Pub Date : 2020-05-01DOI: 10.1109/SP40000.2020.00017
Feng Xiao, Jinquan Zhang, Jianwei Huang, G. Gu, Dinghao Wu, Peng Liu
Software-Defined Networking (SDN) is an emerging network architecture that provides programmable networking through a logically centralized controller. As SDN becomes more prominent, its security vulnerabilities become more evident than ever. Serving as the "brain" of a software-defined network, how the control plane (of the network) is exposed to external inputs (i.e., data plane messages) is directly correlated with how secure the network is. Fortunately, due to some unique SDN design choices (e.g., control plane and data plane separation), attackers often struggle to find a reachable path to those vulnerable logic hidden deeply within the control plane.In this paper, we demonstrate that it is possible for a weak adversary who only controls a commodity network device (host or switch) to attack previously unreachable control plane components by maliciously increasing reachability in the control plane. We introduce D2C2 (data dependency creation and chaining) attack, which leverages some widely-used SDN protocol features (e.g., custom fields) to create and chain unexpected data dependencies in order to achieve greater reachability. We have developed a novel tool, SVHunter, which can effectively identify D2C2 vulnerabilities. Till now we have evaluated SVHunter on three mainstream open-source SDN controllers (i.e., ONOS, Floodlight, and Opendaylight) as well as one security-enhanced controller (i.e., SE-Floodlight). SVHunter detects 18 previously unknown vulnerabilities, all of which can be exploited remotely to launch serious attacks such as executing arbitrary commands, exfiltrating confidential files, and crashing SDN services.
{"title":"Unexpected Data Dependency Creation and Chaining: A New Attack to SDN","authors":"Feng Xiao, Jinquan Zhang, Jianwei Huang, G. Gu, Dinghao Wu, Peng Liu","doi":"10.1109/SP40000.2020.00017","DOIUrl":"https://doi.org/10.1109/SP40000.2020.00017","url":null,"abstract":"Software-Defined Networking (SDN) is an emerging network architecture that provides programmable networking through a logically centralized controller. As SDN becomes more prominent, its security vulnerabilities become more evident than ever. Serving as the \"brain\" of a software-defined network, how the control plane (of the network) is exposed to external inputs (i.e., data plane messages) is directly correlated with how secure the network is. Fortunately, due to some unique SDN design choices (e.g., control plane and data plane separation), attackers often struggle to find a reachable path to those vulnerable logic hidden deeply within the control plane.In this paper, we demonstrate that it is possible for a weak adversary who only controls a commodity network device (host or switch) to attack previously unreachable control plane components by maliciously increasing reachability in the control plane. We introduce D2C2 (data dependency creation and chaining) attack, which leverages some widely-used SDN protocol features (e.g., custom fields) to create and chain unexpected data dependencies in order to achieve greater reachability. We have developed a novel tool, SVHunter, which can effectively identify D2C2 vulnerabilities. Till now we have evaluated SVHunter on three mainstream open-source SDN controllers (i.e., ONOS, Floodlight, and Opendaylight) as well as one security-enhanced controller (i.e., SE-Floodlight). SVHunter detects 18 previously unknown vulnerabilities, all of which can be exploited remotely to launch serious attacks such as executing arbitrary commands, exfiltrating confidential files, and crashing SDN services.","PeriodicalId":6849,"journal":{"name":"2020 IEEE Symposium on Security and Privacy (SP)","volume":"39 7","pages":"1512-1526"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72547810","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 : 2020-05-01DOI: 10.1109/SP40000.2020.00114
Jonathan Protzenko, Bryan Parno, Aymeric Fromherz, C. Hawblitzel, M. Polubelova, K. Bhargavan, Benjamin Beurdouche, Joonwon Choi, Antoine Delignat-Lavaud, C. Fournet, T. Ramananandro, Aseem Rastogi, N. Swamy, C. Wintersteiger, Santiago Zanella Béguelin
We present EverCrypt: a comprehensive collection of verified, high-performance cryptographic functionalities available via a carefully designed API. The API provably supports agility (choosing between multiple algorithms for the same functionality) and multiplexing (choosing between multiple implementations of the same algorithm). Through abstraction and zero-cost generic programming, we show how agility can simplify verification without sacrificing performance, and we demonstrate how C and assembly can be composed and verified against shared specifications. We substantiate the effectiveness of these techniques with new verified implementations (including hashes, Curve25519, and AES-GCM) whose performance matches or exceeds the best unverified implementations. We validate the API design with two high-performance verified case studies built atop EverCrypt, resulting in line-rate performance for a secure network protocol and a Merkle-tree library, used in a production blockchain, that supports 2.7 million insertions/sec. Altogether, EverCrypt consists of over 124K verified lines of specs, code, and proofs, and it produces over 29K lines of C and 14K lines of assembly code.
{"title":"EverCrypt: A Fast, Verified, Cross-Platform Cryptographic Provider","authors":"Jonathan Protzenko, Bryan Parno, Aymeric Fromherz, C. Hawblitzel, M. Polubelova, K. Bhargavan, Benjamin Beurdouche, Joonwon Choi, Antoine Delignat-Lavaud, C. Fournet, T. Ramananandro, Aseem Rastogi, N. Swamy, C. Wintersteiger, Santiago Zanella Béguelin","doi":"10.1109/SP40000.2020.00114","DOIUrl":"https://doi.org/10.1109/SP40000.2020.00114","url":null,"abstract":"We present EverCrypt: a comprehensive collection of verified, high-performance cryptographic functionalities available via a carefully designed API. The API provably supports agility (choosing between multiple algorithms for the same functionality) and multiplexing (choosing between multiple implementations of the same algorithm). Through abstraction and zero-cost generic programming, we show how agility can simplify verification without sacrificing performance, and we demonstrate how C and assembly can be composed and verified against shared specifications. We substantiate the effectiveness of these techniques with new verified implementations (including hashes, Curve25519, and AES-GCM) whose performance matches or exceeds the best unverified implementations. We validate the API design with two high-performance verified case studies built atop EverCrypt, resulting in line-rate performance for a secure network protocol and a Merkle-tree library, used in a production blockchain, that supports 2.7 million insertions/sec. Altogether, EverCrypt consists of over 124K verified lines of specs, code, and proofs, and it produces over 29K lines of C and 14K lines of assembly code.","PeriodicalId":6849,"journal":{"name":"2020 IEEE Symposium on Security and Privacy (SP)","volume":"47 1","pages":"983-1002"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73524268","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 : 2020-05-01DOI: 10.1109/SP40000.2020.00029
Evgenios M. Kornaropoulos, Charalampos Papamanthou, R. Tamassia
Recent foundational work on leakage-abuse attacks on encrypted databases has broadened our understanding of what an adversary can accomplish with a standard leakage profile. Nevertheless, all known value reconstruction attacks succeed under strong assumptions that may not hold in the real world. The most prevalent assumption is that queries are issued uniformly at random by the client. We present the first value reconstruction attacks that succeed without any knowledge about the query or data distribution. Our approach uses the search-pattern leakage, which exists in all known structured encryption schemes but has not been fully exploited so far. At the core of our method lies a support size estimator, a technique that utilizes the repetition of search tokens with the same response to estimate distances between encrypted values without any assumptions about the underlying distribution. We develop distribution-agnostic reconstruction attacks for both range queries and k-nearest-neighbor (k-NN) queries based on information extracted from the search-pattern leakage. Our new range attack follows a different algorithmic approach than state-of-the-art attacks, which are fine-tuned to succeed under the uniformly distributed queries. Instead, we reconstruct plaintext values under a variety of skewed query distributions and even outperform the accuracy of previous approaches under the uniform query distribution. Our new k-NN attack succeeds with far fewer samples than previous attacks and scales to much larger values of k. We demonstrate the effectiveness of our attacks by experimentally testing them on a wide range of query distributions and database densities, both unknown to the adversary.
{"title":"The State of the Uniform: Attacks on Encrypted Databases Beyond the Uniform Query Distribution","authors":"Evgenios M. Kornaropoulos, Charalampos Papamanthou, R. Tamassia","doi":"10.1109/SP40000.2020.00029","DOIUrl":"https://doi.org/10.1109/SP40000.2020.00029","url":null,"abstract":"Recent foundational work on leakage-abuse attacks on encrypted databases has broadened our understanding of what an adversary can accomplish with a standard leakage profile. Nevertheless, all known value reconstruction attacks succeed under strong assumptions that may not hold in the real world. The most prevalent assumption is that queries are issued uniformly at random by the client. We present the first value reconstruction attacks that succeed without any knowledge about the query or data distribution. Our approach uses the search-pattern leakage, which exists in all known structured encryption schemes but has not been fully exploited so far. At the core of our method lies a support size estimator, a technique that utilizes the repetition of search tokens with the same response to estimate distances between encrypted values without any assumptions about the underlying distribution. We develop distribution-agnostic reconstruction attacks for both range queries and k-nearest-neighbor (k-NN) queries based on information extracted from the search-pattern leakage. Our new range attack follows a different algorithmic approach than state-of-the-art attacks, which are fine-tuned to succeed under the uniformly distributed queries. Instead, we reconstruct plaintext values under a variety of skewed query distributions and even outperform the accuracy of previous approaches under the uniform query distribution. Our new k-NN attack succeeds with far fewer samples than previous attacks and scales to much larger values of k. We demonstrate the effectiveness of our attacks by experimentally testing them on a wide range of query distributions and database densities, both unknown to the adversary.","PeriodicalId":6849,"journal":{"name":"2020 IEEE Symposium on Security and Privacy (SP)","volume":"118 1","pages":"1223-1240"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77931004","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 : 2020-05-01DOI: 10.1109/SP40000.2020.00061
David Cerdeira, Nuno Santos, Pedro Fonseca, S. Pinto
Hundreds of millions of mobile devices worldwide rely on Trusted Execution Environments (TEEs) built with Arm TrustZone for the protection of security-critical applications (e.g., DRM) and operating system (OS) components (e.g., Android keystore). TEEs are often assumed to be highly secure; however, over the past years, TEEs have been successfully attacked multiple times, with highly damaging impact across various platforms. Unfortunately, these attacks have been possible by the presence of security flaws in TEE systems. In this paper, we aim to understand which types of vulnerabilities and limitations affect existing TrustZone-assisted TEE systems, what are the main challenges to build them correctly, and what contributions can be borrowed from the research community to overcome them. To this end, we present a security analysis of popular TrustZone-assisted TEE systems (targeting Cortex-A processors) developed by Qualcomm, Trustonic, Huawei, Nvidia, and Linaro. By studying publicly documented exploits and vulnerabilities as well as by reverse engineering the TEE firmware, we identified several critical vulnerabilities across existing systems which makes it legitimate to raise reasonable concerns about the security of commercial TEE implementations.
{"title":"SoK: Understanding the Prevailing Security Vulnerabilities in TrustZone-assisted TEE Systems","authors":"David Cerdeira, Nuno Santos, Pedro Fonseca, S. Pinto","doi":"10.1109/SP40000.2020.00061","DOIUrl":"https://doi.org/10.1109/SP40000.2020.00061","url":null,"abstract":"Hundreds of millions of mobile devices worldwide rely on Trusted Execution Environments (TEEs) built with Arm TrustZone for the protection of security-critical applications (e.g., DRM) and operating system (OS) components (e.g., Android keystore). TEEs are often assumed to be highly secure; however, over the past years, TEEs have been successfully attacked multiple times, with highly damaging impact across various platforms. Unfortunately, these attacks have been possible by the presence of security flaws in TEE systems. In this paper, we aim to understand which types of vulnerabilities and limitations affect existing TrustZone-assisted TEE systems, what are the main challenges to build them correctly, and what contributions can be borrowed from the research community to overcome them. To this end, we present a security analysis of popular TrustZone-assisted TEE systems (targeting Cortex-A processors) developed by Qualcomm, Trustonic, Huawei, Nvidia, and Linaro. By studying publicly documented exploits and vulnerabilities as well as by reverse engineering the TEE firmware, we identified several critical vulnerabilities across existing systems which makes it legitimate to raise reasonable concerns about the security of commercial TEE implementations.","PeriodicalId":6849,"journal":{"name":"2020 IEEE Symposium on Security and Privacy (SP)","volume":"44 1","pages":"1416-1432"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76357605","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 : 2020-05-01DOI: 10.1109/SP40000.2020.00016
Chun Guo, Jonathan Katz, X. Wang, Yu Yu
Many implementations of secure computation use fixed-key AES (modeled as a random permutation); this results in substantial performance benefits due to existing hardware support for AES and the ability to avoid recomputing the AES key schedule. Surveying these implementations, however, we find that most utilize AES in a heuristic fashion; in the best case this leaves a gap in the security proof, but in many cases we show it allows for explicit attacks.Motivated by this unsatisfactory state of affairs, we initiate a comprehensive study of how to use fixed-key block ciphers for secure computation—in particular for OT extension and circuit garbling—efficiently and securely. Specifically:•We consider several notions of pseudorandomness for hash functions (e.g., correlation robustness), and show provably secure schemes for OT extension, garbling, and other applications based on hash functions satisfying these notions.•We provide provably secure constructions, in the (non-programmable) random-permutation model, of hash functions satisfying the different notions of pseudorandomness we consider.Taken together, our results provide end-to-end security proofs for implementations of secure-computation protocols based on fixed-key block ciphers (modeled as random permutations). Perhaps surprisingly, at the same time our work also results in noticeable performance improvements over the state-of-the-art.
{"title":"Efficient and Secure Multiparty Computation from Fixed-Key Block Ciphers","authors":"Chun Guo, Jonathan Katz, X. Wang, Yu Yu","doi":"10.1109/SP40000.2020.00016","DOIUrl":"https://doi.org/10.1109/SP40000.2020.00016","url":null,"abstract":"Many implementations of secure computation use fixed-key AES (modeled as a random permutation); this results in substantial performance benefits due to existing hardware support for AES and the ability to avoid recomputing the AES key schedule. Surveying these implementations, however, we find that most utilize AES in a heuristic fashion; in the best case this leaves a gap in the security proof, but in many cases we show it allows for explicit attacks.Motivated by this unsatisfactory state of affairs, we initiate a comprehensive study of how to use fixed-key block ciphers for secure computation—in particular for OT extension and circuit garbling—efficiently and securely. Specifically:•We consider several notions of pseudorandomness for hash functions (e.g., correlation robustness), and show provably secure schemes for OT extension, garbling, and other applications based on hash functions satisfying these notions.•We provide provably secure constructions, in the (non-programmable) random-permutation model, of hash functions satisfying the different notions of pseudorandomness we consider.Taken together, our results provide end-to-end security proofs for implementations of secure-computation protocols based on fixed-key block ciphers (modeled as random permutations). Perhaps surprisingly, at the same time our work also results in noticeable performance improvements over the state-of-the-art.","PeriodicalId":6849,"journal":{"name":"2020 IEEE Symposium on Security and Privacy (SP)","volume":"172 1","pages":"825-841"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73309226","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 : 2020-05-01DOI: 10.1109/SP40000.2020.00068
Jonathan Lee, K. Nikitin, Srinath T. V. Setty
This paper introduces a new approach to reduce end-to-end costs in large-scale replicated systems built under a Byzantine fault model. Specifically, our approach transforms a given replicated state machine (RSM) to another RSM where nodes incur lower costs by delegating state machine execution: an untrusted prover produces succinct cryptographic proofs of correct state transitions along with state changes, which nodes in the transformed RSM verify and apply respectively.To realize our approach, we build Piperine, a system that makes the proof machinery profitable in the context of RSMs. Specifically, Piperine reduces the costs of both proving and verifying the correctness of state machine execution while retaining liveness—a distinctive requirement in the context of RSMs. Our experimental evaluation demonstrates that, for a payment service, employing Piperine is more profitable than naive reexecution of transactions as long as there are > 104 nodes. When we apply Piperine to ERC-20 transactions in Ethereum (a real-world RSM with up to 105 nodes), it reduces per-transaction costs by 5.4× and network costs by 2.7×.
{"title":"Replicated state machines without replicated execution","authors":"Jonathan Lee, K. Nikitin, Srinath T. V. Setty","doi":"10.1109/SP40000.2020.00068","DOIUrl":"https://doi.org/10.1109/SP40000.2020.00068","url":null,"abstract":"This paper introduces a new approach to reduce end-to-end costs in large-scale replicated systems built under a Byzantine fault model. Specifically, our approach transforms a given replicated state machine (RSM) to another RSM where nodes incur lower costs by delegating state machine execution: an untrusted prover produces succinct cryptographic proofs of correct state transitions along with state changes, which nodes in the transformed RSM verify and apply respectively.To realize our approach, we build Piperine, a system that makes the proof machinery profitable in the context of RSMs. Specifically, Piperine reduces the costs of both proving and verifying the correctness of state machine execution while retaining liveness—a distinctive requirement in the context of RSMs. Our experimental evaluation demonstrates that, for a payment service, employing Piperine is more profitable than naive reexecution of transactions as long as there are > 104 nodes. When we apply Piperine to ERC-20 transactions in Ethereum (a real-world RSM with up to 105 nodes), it reduces per-transaction costs by 5.4× and network costs by 2.7×.","PeriodicalId":6849,"journal":{"name":"2020 IEEE Symposium on Security and Privacy (SP)","volume":"12 1","pages":"119-134"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73950582","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 : 2020-05-01DOI: 10.1109/SP40000.2020.00012
Michael Carl Tschantz, S. Sen, Anupam Datta
We present formal models of the associative and causal views of differential privacy. Under the associative view, the possibility of dependencies between data points precludes a simple statement of differential privacy's guarantee as conditioning upon a single changed data point. However, we show that a simple characterization of differential privacy as limiting the effect of a single data point does exist under the causal view, without independence assumptions about data points. We believe this characterization resolves disagreement and confusion in prior work about the consequences of differential privacy. The associative view needing assumptions boils down to the contrapositive of the maxim that correlation doesn't imply causation: differential privacy ensuring a lack of (strong) causation does not imply a lack of (strong) association. Our characterization also opens up the possibility of applying results from statistics, experimental design, and science about causation while studying differential privacy.
{"title":"SoK: Differential Privacy as a Causal Property","authors":"Michael Carl Tschantz, S. Sen, Anupam Datta","doi":"10.1109/SP40000.2020.00012","DOIUrl":"https://doi.org/10.1109/SP40000.2020.00012","url":null,"abstract":"We present formal models of the associative and causal views of differential privacy. Under the associative view, the possibility of dependencies between data points precludes a simple statement of differential privacy's guarantee as conditioning upon a single changed data point. However, we show that a simple characterization of differential privacy as limiting the effect of a single data point does exist under the causal view, without independence assumptions about data points. We believe this characterization resolves disagreement and confusion in prior work about the consequences of differential privacy. The associative view needing assumptions boils down to the contrapositive of the maxim that correlation doesn't imply causation: differential privacy ensuring a lack of (strong) causation does not imply a lack of (strong) association. Our characterization also opens up the possibility of applying results from statistics, experimental design, and science about causation while studying differential privacy.","PeriodicalId":6849,"journal":{"name":"2020 IEEE Symposium on Security and Privacy (SP)","volume":"31 1","pages":"354-371"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81732711","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 : 2020-05-01DOI: 10.1109/SP40000.2020.00048
Thomas Haines, Sarah Jamie Lewis, Olivier Pereira, Vanessa Teague
The Scytl/SwissPost e-voting solution was intended to provide complete verifiability for Swiss government elections. We show failures in both individual verifiability and universal verifiability (as defined in Swiss Federal Ordinance 161.116), based on mistaken implementations of cryptographic components. These failures allow for the construction of "proofs" of an accurate election outcome that pass verification though the votes have been manipulated. Using sophisticated cryptographic protocols without a proper consideration of what properties they offer, and under which conditions, can introduce opportunities for undetectable fraud even though the system appears to allow verification of the outcome.Our findings are immediately relevant to systems in use in Switzerland and Australia, and probably also elsewhere.
{"title":"How not to prove your election outcome","authors":"Thomas Haines, Sarah Jamie Lewis, Olivier Pereira, Vanessa Teague","doi":"10.1109/SP40000.2020.00048","DOIUrl":"https://doi.org/10.1109/SP40000.2020.00048","url":null,"abstract":"The Scytl/SwissPost e-voting solution was intended to provide complete verifiability for Swiss government elections. We show failures in both individual verifiability and universal verifiability (as defined in Swiss Federal Ordinance 161.116), based on mistaken implementations of cryptographic components. These failures allow for the construction of \"proofs\" of an accurate election outcome that pass verification though the votes have been manipulated. Using sophisticated cryptographic protocols without a proper consideration of what properties they offer, and under which conditions, can introduce opportunities for undetectable fraud even though the system appears to allow verification of the outcome.Our findings are immediately relevant to systems in use in Switzerland and Australia, and probably also elsewhere.","PeriodicalId":6849,"journal":{"name":"2020 IEEE Symposium on Security and Privacy (SP)","volume":"9 1","pages":"644-660"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85455516","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 : 2020-05-01DOI: 10.1109/SP40000.2020.00075
Jonathan Berger, Amit Klein, Benny Pinkas
The IPv6 protocol was designed with security in mind. One of the changes that IPv6 has introduced over IPv4 is a new 20-bit flow label field in its protocol header.We show that remote servers can use the flow label field in order to assign a unique ID to each device when communicating with machines running Windows 10 (versions 1703 and higher), and Linux and Android (kernel versions 4.3 and higher). The servers are then able to associate the respective device IDs with subsequent transmissions sent from those machines. This identification is done by exploiting the flow label field generation logic and works across all browsers regardless of network changes. Furthermore, a variant of this attack also works passively, namely without actively triggering traffic from those machines.To design the attack we reverse-engineered and cryptanalyzed the Windows flow label generation code and inspected the Linux kernel flow label generation code. We provide a practical technique to partially extract the key used by each of these algorithms, and observe that this key can identify individual devices across networks, VPNs, browsers and privacy settings. We deployed a demo (for both Windows and Linux/Android) showing that key extraction and machine fingerprinting works in the wild, and tested it from networks around the world.
{"title":"Flaw Label: Exploiting IPv6 Flow Label","authors":"Jonathan Berger, Amit Klein, Benny Pinkas","doi":"10.1109/SP40000.2020.00075","DOIUrl":"https://doi.org/10.1109/SP40000.2020.00075","url":null,"abstract":"The IPv6 protocol was designed with security in mind. One of the changes that IPv6 has introduced over IPv4 is a new 20-bit flow label field in its protocol header.We show that remote servers can use the flow label field in order to assign a unique ID to each device when communicating with machines running Windows 10 (versions 1703 and higher), and Linux and Android (kernel versions 4.3 and higher). The servers are then able to associate the respective device IDs with subsequent transmissions sent from those machines. This identification is done by exploiting the flow label field generation logic and works across all browsers regardless of network changes. Furthermore, a variant of this attack also works passively, namely without actively triggering traffic from those machines.To design the attack we reverse-engineered and cryptanalyzed the Windows flow label generation code and inspected the Linux kernel flow label generation code. We provide a practical technique to partially extract the key used by each of these algorithms, and observe that this key can identify individual devices across networks, VPNs, browsers and privacy settings. We deployed a demo (for both Windows and Linux/Android) showing that key extraction and machine fingerprinting works in the wild, and tested it from networks around the world.","PeriodicalId":6849,"journal":{"name":"2020 IEEE Symposium on Security and Privacy (SP)","volume":"1 1","pages":"1259-1276"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84832204","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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