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1. TPM-Fail:TPM meets Timing and Lattice Attacks

   Moghimi, Daniel; Sunar, Berk; Eisenbarth, Thomas; Heninger, Nadia (January 2020, 29th USENIX Security Symposium (USENIX Security 20))

   null (Ed.)

   Trusted Platform Module (TPM) serves as a hardwarebased root of trust that protects cryptographic keys from privileged system and physical adversaries. In this work, we perform a black-box timing analysis of TPM 2.0 devices deployed on commodity computers. Our analysis reveals that some of these devices feature secret-dependent execution times during signature generation based on elliptic curves. In particular, we discovered timing leakage on an Intel firmwarebased TPM as well as a hardware TPM. We show how this information allows an attacker to apply lattice techniques to recover 256-bit private keys for ECDSA and ECSchnorr signatures. On Intel fTPM, our key recovery succeeds after about 1,300 observations and in less than two minutes. Similarly, we extract the private ECDSA key from a hardware TPM manufactured by STMicroelectronics, which is certified at Common Criteria (CC) EAL 4+, after fewer than 40,000 observations. We further highlight the impact of these vulnerabilities by demonstrating a remote attack against a StrongSwan IPsec VPN that uses a TPM to generate the digital signatures for authentication. In this attack, the remote client recovers the server’s private authentication key by timing only 45,000 authentication handshakes via a network connection. The vulnerabilities we have uncovered emphasize the difficulty of correctly implementing known constant-time techniques, and show the importance of evolutionary testing and transparent evaluation of cryptographic implementations. Even certified devices that claim resistance against attacks require additional scrutiny by the community and industry, as we learn more about these attacks. 

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2. pyecsca: Reverse engineering black-box elliptic curve cryptography via side-channel analysis

   https://doi.org/10.46586/tches.v2024.i4.355-381  

   Jancar, Jan; Suchanek, Vojtech; Svenda, Petr; Sedlacek, Vladimir; Chmielewski, Łukasz (September 2024, IACR Transactions on Cryptographic Hardware and Embedded Systems)

   Side-channel attacks on elliptic curve cryptography (ECC) often assume a white-box attacker who has detailed knowledge of the implementation choices taken by the target implementation. Due to the complex and layered nature of ECC, there are many choices that a developer makes to obtain a functional and interoperable implementation. These include the curve model, coordinate system, addition formulas, and the scalar multiplier, or lower-level details such as the finite-field multiplication algorithm. This creates a gap between the attack requirements and a real-world attacker that often only has black-box access to the target – i.e., has no access to the source code nor knowledge of specific implementation choices made. Yet, when the gap is closed, even real-world implementations of ECC succumb to side-channel attacks, as evidenced by attacks such as TPM-Fail, Minerva, the Side Journey to Titan, or TPMScan [MSE+20; JSS+20; RLM+21; SDB+24].We study this gap by first analyzing open-source ECC libraries for insight into realworld implementation choices. We then examine the space of all ECC implementations combinatorially. Finally, we present a set of novel methods for automated reverse engineering of black-box ECC implementations and release a documented and usable open-source toolkit for side-channel analysis of ECC called pyecsca.Our methods turn attacks around: instead of attempting to recover the private key, they attempt to recover the implementation configuration given control over the private and public inputs. We evaluate them on two simulation levels and study the effect of noise on their performance. Our methods are able to 1) reverse-engineer the scalar multiplication algorithm completely and 2) infer significant information about the coordinate system and addition formulas used in a target implementation. Furthermore, they can bypass coordinate and curve randomization countermeasures. 

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3. TPM-FAIL: TPM meets Timing and Lattice Attacks

   Moghimi, Daniel; Sunar, Berk; Eisenbarth, Thomas; Heninger, Nadia (January 2020, Proceedings of the 29th USENIX Security Symposium)

   null (Ed.)

   Trusted Platform Module (TPM) serves as a hardware based root of trust that protects cryptographic keys from privileged system and physical adversaries. In this work, we perform a black-box timing analysis of TPM 2.0 devices deployed on commodity computers. Our analysis reveals that some of these devices feature secret-dependent execution times during signature generation based on elliptic curves. In particular, we discovered timing leakage on an Intel firmware based TPM as well as a hardware TPM. We show how this information allows an attacker to apply lattice techniques to recover 256-bit private keys for ECDSA and ECSchnorr signatures. On Intel fTPM, our key recovery succeeds after about 1,300 observations and in less than two minutes. Similarly, we extract the private ECDSA key from a hardware TPM manufactured by STMicroelectronics, which is certified at Common Criteria (CC) EAL 4+, after fewer than 40,000 observations. We further highlight the impact of these vulnerabilities by demonstrating a remote attack against a StrongSwan IPsec VPN that uses a TPM to generate the digital signatures for authentication. In this attack, the remote client recovers the server’s private authentication key by timing only 45,000 authentication handshakes via a network connection. The vulnerabilities we have uncovered emphasize the difficulty of correctly implementing known constant-time techniques, and show the importance of evolutionary testing and transparent evaluation of cryptographic implementations. Even certified devices that claim resistance against attacks require additional scrutiny by the community and industry, as we learn more about these attacks. 

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4. Poster: A Fast Monitor for Slow Network Attacks

   Wei, Cuidi; Tu, Shaoyu; Hasegawa, Toru; Koizumi, Yuki; Ramakrishnan, K K; Takemasa, Junji; Wood, Timothy (June 2024, IEEE Cloud Summit)

   Abstract—Recent work has demonstrated how programmable switches can effectively detect attack traffic, such as denial- of-service attacks in the midst of high-volume network traffic. However, these techniques primarily rely on sampling- or sketch- based data structures that can only be used to approximate the characteristics of dominant flows in the network. As a result, such techniques are unable to effectively detect slow attacks such as SYN port scans, SSH brute forcing, or HTTP connection exploits, which do so by stealthily adding only a few packets to the network. In this work we explore how the combination of programmable switches, Smart network interface cards (sNICs), and hosts can enable fine-grained analysis of every flow in a cloud network, even those with only a small number of packets. We focus on analyzing packets at the start of each flow, as those packets often can help indicate whether a flow is benign or suspicious, e.g., by detecting an attack which fails to complete the TCP handshake in order to waste server connection resources. Our approach leverages the high-speed processing of a programmable switch while overcoming its primary limitation – very limited memory capacity – by judiciously sending some state for processing to the sNIC or the host which typically has more memory, but lower bandwidth. Achieving this requires careful design of data structures on the switch, such as a bloom filter and flow logs, and communication protocols between the switch, sNIC, and host, to coordinate state. 

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5. Poster: A Fast Monitor for Slow Network Attacks

   https://doi.org/10.1109/Cloud-Summit61220.2024.00032  

   Wei, Cuidi; Tu, Shaoyu; Hasegawa, Toru; Koizumi, Yuki; Ramakrishnan, K K; Takemasa, Junji; Wood, Timothy (June 2024, IEEE)

   Recent work has demonstrated how programmable switches can effectively detect attack traffic, such as denial-of- service attacks in the midst of high-volume network traffic. However, these techniques primarily rely on sampling- or sketch- based data structures that can only be used to approximate the characteristics of dominant flows in the network. As a result, such techniques are unable to effectively detect slow attacks such as SYN port scans, SSH brute forcing, or HTTP connection exploits, which do so by stealthily adding only a few packets to the network. In this work we explore how the combination of programmable switches, Smart network interface cards (sNICs), and hosts can enable fine-grained analysis of every flow in a cloud network, even those with only a small number of packets. We focus on analyzing packets at the start of each flow, as those packets often can help indicate whether a flow is benign or suspicious, e.g., by detecting an attack which fails to complete the TCP handshake in order to waste server connection resources. Our approach leverages the high-speed processing of a programmable switch while overcoming its primary limitation - very limited memory capacity - by judiciously sending some state for processing to the sNIC or the host which typically has more memory, but lower bandwidth. Achieving this requires careful design of data structures on the switch, such as a bloom filter and flow logs, and communication protocols between the switch, sNIC , and host, to coordinate state. 

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