Pub Date : 2023-05-01DOI: 10.1109/SP46215.2023.10179368
S. Gast, Jonas Juffinger, Martin Schwarzl, Gururaj Saileshwar, Andreas Kogler, Simone Franza, Markus Köstl, D. Gruss
Modern superscalar CPUs have multiple execution units that independently execute operations from the instruction stream. Previous work has shown that numerous side channels exist around these out-of-order execution pipelines, particularly for an attacker running on an SMT core.In this paper, we present the SQUIP attack, the first side-channel attack on scheduler queues, which are critical for deciding the schedule of instructions to be executed in superscalar CPUs. Scheduler queues have not been explored as a side channel so far, as Intel CPUs only have a single scheduler queue, and contention thereof would be virtually the same as contention of the reorder buffer. However, the Apple M1, AMD Zen 2, and Zen 3 microarchitectures have separate scheduler queues per execution unit. We first reverse-engineer the behavior of the scheduler queues on these CPUs and show that they can be primed and probed. The SQUIP attack observes the occupancy level from within the same hardware core and across SMT threads. We evaluate the performance of the SQUIP attack in a covert channel, exfiltrating 0.89 Mbit/s from a co-located virtual machine at an error rate below 0.8 %, and 2.70 Mbit/s from a co-located process at an error rate below 0.8 %. We then demonstrate the side channel on an mbedTLS RSA signature process in a co-located process and in a co-located virtual machine. Our attack recovers full RSA-4096 keys with only 50 500 traces and less than 5 to 18 bit errors on average. Finally, we discuss mitigations necessary, especially for Zen 2 and Zen 3 systems, to prevent our attacks.
{"title":"SQUIP: Exploiting the Scheduler Queue Contention Side Channel","authors":"S. Gast, Jonas Juffinger, Martin Schwarzl, Gururaj Saileshwar, Andreas Kogler, Simone Franza, Markus Köstl, D. Gruss","doi":"10.1109/SP46215.2023.10179368","DOIUrl":"https://doi.org/10.1109/SP46215.2023.10179368","url":null,"abstract":"Modern superscalar CPUs have multiple execution units that independently execute operations from the instruction stream. Previous work has shown that numerous side channels exist around these out-of-order execution pipelines, particularly for an attacker running on an SMT core.In this paper, we present the SQUIP attack, the first side-channel attack on scheduler queues, which are critical for deciding the schedule of instructions to be executed in superscalar CPUs. Scheduler queues have not been explored as a side channel so far, as Intel CPUs only have a single scheduler queue, and contention thereof would be virtually the same as contention of the reorder buffer. However, the Apple M1, AMD Zen 2, and Zen 3 microarchitectures have separate scheduler queues per execution unit. We first reverse-engineer the behavior of the scheduler queues on these CPUs and show that they can be primed and probed. The SQUIP attack observes the occupancy level from within the same hardware core and across SMT threads. We evaluate the performance of the SQUIP attack in a covert channel, exfiltrating 0.89 Mbit/s from a co-located virtual machine at an error rate below 0.8 %, and 2.70 Mbit/s from a co-located process at an error rate below 0.8 %. We then demonstrate the side channel on an mbedTLS RSA signature process in a co-located process and in a co-located virtual machine. Our attack recovers full RSA-4096 keys with only 50 500 traces and less than 5 to 18 bit errors on average. Finally, we discuss mitigations necessary, especially for Zen 2 and Zen 3 systems, to prevent our attacks.","PeriodicalId":439989,"journal":{"name":"2023 IEEE Symposium on Security and Privacy (SP)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115399455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.1109/SP46215.2023.10179398
Dae R. Jeong, Byoungyoung Lee, I. Shin, Youngjin Kwon
Discovering kernel concurrency bugs through fuzzing is challenging. Identifying kernel concurrency bugs, as opposed to non-concurrency bugs, necessitates an analysis of possible interleavings between two or more threads. However, because the search space of thread interleaving is vast, it is impractical to investigate all conceivable thread interleavings. To explore the vast search space, most previous approaches perform random or simple heuristic searches without having coverage for thread interleaving or with an insufficient form of coverage. As a result, they either conduct wasteful searches with redundant executions or overlook concurrent bugs that their coverage cannot address.To overcome such limitations, we propose SegFuzz, a fuzzing framework for kernel concurrency bugs. When exploring the search space of thread interleavings, SegFuzz decomposes an entire thread interleaving into a set of segments, each of which represents an interleaving of the small number of instructions, and utilizes individual segments as interleaving coverage, called interleaving segment coverage. When searching for thread interleavings, SegFuzz mutates interleavings in explored interleaving segments to construct new thread interleavings that have not yet been explored. With SegFuzz, we discover new 21 concurrency bugs in Linux kernels, and demonstrate the efficiency of SegFuzz by showing that SegFuzz can identify known bugs on average 4.1 times quickly than the state-of-the-art approaches.
{"title":"SegFuzz: Segmentizing Thread Interleaving to Discover Kernel Concurrency Bugs through Fuzzing","authors":"Dae R. Jeong, Byoungyoung Lee, I. Shin, Youngjin Kwon","doi":"10.1109/SP46215.2023.10179398","DOIUrl":"https://doi.org/10.1109/SP46215.2023.10179398","url":null,"abstract":"Discovering kernel concurrency bugs through fuzzing is challenging. Identifying kernel concurrency bugs, as opposed to non-concurrency bugs, necessitates an analysis of possible interleavings between two or more threads. However, because the search space of thread interleaving is vast, it is impractical to investigate all conceivable thread interleavings. To explore the vast search space, most previous approaches perform random or simple heuristic searches without having coverage for thread interleaving or with an insufficient form of coverage. As a result, they either conduct wasteful searches with redundant executions or overlook concurrent bugs that their coverage cannot address.To overcome such limitations, we propose SegFuzz, a fuzzing framework for kernel concurrency bugs. When exploring the search space of thread interleavings, SegFuzz decomposes an entire thread interleaving into a set of segments, each of which represents an interleaving of the small number of instructions, and utilizes individual segments as interleaving coverage, called interleaving segment coverage. When searching for thread interleavings, SegFuzz mutates interleavings in explored interleaving segments to construct new thread interleavings that have not yet been explored. With SegFuzz, we discover new 21 concurrency bugs in Linux kernels, and demonstrate the efficiency of SegFuzz by showing that SegFuzz can identify known bugs on average 4.1 times quickly than the state-of-the-art approaches.","PeriodicalId":439989,"journal":{"name":"2023 IEEE Symposium on Security and Privacy (SP)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114870258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.1109/SP46215.2023.10179358
Tyler Tucker, Hunter Searle, Kevin R. B. Butler, Patrick Traynor
Bluetooth is overwhelmingly the protocol of choice for personal area networking, and the Bluetooth Classic standard has been in continuous use for over 20 years. Bluetooth devices make themselves Discoverable to communicate, but best practice to protect privacy is to ensure that devices remain in Non-Discoverable mode. This paper demonstrates the futility of protecting devices by making them Non-Discoverable. We introduce the Blue’s Clues attack, which presents the first direct, non-disruptive approach to fully extracting the permanent, unique Bluetooth MAC identifier from targeted devices in Non-Discoverable mode. We also demonstrate that we can fully characterize device capabilities and retrieve identifiers, some of which we discover often contain identifying information about the device owner. We demonstrate Blue’s Clues using a software-defined radio and mounting the attack over the air against both our own devices and, with institutional approval, throughout a public building. We find that a wide variety of Bluetooth devices can be uniquely identified in less than 10 seconds on average, with affected devices ranging from smartphones and headphones to gas pump skimmers and nanny-cams, spanning all versions of the Bluetooth Classic standard. While we provide potential mitigation against attacks, Blue’s Clues forces a reassessment of over 20 years of best practices for protecting devices against discovery.
{"title":"Blue’s Clues: Practical Discovery of Non-Discoverable Bluetooth Devices","authors":"Tyler Tucker, Hunter Searle, Kevin R. B. Butler, Patrick Traynor","doi":"10.1109/SP46215.2023.10179358","DOIUrl":"https://doi.org/10.1109/SP46215.2023.10179358","url":null,"abstract":"Bluetooth is overwhelmingly the protocol of choice for personal area networking, and the Bluetooth Classic standard has been in continuous use for over 20 years. Bluetooth devices make themselves Discoverable to communicate, but best practice to protect privacy is to ensure that devices remain in Non-Discoverable mode. This paper demonstrates the futility of protecting devices by making them Non-Discoverable. We introduce the Blue’s Clues attack, which presents the first direct, non-disruptive approach to fully extracting the permanent, unique Bluetooth MAC identifier from targeted devices in Non-Discoverable mode. We also demonstrate that we can fully characterize device capabilities and retrieve identifiers, some of which we discover often contain identifying information about the device owner. We demonstrate Blue’s Clues using a software-defined radio and mounting the attack over the air against both our own devices and, with institutional approval, throughout a public building. We find that a wide variety of Bluetooth devices can be uniquely identified in less than 10 seconds on average, with affected devices ranging from smartphones and headphones to gas pump skimmers and nanny-cams, spanning all versions of the Bluetooth Classic standard. While we provide potential mitigation against attacks, Blue’s Clues forces a reassessment of over 20 years of best practices for protecting devices against discovery.","PeriodicalId":439989,"journal":{"name":"2023 IEEE Symposium on Security and Privacy (SP)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125420874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.1109/SP46215.2023.10179456
Muhammad Saad, David A. Mohaisen
The biased distribution of cryptocurrency nodes across Autonomous Systems (ASes) increases the risk of spatial partitioning attacks, allowing an adversary to isolate nodes by hijacking AS prefixes. Prior works on spatial partitioning attacks have mainly focused on the Bitcoin network, showing that the prominent cryptocurrency network can be paralyzed by disrupting the physical topology through BGP hijacks.Despite the persisting threat of BGP hijacks, Bitcoin and other cryptocurrencies have not been frequently targeted, likely due to their shielded overlay topology, which limits the exposure of physical network anomalies. In this paper, we present a new perspective by examining the security of cryptocurrency networks, considering shared network resources (network interdependence). We conduct measurements extending beyond the Bitcoin network and analyze commonalities in Bitcoin, Ethereum, and Ripple node hosting patterns. We observe that all three networks are highly centralized, predominantly sharing the common ASes. We also note that among the three cryptocurrencies, Ripple does not shield its overlay topology, which can be exploited to learn about the physical network anomalies. The observed network anomalies present practical attack strategies that can be launched to target all three cryptocurrencies simultaneously. 1 We supplement our analysis by surveying recent BGP attacks on high-profile ASes and recognizing a need for application-level countermeasures. We propose attack countermeasures that reduce the risk of spatial partitioning, notwithstanding the increasing centralization of nodes and network interdependence.
{"title":"Three Birds with One Stone: Efficient Partitioning Attacks on Interdependent Cryptocurrency Networks","authors":"Muhammad Saad, David A. Mohaisen","doi":"10.1109/SP46215.2023.10179456","DOIUrl":"https://doi.org/10.1109/SP46215.2023.10179456","url":null,"abstract":"The biased distribution of cryptocurrency nodes across Autonomous Systems (ASes) increases the risk of spatial partitioning attacks, allowing an adversary to isolate nodes by hijacking AS prefixes. Prior works on spatial partitioning attacks have mainly focused on the Bitcoin network, showing that the prominent cryptocurrency network can be paralyzed by disrupting the physical topology through BGP hijacks.Despite the persisting threat of BGP hijacks, Bitcoin and other cryptocurrencies have not been frequently targeted, likely due to their shielded overlay topology, which limits the exposure of physical network anomalies. In this paper, we present a new perspective by examining the security of cryptocurrency networks, considering shared network resources (network interdependence). We conduct measurements extending beyond the Bitcoin network and analyze commonalities in Bitcoin, Ethereum, and Ripple node hosting patterns. We observe that all three networks are highly centralized, predominantly sharing the common ASes. We also note that among the three cryptocurrencies, Ripple does not shield its overlay topology, which can be exploited to learn about the physical network anomalies. The observed network anomalies present practical attack strategies that can be launched to target all three cryptocurrencies simultaneously. 1 We supplement our analysis by surveying recent BGP attacks on high-profile ASes and recognizing a need for application-level countermeasures. We propose attack countermeasures that reduce the risk of spatial partitioning, notwithstanding the increasing centralization of nodes and network interdependence.","PeriodicalId":439989,"journal":{"name":"2023 IEEE Symposium on Security and Privacy (SP)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125778794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.1109/SP46215.2023.10179481
Sijun Tan, Weikeng Chen, Ryan Deng, R. A. Popa
Systems with distributed trust have attracted growing research attention and seen increasing industry adoptions. In these systems, critical secrets are distributed across N servers, and computations are performed privately using secure multi-party computation (SMPC). Authentication for these distributed-trust systems faces two challenges. The first challenge is ease-of-use. Namely, how can an authentication protocol maintain its user experience without sacrificing security? To avoid a central point of attack, a client needs to authenticate to each server separately. However, this would require the client to authenticate N times for each authentication factor, which greatly hampers usability. The second challenge is privacy, as the client’s sensitive profiles are now exposed to all N servers under different trust domains, which creates N times the attack surface for the profile data.We present MPCAuth, a multi-factor authentication system for distributed-trust applications that address both challenges. Our system enables a client to authenticate to N servers independently with the work of only one authentication. In addition, our system is profile hiding, meaning that the client’s authentication profiles such as her email username, phone number, passwords, and biometric features are not revealed unless all servers are compromised. We propose secure and practical protocols for an array of widely adopted authentication factors, including email passcodes, SMS messages, U2F, security questions/passwords, and biometrics. Our system finds practical applications in the space of cryptocurrency custody and collaborative machine learning, and benefits future adoptions of distributed-trust applications.
分布式信任系统吸引了越来越多的研究关注，并被越来越多的行业所采用。在这些系统中，关键机密分布在 N 台服务器上，并使用安全多方计算（SMPC）进行私密计算。这些分布式信任系统的身份验证面临两个挑战。第一个挑战是易用性。也就是说，认证协议如何才能在不牺牲安全性的前提下保持用户体验？为了避免中心攻击点，客户端需要分别对每个服务器进行身份验证。然而，这就要求客户端对每个认证因素进行 N 次认证，从而大大影响了可用性。第二个挑战是隐私问题，因为客户端的敏感档案现在暴露在不同信任域下的所有 N 台服务器上，这就为档案数据创造了 N 倍的攻击面。我们的系统使客户端只需进行一次身份验证，就能对 N 台服务器进行独立身份验证。此外，我们的系统还具有配置文件隐藏功能，也就是说，除非所有服务器都遭到破坏，否则客户端的身份验证配置文件（如电子邮件用户名、电话号码、密码和生物特征）不会泄露。我们为一系列广泛采用的认证因素提出了安全实用的协议，包括电子邮件密码、短信、U2F、安全问题/密码和生物识别。我们的系统可实际应用于加密货币保管和协作机器学习领域，并有利于未来分布式信任应用的采用。
{"title":"MPCAuth: Multi-factor Authentication for Distributed-trust Systems","authors":"Sijun Tan, Weikeng Chen, Ryan Deng, R. A. Popa","doi":"10.1109/SP46215.2023.10179481","DOIUrl":"https://doi.org/10.1109/SP46215.2023.10179481","url":null,"abstract":"Systems with distributed trust have attracted growing research attention and seen increasing industry adoptions. In these systems, critical secrets are distributed across N servers, and computations are performed privately using secure multi-party computation (SMPC). Authentication for these distributed-trust systems faces two challenges. The first challenge is ease-of-use. Namely, how can an authentication protocol maintain its user experience without sacrificing security? To avoid a central point of attack, a client needs to authenticate to each server separately. However, this would require the client to authenticate N times for each authentication factor, which greatly hampers usability. The second challenge is privacy, as the client’s sensitive profiles are now exposed to all N servers under different trust domains, which creates N times the attack surface for the profile data.We present MPCAuth, a multi-factor authentication system for distributed-trust applications that address both challenges. Our system enables a client to authenticate to N servers independently with the work of only one authentication. In addition, our system is profile hiding, meaning that the client’s authentication profiles such as her email username, phone number, passwords, and biometric features are not revealed unless all servers are compromised. We propose secure and practical protocols for an array of widely adopted authentication factors, including email passcodes, SMS messages, U2F, security questions/passwords, and biometrics. Our system finds practical applications in the space of cryptocurrency custody and collaborative machine learning, and benefits future adoptions of distributed-trust applications.","PeriodicalId":439989,"journal":{"name":"2023 IEEE Symposium on Security and Privacy (SP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130466900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.1109/SP46215.2023.10179290
Matilda Backendal, Miro Haller, Kenneth G. Paterson
MEGA is a leading cloud storage platform with more than 250 million users and 1000 Petabytes of stored data. MEGA claims to offer user-controlled, end-to-end security. This is achieved by having all data encryption and decryption operations done on MEGA clients, under the control of keys that are only available to those clients. This is intended to protect MEGA users from attacks by MEGA itself, or by adversaries who have taken control of MEGA’s infrastructure.We provide a detailed analysis of MEGA’s use of cryptography in such a malicious server setting. We present five distinct attacks against MEGA, which together allow for a full compromise of the confidentiality of user files. Additionally, the integrity of user data is damaged to the extent that an attacker can insert malicious files of their choice which pass all authenticity checks of the client. We built proof-of-concept versions of all the attacks. Four of the five attacks are eminently practical. They have all been responsibly disclosed to MEGA and remediation is underway.Taken together, our attacks highlight significant shortcomings in MEGA’s cryptographic architecture. We present immediately deployable countermeasures, as well as longer-term recommendations. We also provide a broader discussion of the challenges of cryptographic deployment at massive scale under strong threat models.
{"title":"MEGA: Malleable Encryption Goes Awry","authors":"Matilda Backendal, Miro Haller, Kenneth G. Paterson","doi":"10.1109/SP46215.2023.10179290","DOIUrl":"https://doi.org/10.1109/SP46215.2023.10179290","url":null,"abstract":"MEGA is a leading cloud storage platform with more than 250 million users and 1000 Petabytes of stored data. MEGA claims to offer user-controlled, end-to-end security. This is achieved by having all data encryption and decryption operations done on MEGA clients, under the control of keys that are only available to those clients. This is intended to protect MEGA users from attacks by MEGA itself, or by adversaries who have taken control of MEGA’s infrastructure.We provide a detailed analysis of MEGA’s use of cryptography in such a malicious server setting. We present five distinct attacks against MEGA, which together allow for a full compromise of the confidentiality of user files. Additionally, the integrity of user data is damaged to the extent that an attacker can insert malicious files of their choice which pass all authenticity checks of the client. We built proof-of-concept versions of all the attacks. Four of the five attacks are eminently practical. They have all been responsibly disclosed to MEGA and remediation is underway.Taken together, our attacks highlight significant shortcomings in MEGA’s cryptographic architecture. We present immediately deployable countermeasures, as well as longer-term recommendations. We also provide a broader discussion of the challenges of cryptographic deployment at massive scale under strong threat models.","PeriodicalId":439989,"journal":{"name":"2023 IEEE Symposium on Security and Privacy (SP)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115030959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.1109/SP46215.2023.10179468
Mayank Rathee, Conghao Shen, Sameer Wagh, R. A. Popa
Federated learning (FL) is an increasingly popular approach for machine learning (ML) in cases where the training dataset is highly distributed. Clients perform local training on their datasets and the updates are then aggregated into the global model. Existing protocols for aggregation are either inefficient, or don’t consider the case of malicious actors in the system. This is a major barrier in making FL an ideal solution for privacy-sensitive ML applications. We present Elsa, a secure aggregation protocol for FL, which breaks this barrier - it is efficient and addresses the existence of malicious actors at the core of its design. Similar to prior work on Prio and Prio+, Elsa provides a novel secure aggregation protocol built out of distributed trust across two servers that keeps individual client updates private as long as one server is honest, defends against malicious clients, and is efficient end-to-end. Compared to prior works, the distinguishing theme in Elsa is that instead of the servers generating cryptographic correlations interactively, the clients act as untrusted dealers of these correlations without compromising the protocol’s security. This leads to a much faster protocol while also achieving stronger security at that efficiency compared to prior work. We introduce new techniques that retain privacy even when a server is malicious at a small added cost of 7-25% in runtime with negligible increase in communication over the case of semi-honest server. Our work improves end-to-end runtime over prior work with similar security guarantees by big margins - single-aggregator RoFL by up to 305x (for the models we consider), and distributed trust Prio by up to 8x.
{"title":"ELSA: Secure Aggregation for Federated Learning with Malicious Actors","authors":"Mayank Rathee, Conghao Shen, Sameer Wagh, R. A. Popa","doi":"10.1109/SP46215.2023.10179468","DOIUrl":"https://doi.org/10.1109/SP46215.2023.10179468","url":null,"abstract":"Federated learning (FL) is an increasingly popular approach for machine learning (ML) in cases where the training dataset is highly distributed. Clients perform local training on their datasets and the updates are then aggregated into the global model. Existing protocols for aggregation are either inefficient, or don’t consider the case of malicious actors in the system. This is a major barrier in making FL an ideal solution for privacy-sensitive ML applications. We present Elsa, a secure aggregation protocol for FL, which breaks this barrier - it is efficient and addresses the existence of malicious actors at the core of its design. Similar to prior work on Prio and Prio+, Elsa provides a novel secure aggregation protocol built out of distributed trust across two servers that keeps individual client updates private as long as one server is honest, defends against malicious clients, and is efficient end-to-end. Compared to prior works, the distinguishing theme in Elsa is that instead of the servers generating cryptographic correlations interactively, the clients act as untrusted dealers of these correlations without compromising the protocol’s security. This leads to a much faster protocol while also achieving stronger security at that efficiency compared to prior work. We introduce new techniques that retain privacy even when a server is malicious at a small added cost of 7-25% in runtime with negligible increase in communication over the case of semi-honest server. Our work improves end-to-end runtime over prior work with similar security guarantees by big margins - single-aggregator RoFL by up to 305x (for the models we consider), and distributed trust Prio by up to 8x.","PeriodicalId":439989,"journal":{"name":"2023 IEEE Symposium on Security and Privacy (SP)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131011436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.1109/SP46215.2023.10179433
Jianhao Xu, L. Bartolomeo, Flavio Toffalini, Bing Mao, Mathias Payer
Code-reuse attacks are dangerous threats that attracted the attention of the security community for years. These attacks aim at corrupting important control-flow transfers for taking control of a process without injecting code. Nowadays, the combinations of multiple mitigations (e.g., ASLR, DEP, and CFI) drastically reduced this attack surface, making running code-reuse exploits more challenging.Unfortunately, security mitigations are combined with compiler optimizations, that do not distinguish between security-related and application code. Blindly deploying code optimizations over code-reuse mitigations may undermine their security guarantees. For instance, compilers may introduce double-fetch vulnerabilities that lead to concurrency issues such as Time-Of-Check to Time-Of-Use (TOCTTOU) attacks.In this work, we propose a new attack vector, called WarpAttack, that exploits compiler-introduced double-fetch optimizations to mount TOCTTOU attacks and bypass code-reuse mitigations. We study the mechanism underlying this attack and present a practical proof-of-concept exploit against the last version of Firefox. Additionally, we propose a lightweight analysis to locate vulnerable double-fetch code (with 3% false positives) and conduct research over six popular applications, five operating systems, and four architectures (32 and 64 bits) to study the diffusion of this threat. Moreover, we study the implication of our attack against six CFI implementations. Finally, we investigate possible research lines for addressing this threat and propose practical solutions to be deployed in existing projects.
{"title":"WarpAttack: Bypassing CFI through Compiler-Introduced Double-Fetches","authors":"Jianhao Xu, L. Bartolomeo, Flavio Toffalini, Bing Mao, Mathias Payer","doi":"10.1109/SP46215.2023.10179433","DOIUrl":"https://doi.org/10.1109/SP46215.2023.10179433","url":null,"abstract":"Code-reuse attacks are dangerous threats that attracted the attention of the security community for years. These attacks aim at corrupting important control-flow transfers for taking control of a process without injecting code. Nowadays, the combinations of multiple mitigations (e.g., ASLR, DEP, and CFI) drastically reduced this attack surface, making running code-reuse exploits more challenging.Unfortunately, security mitigations are combined with compiler optimizations, that do not distinguish between security-related and application code. Blindly deploying code optimizations over code-reuse mitigations may undermine their security guarantees. For instance, compilers may introduce double-fetch vulnerabilities that lead to concurrency issues such as Time-Of-Check to Time-Of-Use (TOCTTOU) attacks.In this work, we propose a new attack vector, called WarpAttack, that exploits compiler-introduced double-fetch optimizations to mount TOCTTOU attacks and bypass code-reuse mitigations. We study the mechanism underlying this attack and present a practical proof-of-concept exploit against the last version of Firefox. Additionally, we propose a lightweight analysis to locate vulnerable double-fetch code (with 3% false positives) and conduct research over six popular applications, five operating systems, and four architectures (32 and 64 bits) to study the diffusion of this threat. Moreover, we study the implication of our attack against six CFI implementations. Finally, we investigate possible research lines for addressing this threat and propose practical solutions to be deployed in existing projects.","PeriodicalId":439989,"journal":{"name":"2023 IEEE Symposium on Security and Privacy (SP)","volume":"247 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133455936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.1109/SP46215.2023.10179356
Lin Ma, Duoming Zhou, Hanjie Wu, Yajin Zhou, Rui Chang, Hao Xiong, L. Wu, K. Ren
When a device is detached from the system, Use-After-Cleanup (UAC) bugs can occur because a running kernel thread may be unaware of the device detachment and attempt to use an object that has been released by the cleanup thread. Our investigation suggests that an attacker can exploit the UAC bugs to obtain the capability of arbitrary code execution and privilege escalation, which receives little attention from the community. While existing tools mainly focus on well-known concurrency bugs like data race, few target UAC bugs.In this paper, we propose a tool named UACatcher to systematically detect UAC bugs. UACatcher consists of three main phases. It first scans the entire kernel to find target layers. Next, it adopts the context- and flow-sensitive inter-procedural analysis and the points-to analysis to locate possible free (deallocation) sites in the bottom-up cleanup thread and use (dereference) sites in the top-down kernel thread that can cause UAC bugs. Then, UACatcher uses the routine switch point algorithm which counts on the synchronizations and path constraints to detect UAC bugs among these sites and estimate exploitable ones. For exploitable bugs, we leverage the pseudoterminal-based device emulation technique to develop practical exploits.We have implemented a prototype of UACatcher and evaluated it on 5.11 Linux kernel. As a result, our tool successfully detected 346 UAC bugs, which were reported to the community (277 have been confirmed and fixed and 15 CVEs have been assigned). Additionally, 13 bugs are exploitable, which can be used to develop working exploits that gain the arbitrary code execution primitive in kernel space and achieve the privilege escalation. Finally, we discuss UACatcher’s limitations and propose possible solutions to fix and prevent UAC bugs.
当设备从系统中分离出来时，可能会出现“清理后使用”(use - after - cleanup, UAC)错误，因为正在运行的内核线程可能不知道设备分离，并试图使用清理线程释放的对象。我们的调查表明，攻击者可以利用UAC漏洞获得任意代码执行和特权升级的能力，这一点很少受到社区的关注。虽然现有的工具主要关注众所周知的并发错误，如数据竞争，但很少针对UAC错误。在本文中，我们提出了一个名为UACatcher的工具来系统地检测UAC漏洞。UACatcher包括三个主要阶段。它首先扫描整个内核以找到目标层。接下来，它采用上下文和流程敏感的过程间分析和指向分析来定位自底向上清理线程中可能的空闲(释放)位置和自顶向下内核线程中可能导致UAC错误的使用(解引用)位置。然后，UACatcher使用基于同步和路径约束的常规切换点算法来检测这些站点之间的UAC漏洞并估计可利用的漏洞。对于可利用的漏洞，我们利用基于伪终端的设备仿真技术来开发实用的漏洞。我们实现了UACatcher的原型，并在5.11 Linux内核上对其进行了评估。结果，我们的工具成功检测了346个UAC漏洞，并向社区报告了这些漏洞(277个已被确认并修复，并分配了15个cve)。此外，有13个漏洞是可利用的，它们可用于开发工作漏洞，从而获得内核空间中的任意代码执行原语并实现特权升级。最后，我们讨论了UACatcher的局限性，并提出了修复和防止UAC错误的可能解决方案。
{"title":"When Top-down Meets Bottom-up: Detecting and Exploiting Use-After-Cleanup Bugs in Linux Kernel","authors":"Lin Ma, Duoming Zhou, Hanjie Wu, Yajin Zhou, Rui Chang, Hao Xiong, L. Wu, K. Ren","doi":"10.1109/SP46215.2023.10179356","DOIUrl":"https://doi.org/10.1109/SP46215.2023.10179356","url":null,"abstract":"When a device is detached from the system, Use-After-Cleanup (UAC) bugs can occur because a running kernel thread may be unaware of the device detachment and attempt to use an object that has been released by the cleanup thread. Our investigation suggests that an attacker can exploit the UAC bugs to obtain the capability of arbitrary code execution and privilege escalation, which receives little attention from the community. While existing tools mainly focus on well-known concurrency bugs like data race, few target UAC bugs.In this paper, we propose a tool named UACatcher to systematically detect UAC bugs. UACatcher consists of three main phases. It first scans the entire kernel to find target layers. Next, it adopts the context- and flow-sensitive inter-procedural analysis and the points-to analysis to locate possible free (deallocation) sites in the bottom-up cleanup thread and use (dereference) sites in the top-down kernel thread that can cause UAC bugs. Then, UACatcher uses the routine switch point algorithm which counts on the synchronizations and path constraints to detect UAC bugs among these sites and estimate exploitable ones. For exploitable bugs, we leverage the pseudoterminal-based device emulation technique to develop practical exploits.We have implemented a prototype of UACatcher and evaluated it on 5.11 Linux kernel. As a result, our tool successfully detected 346 UAC bugs, which were reported to the community (277 have been confirmed and fixed and 15 CVEs have been assigned). Additionally, 13 bugs are exploitable, which can be used to develop working exploits that gain the arbitrary code execution primitive in kernel space and achieve the privilege escalation. Finally, we discuss UACatcher’s limitations and propose possible solutions to fix and prevent UAC bugs.","PeriodicalId":439989,"journal":{"name":"2023 IEEE Symposium on Security and Privacy (SP)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133278958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Link-flooding attacks (LFAs) can cut off the Internet connection to selected server targets and are hard to mitigate because adversaries use normal-looking and low-rate flows and can dynamically adjust the attack strategy. Traditional centralized defense systems cannot locally and efficiently suppress malicious traffic. Though emerging programmable switches offer an opportunity to bring defense systems closer to targeted links, their limited resource and lack of support for runtime reconfiguration limit their usage for link-flooding defenses.We present Mew1, a resource-efficient and runtime adaptable link-flooding defense system. Mew can counter various LFAs even when a massive number of flows are concentrated on a link, or when the attack strategy changes quickly. We design a distributed storage mechanism and a lossless state migration mechanism to reduce the storage bottleneck of programmable networks. We develop cooperative defense APIs to support multi-grained co-detection and co-mitigation without excessive overhead. Mew's dynamic defense mechanism can constantly analyze network conditions and activate corresponding defenses without rebooting devices or interrupting other running functions. We develop a prototype of Mew by using real-world programmable switches, which are located in five cities. Our experiments show that the real-world prototype can defend against large-scale and dynamic LFAs effectively.
{"title":"Mew: Enabling Large-Scale and Dynamic Link-Flooding Defenses on Programmable Switches","authors":"Huancheng Zhou, Sungmin Hong, Yangyang Liu, Xiapu Luo, Weichao Li, G. Gu","doi":"10.1109/SP46215.2023.10179404","DOIUrl":"https://doi.org/10.1109/SP46215.2023.10179404","url":null,"abstract":"Link-flooding attacks (LFAs) can cut off the Internet connection to selected server targets and are hard to mitigate because adversaries use normal-looking and low-rate flows and can dynamically adjust the attack strategy. Traditional centralized defense systems cannot locally and efficiently suppress malicious traffic. Though emerging programmable switches offer an opportunity to bring defense systems closer to targeted links, their limited resource and lack of support for runtime reconfiguration limit their usage for link-flooding defenses.We present Mew1, a resource-efficient and runtime adaptable link-flooding defense system. Mew can counter various LFAs even when a massive number of flows are concentrated on a link, or when the attack strategy changes quickly. We design a distributed storage mechanism and a lossless state migration mechanism to reduce the storage bottleneck of programmable networks. We develop cooperative defense APIs to support multi-grained co-detection and co-mitigation without excessive overhead. Mew's dynamic defense mechanism can constantly analyze network conditions and activate corresponding defenses without rebooting devices or interrupting other running functions. We develop a prototype of Mew by using real-world programmable switches, which are located in five cities. Our experiments show that the real-world prototype can defend against large-scale and dynamic LFAs effectively.","PeriodicalId":439989,"journal":{"name":"2023 IEEE Symposium on Security and Privacy (SP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130246321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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