NIST's PQC standardization process is in the third round, and a first final choice between one of three remaining lattice-based keyencapsulation mechanisms is expected by the end of 2021. This makes studying the implementation-security aspect of the candidates a pressing matter. However, while the development of side-channel attacks and corresponding countermeasures has seen continuous interest, fault attacks are still a vastly underdeveloped field. In fact, a first practical fault attack on lattice-based KEMs was demonstrated just very recently by Pessl and Prokop. However, while their attack can bypass some standard fault countermeasures, it may be defeated using shuffling, and their use of skipping faults makes it also highly implementation dependent. Thus, the vulnerability of implementations against fault attacks and the concrete need for countermeasures is still not well understood. In this work, we shine light on this problem and demonstrate new attack paths. Concretely, we show that the combination of fault injections with chosen-ciphertext attacks is a significant threat to implementations and can bypass several countermeasures. We state an attack on Kyber which combines ciphertext manipulation-flipping a single bit of an otherwise valid ciphertext-with a fault that "corrects" the ciphertext again during decapsulation. By then using the Fujisaki-Okamoto transform as an oracle, i.e., observing whether or not decapsulation fails, we derive inequalities involving secret data, from which we may recover the private key. Our attack is not defeated by many standard countermeasures such as shuffling in time or Boolean masking, and the fault may be introduced over a large execution-time interval at several places. In addition, we improve a known recovery technique to efficiently and practically recover the secret key from a smaller number of inequalities compared to the previous method.

Single-trace attacks are a considerable threat to implementations of classic public-key schemes, and their implications on newer lattice-based schemes are still not well understood. Two recent works have presented successful single-trace attacks targeting the Number Theoretic Transform (NTT), which is at the heart of many lattice-based schemes. However, these attacks either require a quite powerful side-channel adversary or are restricted to specific scenarios such as the encryption of ephemeral secrets. It is still an open question if such attacks can be performed by simpler adversaries while targeting more common public-key scenarios. In this paper, we answer this question positively. First, we present a method for crafting ring/module-LWE ciphertexts that result in sparse polynomials at the input of inverse NTT computations, independent of the used private key. We then demonstrate how this sparseness can be incorporated into a side-channel attack, thereby significantly improving noise resistance of the attack compared to previous works. The effectiveness of our attack is shown on the use-case of CCA2 secure Kyber k-module-LWE, where k ∈ {2, 3, 4}. Our k-trace attack on the long-term secret can handle noise up to a σ ≤ 1.2 in the noisy Hamming weight leakage model, also for masked implementations. A 2k-trace variant for Kyber1024 even allows noise σ ≤ 2.2 also in the masked case, with more traces allowing us to recover keys up to σ ≤ 2.7. Single-trace attack variants have a noise tolerance depending on the Kyber parameter set, ranging from σ ≤ 0.5 to σ ≤ 0.7. As a comparison, similar previous attacks in the masked setting were only successful with σ ≤ 0.5.

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The Number Theoretic Transform (NTT) is a major building block in recently introduced lattice based post-quantum (PQ) cryptography. The NTT was target of a number of recently proposed Belief Propagation (BP)-based Side Channel Attacks (SCAs). Ravi et al. have recently proposed a number of countermeasures mitigating these attacks.In 2021, Hamburg et al. presented a chosen-ciphertext enabled SCA improving noise-resistance, which we use as a starting point to state our findings. We introduce a pre-processing step as well as a new factor node which we call shuffle node. Shuffle nodes allow for a modified version of BP when included into a factor graph. The node iteratively learns the shuffling permutation of fine shuffling within a BP run.We further expand our attacker model and describe several matching algorithms to find inter-layer connections based on shuffled measurements. Our matching algorithm allows for either mixing prior distributions according to a doubly stochastic mix matrix or to extract permutations and perform an exact un-matching of layers. We additionally discuss the usage of sub-graph inference to reduce uncertainty and improve un-shuffling of butterflies.Based on our results, we conclude that the proposed countermeasures of Ravi et al. are powerful and counter Hamburg et al., yet could lead to a false security perception – a powerful adversary could still launch successful attacks. We discuss on the capabilities needed to defeat shuffling in the setting of Hamburg et al. using our expanded attacker model.Our methods are not limited to the presented case but provide a toolkit to analyze and evaluate shuffling countermeasures in BP-based attack scenarios.