International Association
for Cryptologic Research

Pseudo-random correlation generators based on the Quasi-Abelian syndrome decoding problem were first attacked in an article published at Asiacrypt~2025, using compressed sensing. In this paper, we revisit the security of the problem using a more traditional cryptanalytic tool, namely correlation attacks.

As a result, we get a new cryptanalysis which outperforms the attack from Asiacrypt 2025 in several directions. It allows recovery of secret error polynomials with larger Hamming weights, runs approximately $1\,000$ times faster and uses $1\,000$ times less memory over $\mathbb{F}_3$. Over $\mathbb{F}_4$, the speed-up and memory gain are even higher.

Due to this new attack, it becomes necessary to entirely revisit the parameters of several pseudo-random correlation generator proposals, including FOLEAGE.

Threshold cryptography distributes trust among multiple parties by enabling joint cryptographic operations without reconstructing secret keys. While post-quantum signature schemes based on the MPC-in-the-Head (MPCitH) paradigm are highly generic, recent impossibility results show that their thresholdization either incurs prohibitive distributed symmetric computations or leads to signature sizes growing with the number of signers. Achieving practical tradeoffs in this setting remains challenging. In this paper, we propose a generic framework for threshold MPCitH signatures based on Merkle-tree commitments. Our approach adapts the PIOP+PCS paradigm to the distributed setting by introducing and instantiating the notion of threshold polynomial commitment schemes (TPCS). We present a generic compiler combining a PIOP, a TPCS, and an arithmetic black box into a threshold signature scheme, and prove its unforgeability from the security of its components. We further provide a concrete Merkle-tree-based TPCS achieving moderate signature-size overhead, as low as 200 bytes per signer at the 128-bit security level. This is to be compared with an overhead of roughly 2 kB per signer for the previously suggested approach to thresholdize MPC-in-the-Head based on GGM trees. By compiling this TPCS with a standard PIOP, we obtain a generic threshold signature scheme from any hard problem or one-way function, which we showcase MQ-based and AES-based instantiations.

Functional adaptor signatures (FAS) are a novel cryptographic primitive introduced at CCS'24 that enable privacy-preserving, fine-grained data-payment exchanges between a seller and a buyer in a trustless and atomic manner. In this setup, the seller holds sensitive data \(x\) (e.g., patient records, climate data), and the buyer specifies a function \(f\) (e.g., aggregate, sum). FAS guarantees that the buyer learns \(f(x)\) (and nothing beyond) if and only if the seller receives payment in blockchain-based tokens. Unlike generic smart contracts, FAS-powered solutions excel in privacy, efficiency, and compatibility with diverse blockchain systems. However, prior FAS constructions were limited to linear functions (where $f$ was linear in $x$), restricting their applicability to more complex and prevalent applications including data analytics and ML model evaluations.

In this work, we extend the capabilities of FAS to support higher-degree functions \((\textit{deg} \geq 2)\), significantly broadening its range of applications. Our core contribution is a novel FAS design leveraging homomorphic encryption, which simultaneously achieves enhanced efficiency and compatibility for general functions. This approach diverges fundamentally from the restricted design in CCS'24 which relied on connections to functional encryption. We implement our homomorphic encryption-based FAS for functions arising in applications such as data analytics and machine learning inference. Remarkably, even for linear functions, our new design achieves an order-of-magnitude improvement in performance compared to CCS'24 constructions. Furthermore, our solutions seamlessly integrate with prominent blockchain systems, requiring only a basic signature verification script on standard transactions, thus ensuring practical deployability. As a conceptual contribution, we introduce the general paradigm of a blockchain-based functional fair exchange (FFE) protocol, rigorously define buyer and seller fairness, and show that FAS implies the general goal of FFE.

Cryptocurrency lending is growing rapidly, and smart-contract-based loans are expected to grow further. However, existing systems are fundamentally limited: they only operate on smart-contract-enabled blockchains, and assets from other blockchains can be used only via tokenized representations.

In this work, we propose an oracle-aided cryptographic protocol that implements the logic of collateralized loans without smart contracts, instead only requiring basic transactions from the underlying blockchain and hence, being compatible with limited-scripting blockchains, including Bitcoin.

For that, we introduce verifiable graph encryption for signatures (VGES), a new cryptographic primitive that, on input a graph modeling the correspondence between transactions for collateral distribution (vertices) and loan repayments (edges), permits to encrypt the signatures on collateral-distribution transactions ensuring: (1) a signature can only be decrypted after completing loan repayments corresponding to a valid path in the graph from the root (graph enforcement); and (2) anyone can verify that encrypted signatures are valid and can be decrypted after doing the required loan repayments according to the graph (verifiability).

We present two provably secure constructions of VGES and the evaluation of our implementation shows that they offer a tradeoff between the number of required on-chain transactions and off-chain computation, while both remain efficient on commodity hardware.

The concrete security of multivariate post-quantum signature schemes is coming under increasing scrutiny as the NIST standardisation process for additional signatures approaches its final stages. Among the leading candidates, the security of MAYO and QR-UOV relies on the hardness of the underdetermined multivariate quadratic (MQ) problem. This work revisits Hashimoto's algorithm for solving underdetermined systems of MQ equations, reinterpreting it as a computation of a pseudo-oil subspace. In light of this geometric point of view, we design a new algorithm that, by computing richer pseudo-oil structures, distributes algebraic work across more than two Gröbner Basis steps, subdividing the initial MQ problem into multiple subproblems that can be solved separately, while linearising multiple equations. Optimising a set of discrete parameters, we select the best trade-off between algebraic solving and combinatorial search. Concretely, our approach lowers the cost of the direct attack against Security Level I parameter sets of MAYO and QR-UOV by 8 and 10 bits, respectively.

A robust combiner for a cryptographic primitive $P$ takes multiple candidate constructions of $P$ and produces a secure construction of $P$ provided that sufficiently many of the candidates are secure. A closely related notion is that of a security amplifier, where given a weakly secure construction of $P$, we aim to obtain a (strongly) secure one. Intuitively, one may expect that any robust combiner should act as an amplifier by thinking of "good randomness" as inducing secure instances, and of "bad randomness" as inducing insecure instances. Formalizing this intuition, however, has turned out to be challenging. Despite significant progress, general results remain limited and confined either to specific primitives or only to the statistical setting.

We establish a new framework of robust indistinguishability combiners, which greatly extends the class of combiners covered by prior work, and prove that they inherently act as security amplifiers. Our results extend to the computational setting, provided that the combiner makes a single query to each candidate. The new framework allows us to rederive previously known amplification results in a simplified manner, as well as prove new amplification results that have so far been out of reach.

As our main application, we present the first security amplifier for functional encryption, resolving an open question that first arose in constructions of indistinguishability obfuscation, and for which a gap was discovered in previous proofs. Our amplifier transforms a weak scheme with any constant indistinguishability error into one with full negligible security.

The SHA-2 family is a U.S. federal standard and mainly includes SHA-256 and SHA-512. In particular, SHA-256 plays a central role in real-world applications and is widely regarded as one of the most important hash functions in use today. At CRYPTO 2026, Li et al. proposed collision attacks up to 37-step SHA-2, but they could not reach 38 steps due to the low-probability uncontrolled part in the corresponding differential characteristics. In this paper, we propose an improved search procedure to find high-quality differential characteristics for 38-step SHA-256 and SHA-512, respectively. Exploiting the special shape of the 38-step differential characteristics, the meet-in-the-middle method to fulfill the corresponding differential conditions is extremely memory-efficient. Consequently, we successfully achieve the first 38-step collision attack on both SHA-256 and SHA-512, whose time complexity is $2^{104.3}$ and $2^{125.4}$, respectively. The memory complexity of the 38-step collision attack is negligible. The methods are also applied to the 36-step and 37-step collision attacks on SHA-2 published at CRYPTO 2026, leading to a significant improvement in both time and memory complexity. In particular, the time complexity of the collision attack on 36-step SHA-256 is only $2^{58.1}$ and the memory complexity is negligible, implying that a practical collision can be found. More remarkably, we apply the new method to 39 steps of SHA-2 and obtain the first effective collision attack on 39-step SHA-512, with a time complexity of $2^{178}$ and negligible memory complexity. However, the method does not yield an effective collision attack on 39-step SHA-256 due to the same issue arising from the low-probability uncontrolled part. Overall, this work further pushed the limit of memory-efficient collision attacks on round-reduced SHA-2 and significantly advances the state of the art.

Pre-constructed Publicly Verifiable Secret Sharing (PPVSS) extends conventional Publicly Verifiable Secret Sharing (PVSS) by requiring the dealer to publish a commitment or encryption of the shared secret, enabling more efficient and versatile constructions for a variety of cryptographic protocols. In this paper, we further enhance this paradigm by introducing Packed Pre-constructed PVSS (3PVSS), which allows a dealer to encode multiple secrets within a single polynomial while maintaining the pre-constructability property. We present two constructions of 3PVSS schemes. In the first construction, the dealer publishes a single commitment to all shared secrets, providing a compact representation that is particularly suitable for applications requiring efficient communication. In the second construction, the dealer publishes individual commitments to each secret, enabling greater flexibility in applications that require independent verification of multiple shared values. Both schemes preserve the key advantages of PPVSS, including the optimistic reconstruction approach enabled by pre-constructability. We demonstrate that these two variants naturally support different applications. Using the first 3PVSS construction, we revisit the ALBATROSS randomness generation protocol proposed by Cascudo and David (ASIACRYPT 2020) and present a more efficient variant with reduced computation and communication costs. As an application of the second construction, we extend the universally verifiable e-voting protocol recently proposed by Baghery, Knapen, Nicolas, and Rahimi (ACNS 2025) to support multi-candidate elections, while preserving universal verifiability. Our results show that the resulting protocols outperform their original counterparts in terms of efficiency.

This paper introduces AuditPay, a novel mechanism for blockchain mixers that enables controlled oversight through an ``auditing budget.’’ Auditors may monitor up to a budgeted number of addresses per epoch (e.g., an hour or a day), without revealing to users which addresses are monitored. Unlike traditional approaches that require users to voluntarily disclose viewing keys to trusted gatekeepers, AuditPay cryptographically enforces auditing compliance while preserving privacy for non-monitored user addresses and without introducing additional trust assumptions.

At the core of AuditPay’s design is a selective encryption mechanism coupled with an efficient audit-key encoding scheme, enforced by a lightweight zero-knowledge proof. Users encrypt audit-relevant information under an audit key, which permits decryption only if the payment is to (or, alternatively, from) an address selected by the auditor for monitoring.

We implement AuditPay as an Ethereum-based payment mixer and show through experiments on our prototype that its performance and gas-cost overheads are modest, providing a practical solution for balancing payment oversight with user privacy.

ML-KEM (FIPS 203) draws a fresh 32-byte coin at each encapsulation. The shared secret is a deterministic function of the public key and this coin, so a known coin is a recovered key. This is elementary. We ask instead how well the coin's secrecy is protected in practice, and we answer by experiment. On six unmodified libraries (OpenSSL 3.5, wolfSSL 5.9, AWS-LC, Go 1.26, Bouncy Castle 1.83, and CIRCL), and a from-scratch reference, the coin-recovery is reachable in every one; what differs is the guard, from a test-walled package in Go to an ordinary production call in wolfSSL. A second path needs no injection function at all: substituting the generator at build time makes the ordinary encapsulation predictable, while the public re-seed interface correctly refuses to. Outside the validated FIPS-140-3 configuration that most deployments do not yet use, the coin's secrecy rests on convention, not construction. The predictability this permits is externally invisible and parameter-controlled, of the class shown once before in Dual_EC_DRBG. We claim no backdoor; we claim only that the door is reachable, and say so while it is still being closed.

One of the main hallmarks of proof-of-work (PoW) consensus protocols is their ability to adjust the difficulty of the PoW, so that it accurately reflects the level of participation and hence maintains security in a setting where protocol participation is unknown and may over time change dramatically. Importantly, this enables the protocol to retain its fundamental characteristics (such as the regularity of dispensing new tokens) irrespectively of the number of parties running the protocol (also known as ``miners'') at any given time.

The speed with which difficulty can be adjusted is a fundamental feature of a blockchain protocol: The faster the rate with which the difficulty is adjusted, the more agile the protocol is in the face of fluctuating participation. In this work, we put forward, for the first time, a blockchain protocol that performs difficulty adjustment in constant time; prior provably secure designs only offered protocols with, at best, poly-logarithmic overhead for difficulty adjustment. Our construction is based on the parallel-chain approach and a new target recalculation function that adjusts mining difficulty making use of information from all chains in the past epoch via a novel application of approximate-agreement techniques that may be of independent interest.

Tweakable block ciphers are important cryptographic primitives for secure memory encryption and partial mitigation of bit flip attacks. Rapid advancements in data-intensive applications such as artificial intelligence and machine learning have motivated the development of new memory technologies with very large data bus widths requiring wide-block memory encryption and its efficient implementation. Recently, the MATTER family of wide-block tweakable ciphers has been proposed for memory encryption in emerging applications. MATTER is a 512-bit balanced Feistel construction which uses the light-weight ASCON permutation as its round function. In this work, we present a comprehensive design space exploration of hardware architectures for accelerating different configurations of MATTER. We provide a detailed comparative analysis of power, performance, area and energy of round-based, unrolled and pipelined hardware implementations of MATTER based on digital synthesis using a 7nm FinFET ASIC standard cell library. We also discuss the suitability of these architectures for different application-specific memory encryption hardware requirements in emerging edge computing systems.

We give several examples of families of polynomials $p_1, ... , p_t \in \mathbb R[x_1, ... , x_n]/\langle x_i^d - 1\rangle_i$ on which the Low-Norm Nullstellensatz Hypothesis of [Devadas-Hopkins-Kalai-Kothari-Lombardi-Mathialagan, STOC 2026] fails to hold. That is, we prove the existence of polynomials $f \in \langle p_1, ... , p_t\rangle$ with coefficient $L^1$ norm $||f||_1 = 1$ but such that every decomposition $f = \sum_i p_i \cdot q_i$ has cost $\sum_i ||q_i||_1 = 2^{\Omega(n)}$. Our examples include one with $d=2$, the regime originally studied by [Devadas et al.], as well as generalizations that would also have sufficed for their purposes.

Our counterexamples highlight an important class of polynomials for (potentially) falsifying the LNNH: for prime $d$, functions $f(x) = f_C(x)=\frac 1 {|C|}\sum_{c\in C} x^c$ that are indicator functions for the input $x \in \mu_d^n\simeq \mathbb Z_d^n$ belonging to a linear subspace $C^\bot \subset \mathbb Z_d^n$, or more generally a coset $C^\bot + \sigma$.

Proxy re-encryption (PRE) enables a semi-trusted proxy to transform a ciphertext under one key into a ciphertext decryptable under another key without learning the underlying plaintext. Existing lattice-based PRE schemes that achieve security against honest re-encryption attacks (HRAs) typically rely on noise flooding during re-encryption to statistically hide dependencies on the original ciphertext and the re-encryption key. However, noise flooding substantially increases ciphertext noise and often causes significant parameter growth.

In this work, we present a single-hop owner-encrypted proxy re-encryption (oePRE) scheme that achieves HRA security without statistical noise flooding. In the owner-encrypted setting, ciphertexts are generated directly by the data owner using her secret key, resulting in a simpler noise structure that facilitates efficient re-encryption. Instead of statistically hiding the inherited ciphertext noise, our construction introduces a small deterministic padding error and relies on computational leakage masking.

To formalise this approach, we introduce the noisy error-leakage LWE (NEL-LWE) assumption, which models the hardness of distinguishing LWE samples given a noisy version of the error term. We show that NEL-LWE follows from the recent Leaky-LWE framework of Lai, Swarnakar, and Woo (CiC'25). We further define computational re-encryption simulatability for owner-encrypted PRE and prove that our BGV-style construction achieves HRA security under standard LWE and PRF assumptions.

Compared with flooding-based HRA-secure lattice PRE schemes, our approach requires only a small additional padding noise and therefore remains much closer to the parameter regime of the underlying IND-CPA-secure construction. Our work demonstrates that computational leakage masking provides a viable alternative to statistical noise flooding for practical single-hop lattice-based proxy re-encryption.

Large Language Models (LLMs) are frontier deep learning systems that have achieved remarkable success across a wide range of AI services. However, their substantial computational and memory requirements make them difficult to deploy and run on local hardware. Due to these resource requirements, users often rely on untrusted cloud infrastructure providers to perform model inference. However, outsourcing introduces the challenge of verifying that the returned output is the genuine result of the specified model. In this work, we present DeepProve, the first system to enable efficient end-to-end verification of full LLM inference (i.e., for all generated tokens of a prompt) on untrusted cloud servers using zero-knowledge proofs (ZKPs). In contrast, prior work either provides only a proof-of-concept partial implementation for a single token (zkGPT, USENIX'25), or focuses exclusively on specific components of the inference pipeline, such as Softmax (zkLLM, CCS'24).

DeepProve achieves end-to-end verification by certifying the correctness of the output sequence rather than encoding the expensive inference computation in-circuit, an approach that would require either circuit size quadratic in the sequence length or costly in-circuit modelling of RAM operations. The core building blocks of DeepProve are sum-check protocol and lookup arguments, which enable efficient proof of correctness of all operators needed for GPT-2 and Gemma 3, such as multi-head attention and layer normalization for GPT-2, and grouped-query attention, root mean square normalization, and rotary positional embeddings for Gemma 3. Our evaluation shows that DeepProve can prove inference of GPT-2 and Gemma 3 at approximately 174 and 86 tokens per minute, respectively, which is 20-60 faster than the state of the art, without any significant loss in accuracy. Verification takes only 1 to 3.7 seconds. By distributing proof computation across multiple nodes, DeepProve can further improve the prover time while reducing the memory requirements for individual machines. With distributed proving, DeepProve can scale the throughput to 1855 tokens per minute. Our work represents the first full system for end-to-end LLM inference verification, thus paving the way for secure and trustworthy AI services.

Revocable and linkable ring signatures ($\mathsf{RLRS}$) were introduced by Zhang et al. (Inscrypt 2019), where a revocation authority (RA) can mandatory revoke the anonymity of the real signer in cases of dispute. However, existing $\mathsf{RLRS}$ constructions face practical challenges. First, the reliance on Public Key Infrastructure (PKI) incurs a substantial burden of certificate management. Second, current schemes suffer from computational or communication overheads that scale linearly with the ring size, hindering their application in large-scale scenarios. Third, prior schemes often assume a fully trusted RA, leaving honest users vulnerable to being framed by a compromised or malicious authority. In this paper, we formalize the notion of Identity-Based Revocable and Linkable Ring Signature ($\mathsf{IB\text{-}RLRS}$), which extends the $\mathsf{RLRS}$ to the ID-based setting and bypasses the need for cumbersome PKI management. Specifically, $\mathsf{IB\text{-}RLRS}$ ensures that the real signer's identity can always be extracted, and that a malicious RA cannot frame honest users who did not participate in the signature generation. Based on the IEEE P1363 standard, a secure $\mathsf{IB\text{-}RLRS}$ scheme is proposed. Specifically, we design a novel ring signature construction featuring logarithmic signature size that requires no trusted setup, and formally prove its security in the random oracle model.

Abstract. The TWEAKEY framework provides a generic construction for designing tweakable block ciphers. Prominent instances are Deoxys-BC and SKINNY, which have been standardized by ISO/IEC. In this paper, we analyze the tweakey schedules of these ciphers and identify strong dependencies between certain subtweakeys, which we call strong key bridges. We then exploit these dependencies in rectangle attacks under the related-tweakey setting. Moreover, we develop a comprehensive constraint programming model to search for rectangle attacks. Our model not only unifies the distinguisher and the key-recovery part while permitting arbitrary key-guessing strategies, but also integrates three new components, i.e., the state-test technique, explicit last-step computation, and the strong key bridges. As a result, we obtain significantly improved cryptanalytic results on both Deoxys-BC and SKINNY. For Deoxys-BC-384 and Deoxys-BC-256, we reduce the time complexity by a factor of $2^{40}$ and $2^{32}$, respectively, yielding the best attacks to date. Moreover, we extend the longest existing attacks on the authenticated encryption schemes Deoxys-I-256 and Deoxys-I-128 by one round. For SKINNY, we improve upon prior best attacks by one more round for SKINNY-128-384 and by two more rounds for SKINNY-64-192.

Public permissionless ledgers are append-only by design, yet are increasingly asked to host data subject to statutory erasure obligations (GDPR Art. 17, EDPB Guidelines 02/2025). The prevailing cryptographic response, rewriting the chain via chameleon hashes and redactable-blockchain constructions, is structurally unavailable on Bitcoin and Ethereum mainnet. This SoK systematizes the orthogonal application-layer design space, in which the ledger is left untouched and erasure is achieved by destroying the key material required to read the on-chain bytes. We organise the literature along two axes, data locus (on-chain ciphertext, anchor-only, or hybrid) and key custody (single-custodian, threshold, time-lock, or witness-encryption), into a twelve-cell grid with canonical constructions from 2006 to 2026. We extend standard IND-CCA security with a key-lifecycle adversary model parametrised by HSM side-channel leakage, coercion fraction over the custody committee, and algorithmic-break horizon, and establish an equivalence proposition between the resulting Destruction-IND notion and the EDPB "render unrecoverable" criterion.

Evaluating seven reference architectures against eleven engineering, cryptographic, and regulatory criteria, including a production RegTech engine processing more than 10^4 events per second, we find that the literature has concentrated on chain-rewriting while the application-layer branch lacks a common threat-model vocabulary. We close this gap and identify five open problems: post-quantum equivalence, forward-secure destruction under leakage, decentralised lifecycle audit (with a multi-custody extension covering encrypted mempools), composition with ZKP selective disclosure, and erasure under multi-regime retention conflict.

End-to-end encryption (E2EE) provides strong confidentiality guarantees to users by preventing service providers from accessing their data. At the same time, it introduces new operational challenges, most notably the restoration of an E2EE-protected backup on a new device after loss of the original device. In recent years, major instant messengers have deployed increasingly sophisticated key-retrieval schemes for encrypted backups, ranging from simple recovery codes to designs that depend on trusted hardware or advanced cryptographic primitives such as oblivious pseudorandom functions (OPRFs), threshold OPRFs, and secret sharing. While recent work has largely emphasized stronger cryptographic guarantees, the practical costs and trust assumptions implied by hardware dependencies and complex primitives are often not made explicit.

We present a structured framework for the comparative evaluation of E2EE backup key-retrieval schemes across usability, deployability, and security properties, and apply it to simple recovery codes, real-world deployments, and recent proposals from the literature, explicitly distinguishing recovery that depends on user-chosen low-entropy secrets from recovery using high-entropy material. Our evaluation shows that schemes whose recovery ultimately relies on user-chosen low-entropy secrets can provide substantially weaker resistance against large-scale adversaries than an approach using simple recovery codes. Even when assuming high-entropy recovery secrets, many recovery protocol designs introduce additional trust assumptions and potential single points of failure (e.g., compromise of specialized components or trusted setups) that can amplify the impact of large-scale adversaries. Overall, our results highlight that added system complexity often trades off against limited security gains under realistic threat models, motivating clearer accounting of cost and distribution of trust in future designs.

Stateful hash-based signature schemes such as XMSS and LMS are increasingly important in post-quantum cryptographic deployments, yet their verification paths remain difficult to fuzz effectively because key generation is substantially more expensive than verification. This paper presents a structured libFuzzer methodology for testing stateful hash-based signature verification in liboqs. The proposed approach uses pre-computed Known Answer Test (KAT) vectors to initialise valid public key, signature, and message buffers once during harness setup, enabling high-throughput mutation of verification inputs without repeated key generation.

Using this methodology, we implemented and upstreamed two fuzz harnesses targeting XMSS/XMSSMT and LMS/HSS-LMS verification paths in liboqs. A ten-minute AddressSanitizer-enabled fuzzing campaign identified an OID-confusion heap-buffer-overflow in xmssmt_core_sign_open, assigned CVE-2026-46344. The flaw occurs when attacker-controlled public-key OID bytes derive a parameter set whose expected signature length exceeds the caller-allocated buffer, resulting in an out-of-bounds read during signature parsing. The issue was reproduced using a five-byte minimal crashing input and a standalone C reproducer, disclosed through the Open Quantum Safe coordinated disclosure process, and fixed in liboqs 0.16.0.

We further identify a mutation-distribution bias affecting short-input LMS fuzzing and resolve it using a round-robin field-rotation strategy. The resulting framework provides a reproducible and upstream-integrated methodology for adversarial testing of stateful post-quantum signature verification implementations.