (by which the processor and operating system cooperate to determine which bit of physical memory a memory access corresponds to, or they crash the program if there’s no such mapping). Attempts to read SGX data from outside an enclave receive special handling by the processor: reads always return a specific value (-1), and writes are ignored completely. The special handling is called “abort page semantics” and should be enough to prevent speculative reads from being able to learn anything.
However, the Foreshadow researchers found a way to bypass the abort page semantics. The data structures used to control the mapping of virtual-memory addresses to physical addresses include a flag to say whether a piece of memory is present (loaded into RAM somewhere) or not. If memory is marked as not being present at all, the processor stops performing any further permissions checks and immediately triggers the page fault mechanism: this means that the abort page mechanics aren’t used. It turns out that applications can mark memory, including enclave memory, as not being present by removing all permissions (read, write, execute) from that memory.
EDITED TO ADD: Intel has responded:
L1 Terminal Fault is addressed by microcode updates released earlier this year, coupled with corresponding updates to operating system and hypervisor software that are available starting today. We’ve provided more information on our web site and continue to encourage everyone to keep their systems up-to-date, as it’s one of the best ways to stay protected.
I think this is a comprehensive link to everything the company is saying about the vulnerability.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/07/recovering_keyb.html
Researchers at the University of California, Irvine, are able to recover user passwords by way of thermal imaging. The tech is pretty straightforward, but it’s interesting to think about the types of scenarios in which it might be pulled off.
Abstract: As a warm-blooded mammalian species, we humans routinely leave thermal residues on various objects with which we come in contact. This includes common input devices, such as keyboards, that are used for entering (among other things) secret information, such as passwords and PINs. Although thermal residue dissipates over time, there is always a certain time window during which thermal energy readings can be harvested from input devices to recover recently entered, and potentially sensitive, information.
To-date, there has been no systematic investigation of thermal profiles of keyboards, and thus no efforts have been made to secure them. This serves as our main motivation for constructing a means for password harvesting from keyboard thermal emanations. Specifically, we introduce Thermanator, a new post factum insider attack based on heat transfer caused by a user typing a password on a typical external keyboard. We conduct and describe a user study that collected thermal residues from 30 users entering 10 unique passwords (both weak and strong) on 4 popular commodity keyboards. Results show that entire sets of key-presses can be recovered by non-expert users as late as 30 seconds after initial password entry, while partial sets can be recovered as late as 1 minute after entry. Furthermore, we find that Hunt-and-Peck typists are particularly vulnerable. We also discuss some Thermanator mitigation strategies.
The main take-away of this work is three-fold: (1) using external keyboards to enter (already much-maligned) passwords is even less secure than previously recognized, (2) post factum (planned or impromptu) thermal imaging attacks are realistic, and finally (3) perhaps it is time to either stop using keyboards for password entry, or abandon passwords altogether.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/05/another_spectre.html
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.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/03/another_branch_.html
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.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/02/jumping_air_gap_2.html
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.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/01/spectre_and_mel.html
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.
EDITED TO ADD (1/5): Another good technical description. And how the exploits work through browsers. A rundown of what vendors are doing. Nicholas Weaver on its effects on individual computers.
EDITED TO ADD (1/7): xkcd.
EDITED TO ADD (1/10): Another good technical description.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/04/stealing_browsi.html
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).
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/04/covert_channel_.html
Researchers build a covert channel between two virtual machines using a shared cache.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/03/jumping_air_gap_1.html
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.
EDITED TO ADD (3/7): Here’s a 2002 paper on this idea.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/01/twofish_power_a.html
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.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2016/11/using_wi-fi_to_.html
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%.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2016/11/ultrasonic_hack.html
Ad networks are surreptitiously using ultrasonic communications to jump from device to device. It should come as no surprise that this communications channel can be used to hack devices as well.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2016/11/self-propagatin.html
This is exactly the sort of Internet-of-Things attack that has me worried:
“IoT Goes Nuclear: Creating a ZigBee Chain Reaction” by Eyal Ronen, Colin OFlynn, Adi Shamir and Achi-Or Weingarten.
Abstract: Within the next few years, billions of IoT devices will densely populate our cities. In this paper we describe a new type of threat in which adjacent IoT devices will infect each other with a worm that will spread explosively over large areas in a kind of nuclear chain reaction, provided that the density of compatible IoT devices exceeds a certain critical mass. In particular, we developed and verified such an infection using the popular Philips Hue smart lamps as a platform. The worm spreads by jumping directly from one lamp to its neighbors, using only their built-in ZigBee wireless connectivity and their physical proximity. The attack can start by plugging in a single infected bulb anywhere in the city, and then catastrophically spread everywhere within minutes, enabling the attacker to turn all the city lights on or off, permanently brick them, or exploit them in a massive DDOS attack. To demonstrate the risks involved, we use results from percolation theory to estimate the critical mass of installed devices for a typical city such as Paris whose area is about 105 square kilometers: The chain reaction will fizzle if there are fewer than about 15,000 randomly located smart lights in the whole city, but will spread everywhere when the number exceeds this critical mass (which had almost certainly been surpassed already).
To make such an attack possible, we had to find a way to remotely yank already installed lamps from their current networks, and to perform over-the-air firmware updates. We overcame the first problem by discovering and exploiting a major bug in the implementation of the Touchlink part of the ZigBee Light Link protocol, which is supposed to stop such attempts with a proximity test. To solve the second problem, we developed a new version of a side channel attack to extract the global AES-CCM key that Philips uses to encrypt and authenticate new firmware. We used only readily available equipment costing a few hundred dollars, and managed to find this key without seeing any actual updates. This demonstrates once again how difficult it is to get security right even for a large company that uses standard cryptographic techniques to protect a major product.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2016/10/eavesdropping_o_6.html
Interesting research: “Don’t Skype & Type! Acoustic Eavesdropping in Voice-Over-IP“:
Abstract: Acoustic emanations of computer keyboards represent a serious privacy issue. As demonstrated in prior work, spectral and temporal properties of keystroke sounds might reveal what a user is typing. However, previous attacks assumed relatively strong adversary models that are not very practical in many real-world settings. Such strong models assume: (i) adversary’s physical proximity to the victim, (ii) precise profiling of the victim’s typing style and keyboard, and/or (iii) significant amount of victim’s typed information (and its corresponding sounds) available to the adversary.
In this paper, we investigate a new and practical keyboard acoustic eavesdropping attack, called Skype & Type (S&T), which is based on Voice-over-IP (VoIP). S&T relaxes prior strong adversary assumptions. Our work is motivated by the simple observation that people often engage in secondary activities (including typing) while participating in VoIP calls. VoIP software can acquire acoustic emanations of pressed keystrokes (which might include passwords and other sensitive information) and transmit them to others involved in the call. In fact, we show that very popular VoIP software (Skype) conveys enough audio information to reconstruct the victim’s input keystrokes typed on the remote keyboard. In particular, our results demonstrate
that, given some knowledge on the victim’s typing style and the keyboard, the attacker attains top-5 accuracy of 91:7% in guessing a random key pressed by the victim. (The accuracy goes down to still alarming 41:89% if the attacker is oblivious to both the typing style and the keyboard). Finally, we provide evidence that Skype & Type attack is robust to various VoIP issues (e.g., Internet bandwidth fluctuations and presence of voice over keystrokes), thus confirming feasibility of this attack.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2016/10/bypassing_intel.html
Researchers discover a clever attack that bypasses the address space layout randomization (ALSR) on Intel’s CPUs.
Here’s the paper. It discusses several possible mitigation techniques.
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2016/08/keystroke_recog.html
This is interesting research: “Keystroke Recognition Using WiFi Signals.” Basically, the user’s hand positions as they type distorts the Wi-Fi signal in predictable ways.
Abstract: Keystroke privacy is critical for ensuring the security of computer systems and the privacy of human users as what being typed could be passwords or privacy sensitive information. In this paper, we show for the first time that WiFi signals
can also be exploited to recognize keystrokes. The intuition is that while typing a certain key, the hands and fingers of a user move in a unique formation and direction and thus generate a unique pattern in the time-series of Channel State Information (CSI) values, which we call CSI-waveform for that key. In this paper, we propose a WiFi signal based keystroke recognition system called WiKey. WiKey consists of two Commercial Off-The-Shelf (COTS) WiFi devices, a sender (such as a router) and a receiver (such as a laptop). The sender continuously emits signals and the receiver continuously receives signals. When a human subject types on a keyboard, WiKey recognizes the typed keys based on how the CSI values at the WiFi signal receiver end. We implemented the WiKey system using a TP-Link TL-WR1043ND WiFi router and a Lenovo X200 laptop. WiKey achieves more than 97.5% detection rate for detecting the keystroke and 96.4% recognition accuracy for classifying single keys. In real-world experiments, WiKey can recognize keystrokes in a continuously typed sentence with an accuracy of 93.5%.