In a Cross-Origin State Inference (COSI) attack, an attacker convinces a victim into visiting an attack web page, which leverages the cross-origin interaction features of the victim's web browser to infer the victim's state at a target web site. Multiple instances of COSI attacks have been found in the past under different names such as login detection or access detection attacks. But, those attacks only consider two states (e.g., logged in or not) and focus on a specific browser leak method (or XS-Leak). This work shows that mounting more complex COSI attacks such as deanonymizing the owner of an account, determining if the victim owns sensitive content, and determining the victim's account type often requires considering more than two states. Furthermore, robust attacks require supporting a variety of browsers since the victim's browser cannot be predicted apriori. To address these issues, we present a novel approach to identify and build complex COSI attacks that differentiate more than two states and support multiple browsers by combining multiple attack vectors, possibly using different XS-Leaks. To enable our approach, we introduce the concept of a COSI attack class. We propose two novel techniques to generalize existing COSI attack instances into COSI attack classes and to discover new COSI attack classes. We systematically apply our techniques to existing attacks, identifying 40 COSI attack classes. As part of this process, we discover a novel XS-Leak based on window.postMessage. We implement our approach into Basta-COSI, a tool to find COSI attacks in a target web site. We apply Basta-COSI to test four stand-alone web applications and 58 popular web sites, finding COSI attacks against each of them.
Recent transient-execution attacks, such as RIDL, Fallout, and ZombieLoad, demonstrated that attackers can leak information while it transits through microarchitectural buffers. Named Microarchitectural Data Sampling (MDS) by Intel, these attacks are likened to "drinking from the firehose", as the attacker has little control over what data is observed and from what origin. Unable to prevent the buffers from leaking, Intel issued countermeasures via microcode updates that overwrite the buffers when the CPU changes security domains. In this work we present CacheOut, a new microarchitectural atta…
This presentation focuses on differences between quantum computing and quantum cryptography. Both are discussed related to classical computer systems in terms of vulnerability. Research concerning quantum cryptography is analyzed in terms of work done by the University of Cambridge in partnership with a division of Toshiba, and also attacks demonstrated by Swedish researchers against QKD of energy-time entangled systems. Quantum computing is covered in terms of classical cryptography related to weaknesses presented by Shor's algorithm. Previous classical vulnerabilities also discussed were con…
Meltdown and Spectre exploit microarchitectural changes the CPU makes during transient out-of-order execution. Using side-channel techniques, these attacks enable leaking arbitrary data from memory. As state-of-the-art software mitigations for Meltdown may incur significant performance overheads, they are only seen as a temporary solution. Thus, software mitigations are disabled on more recent processors, which are not susceptible to Meltdown anymore. In this paper, we show that Meltdown-like attacks are still possible on recent CPUs which are not vulnerable to the original Meltdown attack. We…
Transient execution attacks utilize micro-architectural covert channels to leak secrets that should not have been accessible during logical program execution. Commonly used micro-architectural covert channels are those that leave lasting footprints in the microarchitectural state, for example, a cache state change, from which the secret is recovered after the transient execution is completed. In this paper, we present SpectreRewind, a new approach to create contention based covert channels for transient execution attacks. In our approach, a covert channel is established by issuing the necessar…
We introduce a new timing side-channel attack on Intel CPU processors. Our Frontal attack exploits timing differences that arise from how the CPU frontend fetches and processes instructions while being interrupted. In particular, we observe that in modern Intel CPUs, some instructions' execution times will depend on which operations precede and succeed them, and on their virtual addresses. Unlike previous attacks that could only profile branches if they contained different code or had known branch targets, the Frontal attack allows the adversary to distinguish between instruction-wise identica…
In this work, we develop efficient disruptions of black-box image translation deepfake generation systems. We are the first to demonstrate black-box deepfake generation disruption by presenting image translation formulations of attacks initially proposed for classification models. Nevertheless, a naive adaptation of classification black-box attacks results in a prohibitive number of queries for image translation systems in the real-world. We present a frustratingly simple yet highly effective algorithm Leaking Universal Perturbations (LUP), that significantly reduces the number of queries need…
Modern processor designs use a variety of microarchitectural methods to achieve high performance. Unfortunately, new side-channels have often been uncovered that exploit these enhanced designs. One area that has received little attention from a security perspective is the processor's hard-ware prefetcher, a critical component used to mitigate DRAM latency in today's systems. Prefetchers, like branch predictors, hold critical state related to the execution of the application, and have the potential to leak secret information. But up to now, there has not been a demonstration of a generic prefet…
University of St. Gallen (HSG)（圣加仑大学（HSG））；German Research Center for Artificial Intelligence (DFKI)（德国人工智能研究中心（DFKI））
Nowadays, organizations collect vast quantities of sensitive information in `Enterprise Resource Planning' (ERP) systems, such as accounting relevant transactions, customer master data, or strategic sales price information. The leakage of such information poses a severe threat for companies as the number of incidents and the reputational damage to those experiencing them continue to increase. At the same time, discoveries in deep learning research revealed that machine learning models could be maliciously misused to create new attack vectors. Understanding the nature of such attacks becomes in…
Using the keyboard LEDs to send data optically was proposed in 2002 by Loughry and Umphress [1] (Appendix A). In this paper we extensively explore this threat in the context of a modern cyber-attack with current hardware and optical equipment. In this type of attack, an advanced persistent threat (APT) uses the keyboard LEDs (Caps-Lock, Num-Lock and Scroll-Lock) to encode information and exfiltrate data from airgapped computers optically. Notably, this exfiltration channel is not monitored by existing data leakage prevention (DLP) systems. We examine this attack and its boundaries for today's …
Recently, the Dragonblood attacks have attracted new interests on the security of WPA-3 implementation and in particular on the Dragonfly code deployed on many open-source libraries. One attack concerns the protection of users passwords during authentication. In the Password Authentication Key Exchange (PAKE) protocol called Dragonfly, the secret, namely the password, is mapped to an elliptic curve point. This operation is sensitive, as it involves the secret password, and therefore its resistance against side-channel attacks is of utmost importance. Following the initial disclosure of Dragonb…
We consider problems where $n$ people are communicating and a random subset of them is trying to leak information, without making it clear who are leaking the information. We introduce a measure of suspicion, and show that the amount of leaked information will always be bounded by the expected increase in suspicion, and that this bound is tight. We ask the question: Suppose a large number of people have some information they want to leak, but they want to ensure that after the communication, an observer will assign probability at most $c$ to the events that each of them is trying to leak the i…
Transient execution attacks that exploit speculation have raised significant concerns in computer systems. Typically, branch predictors are leveraged to trigger mis-speculation in transient execution attacks. In this work, we demonstrate a new class of speculation-based attack that targets branch prediction unit (BPU). We find that speculative resolution of conditional branches (i.e., in nested speculation) alter the states of pattern history table (PHT) in modern processors, which are not restored after the corresponding branches are later squashed. Such characteristic allows attackers to exp…
Stop Tracking Me! Proactive Defense Against Attribute Inference Attack in LLMs
School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院）；NLPR & MAIS, Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）
