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📑 Papers
deploymentsafety.openai.compaper

GPT-Rosalind-6 System Card Addendum

GPT-Rosalind-6 System Card Addendum is OpenAI's safety documentation for a life-sciences model that shares weights with GPT-6 Astra. It rates the model High in Biological and Chemical and Critical in Cybersecurity under the Preparedness Framework. It reports biology evaluations, trusted-access controls, biosecurity refusal pass rates, a historical cyber jailbreak regression (14.3% task success), and sabotage and monitor-evasion results.

GPT-Rosalind-6GPT-6 AstraOpenAI
Preparedness FrameworkGPT-Rosalind-5.5ExploitBench+5

AI Security, GRC· Published and added 30 Oct 2026

arxiv.orgpaper

TextSeal2: Distortion-Free LLM Watermarking with Copula Mixing and Memoryless Races

TextSeal2 is a distortion-free LLM text watermark that merges two or more keys into one virtual key and couples it to fresh noise through AutoMark's Gaussian copula. Under speculative decoding it verifies keyed drafts with an extra exponential race, so output matches the target model and acceptance rate is unchanged. On three LLMs at a 10^-3 false-positive rate, it detects 8 to 22 points more 100-token answers than TextSeal.

TextSeal2TextSealAutoMark+2
Gumbel-max schemespeculative decodingGaussian copula+1

AI Security· Added 31 Oct 2026, published 29 Oct 2026

arxiv.orgpaper

Understanding and Mitigating Role Spoofing in LLMs

Understanding and Mitigating Role Spoofing in LLMs is an arXiv paper (October 2026) on role spoofing, a prompt injection where malicious tool output impersonates the user. It shows models track "who said what" using both content cues (semantics, style) and structure cues (control tokens, formatting). Attacks combining fake structure and content succeed often, adversarial training stops only content-based attacks, and linear probes trained to predict conversation roles detect spoofing across settings.

LLM
role spoofingrole confusionprompt injection+1

AI Security· Added 31 Oct 2026, published 29 Oct 2026

arxiv.orgpaper

SEAL: Sealed Queries for Local Sanitization against Indirect Prompt Injection

SEAL is a defense against indirect prompt injection for local LLM agents. It learns a soft prompt and scoring readout offline, then uses a frozen task model to score and delete injected tokens from tool outputs, with queries built from trusted initial context. On AgentDojo, attack success falls from 34.6% to 0.1% and Joint rises from 51.4% to 77.5%, using about 127x fewer defense tokens than PISanitizer.

LLMAgentDojoAgentDyn+1
indirect prompt injection

AI Security· Added 31 Oct 2026, published 29 Oct 2026

arxiv.orgpaper

REALM: Identifying Minimal Task Assets for LLM Agents

REALM (Required Execution Assets Linked to a Mission) is an approach to applying least privilege to LLM agents by identifying the assets a task needs, including ones discovered at runtime. It models assets as Dependency Graph nodes, separates discovering an asset from authorizing it, and exposes resource-bound Partial APIs inside a Task Container. On AgentDyn with qwen3.5-flash, attack success rate falls from 16.6% to 0.2%, with 40.0% task completion on clean tasks and 36.4% on injected cases.

QwenLLMAgentDyn
prompt injectionleast privilegeREALM

AI Security· Added 31 Oct 2026, published 29 Oct 2026

x.compaper

Cryptography and Security Papers (@FSFG) on X

PrivacyEvalClaw is a tool-augmented deliberative agent that audits privacy leakage in LLM jailbreak responses. The paper is by Krishna Kanth Nakka and co-authors, and it was accepted to AACL-IJCNLP 2026 (arXiv 2610.36711, cs.CR). The tweet gives only the title, authors and venue, so the method and results are not described.

LLM
PrivacyEvalClaw

AI Security· Added 30 Oct 2026, published 29 Oct 2026

arxiv.orgpaper

Appreciation Teaches Unauthorized Execution: Self-Evolution Degrades the Robustness of Personal Agents to Indirect Prompt Injection

Paper studying whether self-evolution weakens personal agents' robustness to indirect prompt injection (IPI). A two-phase method has the user ask the agent to follow tasks in external content, then tests with a third-party injected task the user did not authorize. Against the non-evolving base agent, attack success rose 14.0 to 48.8 points under skill evolution and 3.0 to 39.3 points under reinforcement learning. Code is released.

indirect prompt injection

AI Security· Added 31 Oct 2026, published 29 Oct 2026

arxiv.orgpaper

PCM: A Proof-Carrying Message Protocol for Verifiable Multi-Agent Communication

Proof-Carrying Messages (PCM) is a protocol where each claim an AI agent sends carries evidence: records from an append-only Merkle log the agent cannot write, with inclusion proofs, signed by an attesting signer it cannot control. Receivers verify offline and mark each claim proven, unproven or failed. On 926 messages (712 lies in 16 classes) PCM accepted 10 lies, all stale evidence (1.4%), while plain A2A accepted all 712. Verification takes about 1 ms.

Model Context ProtocolA2AuAgents
prompt injectionRFC 9421SCITT+3

AI Security· Added 31 Oct 2026, published 29 Oct 2026

deploymentsafety.openai.compaper

Addendum to GPT-6 Luna System Card: October 28, 2026 Update

Addendum to the GPT-6 Luna system card for the model update of 29 October 2026 (the title says October 28). OpenAI keeps the High rating for cybersecurity and biological/chemical capability under its Preparedness Framework. It reports ExploitBench 46.19% and SEC-Bench Pro 51.75% (GPT-6 Astra: 85.4%), higher multiturn jailbreak defender success than the October 7 version, and GPT-Red prompt-injection results. It also reports weaker factuality and dual-use biology refusal.

GPT-6 LunaGPT-6 AstraOpenAI+1
Preparedness FrameworkGPT-RedExploitBench+4

AI Security· Published and added 29 Oct 2026

x.compaper

Cryptography and Security Papers (@FSFG) on X

Log-To-Leak is an arXiv paper (cs.CR, cs.AI) by Yuepeng Hu, Chongyu Fan, Sirat Samyoun and Jian Du on prompt injection attacks against tool-using LLM agents through the Model Context Protocol. The title points to a logging-based data leakage channel. The fetched page holds only the title, authors and arXiv link, with no abstract, so the method and results are not visible here.

Model Context ProtocolLLM
Log-To-Leakprompt injection

AI Security· Added 29 Oct 2026, published 28 Oct 2026

ethresear.chpaper

Secure Transaction Verification and Authorization (STVA)

Secure Transaction Verification and Authorization (STVA) is a draft Standards Track ERC (created October 2026) by @MATOBOYCRYPTO65. It proposes structured human-readable metadata and semantic intent for transactions and UserOperations, an independent simulation and verification interface, and scoped, revocable capability tokens for privileged operations. It targets blind signing and frontend supply-chain attacks, citing the February 2025 Bybit Safe multisig theft. The page gives only the abstract, motivation and core concepts.

EthereumSafe
BybitEIP-712ERC-1271+5

Blockchain· Published and added 28 Oct 2026

eprint.iacr.orgpaper

Shor's algorithm compiled on cat qubits: 22 593 qubits for RSA-2048 in 3.14 days

Shor's algorithm compiled on cat qubits is an IACR ePrint (2026/2665) giving an end-to-end resource estimate on superconducting cat qubits, using repetition and LDPC cat codes. Factoring RSA-2048 needs about 23,000 cat qubits and 3.14 days, assuming phase-flip noise p_Z = 5e-4 and no bit-flips. secp256k1 ECDLP needs at most 30,000 qubits and 1 hour. A space-for-time trade runs RSA-2048 in 1.25 hours on about 611,000 qubits.

Bitcoin
Shor's algorithmRSA-2048secp256k1+5

other· Published and added 28 Oct 2026

eprint.iacr.orgpaper

Beyond the Event Horizon of Keccak, Extending the Observation from 2011 and applications

Beyond the Event Horizon of Keccak extends a 2011 observation that a path in the Keccak sponge from a zero-capacity state back to one yields infinite second-preimage families. Three theorems cover loops from any capacity value x, k-block loops and cycles, and Joux-style multicollisions with search cost independent of k. Verified examples run on Keccak-f[200] and Keccak-f[1600] with c=32; it also proposes bridge-based protocols.

KeccakSHA-3Lean
Danilo GligoroskiJoux multicollisionssecond preimages+2

other· Published and added 28 Oct 2026

arxiv.orgpaper

When LLM Architectures Meet Smart Contract Vulnerability Detection: a Replication Study

This arXiv paper (October 2026) replicates Chen et al.'s study of LLM-based smart contract vulnerability detection. It confirms the high-recall, low-precision pattern on GPT-4, then tests Mixture-of-Experts and RNN-like models plus a preliminary State Space Model run. Gemma-3 matches GPT-4's profile despite far fewer parameters, while two Mixture-of-Experts models diverge, so architecture family alone does not predict detection behavior.

GPT-4GemmaLLM
Chen et al.

AI Security, AppSec· Added 30 Oct 2026, published 28 Oct 2026

arxiv.orgpaper

Session-Bound Behavioral Watermarking for Autonomous LLM Agents

AgentAnchor is a session-keyed behavioral watermark for attributing LLM agent trajectory logs to an owner. It derives per-step keys from a secret key, a fresh public session ID and semantic observation states, and embeds parity evidence through a KL-bounded exponential tilt. The paper formalizes learned cross-session forgery, and a trusted verifier checks disputed logs using wrong-key calibration and abstention.

LLM
AgentAnchorlearned forgery

AI Security· Added 30 Oct 2026, published 28 Oct 2026

arxiv.orgpaper

Post-Training Large Language Models with LLMON

LLMON (LLM Object Notation) is a framework that separates instructions from data and requires explicit identifier-based execution. The authors post-train Granite-4.1 3B and 8B base models with SFT then RL on a 4.6B-token structured corpus covering general, RAG and tool-calling data, with distractor variants. Attack success rates on indirect prompt-injection benchmarks fall from 53-100% to 0.02-5.6%, and general capability is preserved. Attention-based metrics diagnose failures per transformer layer.

LLMONGranite 4.1LLM
prompt injectionindirect prompt injection

AI Security· Added 30 Oct 2026, published 28 Oct 2026

arxiv.orgpaper

Structured Security Explanations for Learning-Based Vulnerability Detection

VulnLens is a framework for binary C/C++ function-level vulnerability detection. A label-blind LLM Explainer describes each function from seven fixed perspectives (data flow, memory access, object lifetime, arithmetic and type behavior, control flow, shared state, external-resource access). A supervised Detector fuses code and explanations by cross-attention. It reaches 75.5% accuracy and 77.2% F1 on a 526-function PrimeVul test set, and 66.4% accuracy on SecVulEval without retraining.

LLMCC+++2
VulnLensPrimeVulSecVulEval

AI Security, AppSec· Added 30 Oct 2026, published 27 Oct 2026

eprint.iacr.orgpaper

Tractable, Not Truncated: Colored-Noise TRNG Security via Fractional Brownian Motion

This ePrint paper models oscillator-based TRNG phase noise, both white and flicker, as fractional Brownian motion. It proves a quasi-renewal property that gives closed-form worst-case min-entropy and sampling requirements, and extends spectral and Allan-variance analysis so noise parameters come from a single timing trace. FPGA and ASIC experiments show flicker noise accounts for over 99% of uncertainty at a 0.99 min-entropy target, allowing a bitrate two to three orders of magnitude higher.

FPGAASIC

Hardware & RF· Added 28 Oct 2026, published 27 Oct 2026

arxiv.orgpaper

Heads of Security: Learned Attention Gates Improve Prompt Injection Robustness

Heads of Security (HoS) is a prompt injection defense that enforces instruction-data separation with learned per-head attention gates, redistributing attention between trusted and untrusted tokens. Evaluated on Llama-3.3-70B-Instruct and GPT-OSS-20B against SecAlign++ and ASIDE. The black-box RL-Hammer attack reaches 97% ASR on GPT-OSS-20B and 85% on SecAlign but 10% on HoS. The white-box Claudini attack needs 3 times more FLOPs on HoS. HoS keeps base-model utility in few-shot settings, where SecAlign and ASIDE degrade.

LlamaGPT-OSS-20BLLM
Heads of Securityprompt injectionSecAlign+++4

AI Security· Added 28 Oct 2026, published 27 Oct 2026

eprint.iacr.orgpaper

Radical isogenies on every model

Radical isogenies on every model is an IACR ePrint paper by Thomas Decru (October 2026). It gives radical isogeny steps of every odd degree N directly on short Weierstrass, Montgomery, twisted Edwards, Huff, Jacobi quartic, twisted Hessian, Legendre and Jacobi intersection curves, plus Kummer lines. In Tate normal form a step drops from 12.5N to 10N multiplications. Montgomery and twisted Edwards curves cost 10.5N+O(1) per step and 2N to push a point. All algorithms are inversion-free, with exact operation counts.

CSIDH
Thomas Decruradical isogeniesVélu's formulae+1

other· Added 28 Oct 2026, published 27 Oct 2026

eprint.iacr.orgpaper

Towards Quantum Sensing for Side-Channel Analysis

Preprint on using nitrogen-vacancy (NV) center quantum sensing for electromagnetic side-channel analysis of ICs. The authors build an NV-based RF spectrometer with 1.1 GHz real-time bandwidth and adjustable center frequency, which reads the spectrum in the time domain without Fourier transforms or frequency sweeps. They use it on RSA decryption emanations and for leakage detection on a software Number Theoretic Transform running on a Cortex-M4 microcontroller.

ARM Cortex-M4
Number Theoretic TransformRSAnitrogen-vacancy centers+1

Hardware & RF· Added 28 Oct 2026, published 27 Oct 2026

eprint.iacr.orgpaper

Alg\{Ossa\}: Decentralized Secure Aggregation with Rotating Committees and Eventual Delivery

AlgOssa is a decentralized secure aggregation protocol built on Ossa, a generic committee-aided, single-server construction for one-shot clients (following OPA and Willow, CRYPTO 2025). Ossa realizes secure aggregation with non-selective abort against a malicious server. AlgOssa adds Algorand-style sortition to rotate leaders and committees, bounds the chance of an honest server, and gives eventual delivery. Classical and post-quantum routes are evaluated.

Algorand
OssaAlgOssaOPA+2

other· Added 28 Oct 2026, published 27 Oct 2026

eprint.iacr.orgpaper

Unshuffling Fisher-Yates: Practical Recovery of Length-128 Permutations and Application to ML-DSA

Paper (IACR ePrint 2026/2658) presenting a single-trace side-channel attack on a software Fisher-Yates shuffle of length 128, the butterfly count in one ML-DSA NTT layer. It removes rejection-sampling timing variation, extracts Hamming weight and identity leakage, and enumerates likely permutations with constraint programming. On a shuffled ML-DSA-44 NTT it recovers secret polynomial s1, fully or up to a few coefficients.

ML-DSA
Fisher-Yates shuffleFIPS 204

Hardware & RF· Added 28 Oct 2026, published 27 Oct 2026

eprint.iacr.orgpaper

Poly2MsgLeaks: Certified Key Recovery from Polynomial-to-Message Leakage

Poly2MsgLeaks is a profiled chosen-ciphertext power-analysis attack on the SMAUG-T (TiMER parameter set) post-quantum KEM that recovers the full 512-coefficient PKE secret from six traces on an STM32F415. It recovers 999 of 1,000 unseen secrets and proves an incorrect key is released with probability at most 2^-2095.6. Single-write message assembly and a two-share masked P2M resisted the evaluated six-execution attack.

SMAUG-TSTM32F415
Poly2MsgLeakschosen-ciphertext attackpolynomial-to-message leakage+1

Hardware & RF· Added 28 Oct 2026, published 27 Oct 2026

eprint.iacr.orgpaper

Falcon Key Recovery from Joint Sampler Leakages

Falcon Key Recovery from Joint Sampler Leakages is an ePrint paper presenting a power side-channel attack on Falcon and FN-DSA that fuses three SamplerZ leakages (exponent class of the center, sign bit, proposal magnitude). It turns them into slab and halfspace constraints solved by softplus interval regression, with no LLL or BKZ. On PQClean Falcon-512 (ARM Cortex-M4) it recovered all 50 keys with at most 34 signatures; on c-fn-dsa it recovered 38 of 50 keys within 200 signatures.

FalconFN-DSAARM Cortex-M4+1
SamplerZc-fn-dsasoftplus interval regression+1

Hardware & RF· Added 28 Oct 2026, published 27 Oct 2026

eprint.iacr.orgpaper

OblivDGL: Oblivious Deep Graph Learning Made Practical

OblivDGL is a secure computation framework for GNN training and inference, modelled on Deep Graph Library. It uses an oblivious message-passing paradigm and an oblivious graph representation built on function secret sharing (FSS). It leaks only total node and edge counts. On four benchmark graph datasets it cuts training communication up to 1024x and runtime up to 14.3x against prior secure GNN systems.

Deep Graph LibraryGraph Neural Network
NDSS 2027

AI Security· Added 28 Oct 2026, published 27 Oct 2026

arxiv.orgpaper

Measuring Users' Security and Privacy Concerns About Third-Party Community Bots on Discord

Measurement study of 23,102 third-party Discord bots and 183,142 user reviews (2021-2026, 49 languages). A fine-tuned DeBERTa classifier plus manual validation yields 8,832 security and privacy reviews, mapped to a 31-theme taxonomy; Data Sharing (30.5%) and Data Collection (16.2%) dominate. Permission count and admin status correlate only weakly with user concerns. The authors build BotLens, an MCP-server auditing framework with six tools.

DiscordModel Context ProtocolLLM
BotLensDeBERTa

other, AI Security· Added 28 Oct 2026, published 27 Oct 2026

eprint.iacr.orgpaper

When Algebraic Structure Meets Too Many Hints

"When Algebraic Structure Meets Too Many Hints" is an ePrint paper (2026/2654) arguing that DDGR hint classes and too-many-hints thresholds are not standalone side-channel security metrics. In synthetic Kyber-512 experiments, NTT-domain residues recover the full secret with about half the hints the uniform mod-q bound predicts. Finite-precision FFT samples need 25% to 55% of the budget for uniform perfect hints. No new attack optimizations are proposed.

Kyber-512ML-KEM
DDGRtoo-many-hintsMLWE with Hints+4

Hardware & RF· Published and added 27 Oct 2026

arxiv.orgpaper

What Victims Take Away: Attack Reuse and Defense Revision after Prompt-Injection Attacks

What Victims Take Away is an October 2026 arXiv paper analysing 563,349 Tensor Trust attack records to see how players reuse prompt injections they received. Within a week, targets reused 10.0% of attacks that broke their defense, versus 0.03% of matched attacks. Breaches were followed by defense changes that cut same-family attack success by 24.5 points. Received texts made up 23.2% of successful hijacks. The authors propose that AI security tools describe techniques without disclosing full attack text.

Tensor TrustLLM
prompt injectionpayoff-biased social learningvictim-offender overlap

AI Security· Added 28 Oct 2026, published 27 Oct 2026

eprint.iacr.orgpaper

Analyzing Compiler-induced Constant-time Violations with Compiler at Scale

CTGREP is a compiler-based framework that applies differential analysis across the whole Clang/LLVM compilation chain to find where, how and under which configurations compiler optimizations break constant-time cryptographic code. Applied to seven libraries, three Clang versions, six targets and thousands of configurations, it led to 48 cases fixed with developers. It also identified seven new problematic LLVM passes and bypassed existing compiler-flag mitigations.

LLVMClang
constant-time violationstiming side-channeldifferential analysis+1

Hardware & RF, AppSec· Added 27 Oct 2026, published 26 Oct 2026

arxiv.orgpaper

Log-To-Leak: Prompt Injection Attacks on Tool-Using LLM Agents via the Model Context Protocol

Log-To-Leak is a prompt-injection attack on tool-using LLM agents that abuses Model Context Protocol tool metadata to trigger an attacker-controlled logging call after the last legitimate call, leaking the user query, server name, server response and agent response. Evaluated on five MCP servers and four agents, it reaches 62.64-100% attack success with 76.55-95.64% logging accuracy. Three defenses leave over 55% residual ASR on GitHub MCP with GPT-4o.

Model Context ProtocolGitHubGPT-4o+1
Log-To-Leaktool poisoningprompt injection

AI Security· Added 28 Oct 2026, published 26 Oct 2026

arxiv.orgpaper

Reva: Real-Time Vulnerability Detection through Contextual Probing of Large Language Models

REVA (REal-time Vulnerability Analysis) is an LLM-based vulnerability detector that screens each new function in one forward pass. It feeds the model a pre-computed module threat model, lightweight static analysis findings and call-graph data, then reads the model's internal representations with a trained probe. On PrimeVul's held-out test set with GLM-5.3-Flash it reaches 60.0% accuracy in about one second per function, matching the agentic VulTriage (59.2%) while over 250 times faster.

LLMGLM
REVAVulTriagePrimeVul

AI Security, AppSec· Added 28 Oct 2026, published 26 Oct 2026

eprint.iacr.orgpaper

LINE-Break: Cryptanalysis and Reverse Engineering of Letter Sealing

LINE-Break is a security analysis of Letter Sealing v2, the custom end-to-end encryption protocol in the LINE messenger. A TLS man-in-the-middle attacker or malicious server can replay, reorder and block messages undetected, and colluding users can forge message authorship in one-to-one and group chats. Stickers and URL previews leak plaintext. The attacks were verified on the real iOS app and an independent implementation.

LINEiOS
Letter SealingLetter Sealing v2Diego F. Aranha+1

Mobile Security, Offensive Security· Published and added 26 Oct 2026

arxiv.orgpaper

Cheap AI-Assisted Reverse Engineering and What It Will Do

"Cheap AI-Assisted Reverse Engineering and What It Will Do" is an October 2026 arXiv paper (Computers and Society) arguing that generative AI strains the law of reverse engineering. AI systems can identify hardware components, extract firmware, decompile object code and clone apps, which removes the cost barrier that laws rely on. The authors map these practices onto trade secret, copyright, anti-circumvention, computer misuse and contract law, and sketch possible legal responses with their trade-offs.

Malware & RE, GRC, AI Security· Added 28 Oct 2026, published 26 Oct 2026

eprint.iacr.orgpaper

Revisiting ZMAC+: Birthday-Bound Attacks and a Beyond-Birthday-Bound Repair

ZMAC+ is a tweakable-block-cipher MAC (List and Nandi, ToSC 2017) with claimed beyond-birthday-bound security. This ePrint paper (2026/2647) shows a tag-swap attack: for two-block tags, a distinguisher and a fresh-message forgery with constant success probability using O(2^{n/2}) queries in the ideal-TBC model. It also corrects a counting error in the published Lemma 4 and proposes a repaired variant with an adaptive PRF bound of order q^2/2^{n+min(n,t)}.

ZMAC+
DoveMACZHashZAE+4

other· Published and added 26 Oct 2026

arxiv.orgpaper

Then there is prompt injection, a malicious email, ...: The Wild Wide West of OpenClaw Agentic System Security

An empirical study of security concerns in the OpenClaw AI personal assistant framework, using 25K+ posts from 13 subreddits (162 security-relevant) and 358 security-tagged GitHub issues (180 retained). It maps 521 CWE instances across 59 weakness types, concentrated in access control, sensitive-data exposure, injection and unsafe execution. It extracts 543 practitioner mitigations into seven strategies and reconstructs a sensitive-data exposure path with dummy secrets.

OpenClawGitHubLLM
prompt injectionCWEtrust boundaries+1

AI Security· Added 28 Oct 2026, published 26 Oct 2026

eprint.iacr.orgpaper

Non-profiled Single-Trace ML-DSA Secret Key Recovery by Horizontal Distribution Analysis

Non-profiled single-trace side-channel attack on ML-DSA-65 (Dilithium) running on ARM Cortex-M4, by Linus Backlund and Elena Dubrova (KTH). It compares observed sample distributions with expected Hamming weight leakage using a Gaussian mixture model, and stacks partitioned trace segments for multiple observations. Information-set decoding corrects misclassifications; with a 2^70 enumeration budget, the full secret key is recovered from one trace in 99% of attacks, using secret key unpacking as the attack point.

ML-DSAARM Cortex-M4
Hamming weight leakagehorizontal attacknon-profiled attack+4

Hardware & RF· Published and added 26 Oct 2026

eprint.iacr.orgpaper

Cryptanalysis and Repair of "Decentralized Multi-authority ABE for NC$^1$ from BDH"

Cryptology ePrint 2026/2642 presents a plaintext-recovery attack on the DBDH and CBDH variants of the Datta, Komargodski and Waters multi-authority ABE for NC1 (Journal of Cryptology, 2023). It needs one corrupt authority and two users, and succeeds with probability one in the static model. The flaw is an invalid extension of the Rouselakis-Waters LSSS matrix-normalization lemma. The paper also attacks two Datta-Pal (PKC 2023) attribute-based inner-product schemes and proves repaired versions secure in the random oracle model.

Datta-Komargodski-Waters multi-authority ABEDatta-Pal attribute-based inner-product functional encryptionRouselakis-Waters LSSS matrix-normalization lemma+3

other· Published and added 26 Oct 2026

eprint.iacr.orgpaper

A Memory-efficient Implementation of Wiedemann XL

A Memory-efficient Implementation of Wiedemann XL is an ePrint paper (2026/2641) giving the first efficient on-the-fly implementation of XL with block Wiedemann for the multivariate quadratic problem. It builds on the CCNY SSE implementation, removes column-index tables, and computes column indices with O(n^2) instead of O(n^3) look-ups. It runs in comparable BW1 time with up to five times less memory, and an AVX2 port covers F256, the main field of UOV.

MQOMSNOVAMAYO+7

other· Published and added 26 Oct 2026

eprint.iacr.orgpaper

Subexponential Algorithms for LWE via Rejection Sampling on Superlattices

Subexponential Algorithms for LWE via Rejection Sampling on Superlattices is an ePrint paper by Ligeng Fan, Changpeng Shao, Hongbo Li and Dingkang Wang. It extends the Ducas, Engelberts and Loyer superlattice framework to give a provable classical search-LWE algorithm for prime q in [n^2, 2n^2], using m=4n samples and time and space exp(O(n/ln ln n)). A second variant runs in 2^((1/2+o(1))n/ln R) for general parameters. It resolves a gap left by Kirchner and Fouque.

Ducas, Engelberts and LoyerKirchner and FouqueBKW algorithm+1

other· Published and added 26 Oct 2026

arxiv.orgpaper

Scope-Gap Injection: Exploiting Evaluator Channel Blind Spots in the OpenClaw Agent Security Competition

Scope-Gap Injection (SGI) is an indirect prompt injection method for multi-stage LLM-agent safety pipelines, tested in the IJCAI 2026 OpenClaw Agent Security Attack Competition. The visible task and skill stay benign while target identifiers, bypass parameters and authorization steps sit in an attachment written as a business worklist, which the S2 LLM judge appears not to inspect. SGI bypassed all three stages (static scan, LLM judge, live audit) for 5 of 19 targets, best F = 0.385. Attachment placement had 78% S2 acceptance versus 23% in-skill. The paper closes with defenses that align evaluator scope with agent channels.

OpenClawLLM
Scope-Gap Injectionindirect prompt injectionIJCAI 2026 OpenClaw Agent Security Attack Competition

AI Security· Added 27 Oct 2026, published 26 Oct 2026

eprint.iacr.orgpaper

Private Information Retrieval with Accountability at Erasure-Optimal Server Redundancy

SynTrace is a single-round compiler that adds accountability to linear private information retrieval (PIR). The client mixes the retrieval query with m audit queries, so audit syndromes identify up to d deviating servers among t colluding ones before reconstruction. The paper proves perfect query privacy and zero false identification within the threshold. For Shamir-based PIR it needs k=t+d+1 servers. For a 32 KiB record from a 1 GiB database it uses 2.25 MiB, against 8.96 MiB for the Eriguchi, Kurosawa and Nuida (TCC 2022) homomorphic-MAC construction.

SynTraceEriguchi-Kurosawa-Nuida homomorphic MACTCC 2022

other· Published and added 26 Oct 2026

deploymentsafety.openai.compaper

Addendum to GPT-6 Astra System Card: GPT-6.1 Terra

Addendum to the GPT-6 Astra system card for OpenAI's GPT-6.1 Terra, rated Critical in cybersecurity and High in biological and chemical capability under the Preparedness Framework. It reports multiturn jailbreak and prompt-injection results, alignment tests (auto-review circumvention, ExploitGym honeypot, monitor evasion), and cyber scores: 97.10% ExploitBench, 24.5% on the internal recent-vulnerability port, 5 of 22 Sandbox Bench targets.

GPT-6.1 TerraGPT-6 AstraOpenAI+1
Preparedness FrameworkExploitGymExploitBench+11

AI Security· Published and added 26 Oct 2026

arxiv.orgpaper

SentryBench: A Cost-Sensitive Benchmark for Adversarial Robustness of Tool-Using LLM Agents in Public-Safety Deployments

SentryBench is a benchmark for tool-using LLM agents in public-safety settings (public alerts, responder dispatch, citizen-record queries). It scores attack success, over-refusal and over-reaction on a cost-sensitive frontier, using real emergency-call transcripts and real injection/jailbreak payloads. Across 840 episodes on three frontier models and three defenses, refuse-more caution raised over-refusal to 100 percent on two models, while a trust-gating wrapper gave the lowest harm on every model.

LLM
SentryBenchover-refusalover-reaction+1

AI Security· Added 27 Oct 2026, published 25 Oct 2026

eprint.iacr.orgpaper

Decision Attacks on Known-Covariance Ring-LWE via Public Gram Determinants

Anis Bkakria's ePrint 2026/2638 gives polynomial-time decision attacks on Known-Covariance Ring-LWE (KCov-RLWE), the assumption Micciancio and Suhl introduced for simulation-secure threshold encryption. The public sample and covariance hint form a bordered Gram matrix whose determinant leaks a residual that differs between real and uniform samples. The attacks cover broad prime-modulus families at ring rank one and transfer to composite moduli with an odd prime divisor. Power-of-two moduli are not covered, and the paper does not break the full threshold-encryption scheme.

Ring-LWE
Known-Covariance Ring-LWEMicciancio and SuhlGram determinant+2

other· Added 26 Oct 2026, published 25 Oct 2026

unicode.orgpaper

UTS #39: Unicode Security Mechanisms

UTS #39 (Unicode Security Mechanisms) is the Unicode Consortium's technical standard for detecting identifier spoofing. It defines the General, IDN and Email security profiles for identifiers, confusable detection through skeleton and bidiSkeleton mappings, and mixed-script detection with resolved script sets and Restriction Levels. It also covers limited contexts for ZWJ/ZWNJ and the confusables and identifier data files. The fetched text is truncated, so later sections are not covered.

Unicode
homograph attackconfusableswhole-script confusables+7

AppSec, Learning· Added 26 Oct 2026, published 25 Oct 2026

arxiv.orgpaper

SymLift: Neural Semantic Lifting for Compile-Free Vulnerability Detection in Context-Incomplete Code Fragments

SymLift is a compile-free vulnerability detection framework for context-incomplete code fragments. A fine-tuned LLM lifts control-flow, data-flow, memory and resource relations into a constrained LLVM-like IR. A parser turns the IR into facts, and Datalog rules derive findings with derivation traces. On Juliet function-level fragments Clang compilation success falls to 12.00%, while SymLift's completion rate drops only 1.17 points. SymLift-Qwen-7B reaches Target-F1 94.41% on FormAI and 91.66% micro-F1 on MegaVul.

LLMQwenLLVM+2
SymLiftFormAIJuliet+2

AppSec, AI Security· Added 28 Oct 2026, published 25 Oct 2026

eprint.iacr.orgpaper

Maximum-Likelihood Decoding of Gabidulin Codes Is NP-Hard Even in Dimension One

Philippe Gaborit proves that maximum-likelihood decoding of Gabidulin codes is NP-hard even for dimension one: deciding rank distance at most n-2 from the code {λg} is NP-complete. The reduction is deterministic, so Rank Syndrome Decoding and Rank Minimum Distance for F_{q^m}-linear codes are NP-complete under deterministic reductions, where the earlier reduction was randomized. It goes through a new pivot problem, Twisted Square Membership.

Gabidulin codes
Philippe GaboritGuruswami-Vardy theoremTwisted Square Membership+2

other· Added 26 Oct 2026, published 25 Oct 2026

eprint.iacr.orgpaper

Revisiting AES Key Wrap: Forgery Bounds, Structural Observations, and Recommendations for the Revision of NIST SP 800-38F

Revisiting AES Key Wrap is an ePrint paper (2026/2636) by John Preuß Mattsson, expanded from technical comments to NIST on the SP 800-38F revision. It shows the stated forgery probabilities ignore adaptive attacks and gives corrected bounds for KW, KWP and TKW. It also shows KW lacks beyond-birthday-bound security, since a forgery leaks a plaintext prefix and an encryption-only distinguisher exists.

AES Key WrapAES
NISTNIST SP 800-38FKW+4

other, GRC· Added 26 Oct 2026, published 25 Oct 2026

eprint.iacr.orgpaper

A Kelsey–Kohno Attack Variant against SHA-2 Message Digests in HSS/LMS and XMSS

Falko Strenzke's ePrint 2026/2635 presents a multi-target second-preimage attack on message hashing in HSS/LMS and XMSS with SHA-256 and SHA-256/192. It herds chaining states from many collected signatures into one state, defeating the key and leaf-index prefix. With 2^64 signatures, SHA-256 cost falls from 2^256 to about 2^166 (2^156 at maximal message length). SHAKE256 parameter sets are unaffected.

HSS/LMSXMSSSHA-256+2
Kelsey–Kohno herding attackKelsey–Schneier expandable messagemulti-target second-preimage attack+2

other· Added 26 Oct 2026, published 25 Oct 2026

arxiv.orgpaper

The Policies of Programming Language Ecosystems: A "Qualitative" Analysis

The Policies of Programming Language Ecosystems is an October 2026 arXiv paper (cs.SE) that compares the policies of eight programming language ecosystems, including CRAN for R, across 38 policy categories. Three authors coded the policies with moderate agreement. Malware, intellectual property and content removal are covered everywhere, while package size limits, metric manipulation, typosquatting and binary uploads diverge.

CRAN
typosquatting

Supply Chain, GRC· Added 28 Oct 2026, published 25 Oct 2026

arxiv.orgpaper

Reversible Pseudonymisation of Documents Sent to External LLMs: an Open Bilingual Benchmark and an Engine

Open bilingual (Russian and UK English) benchmark of five open pseudonymisation tools and a regex baseline, plus a new engine built on the two strongest tools. On a held-out set of 1,000 synthetic documents per language, the best existing tools leave a whole personal value visible in 61% (Russian) and 58% (UK) of documents. The engine does so in 0.3% and 0.2%. Russian name restoration reaches only 94.6%, below the 99% threshold. Real documents were not tested.

LLMpii-guard

AI Security· Added 27 Oct 2026, published 25 Oct 2026

eprint.iacr.orgpaper

On the Inapplicability of Residue-Confined Error Attacks to CRT-FHE with Non-Degenerate Error Distributions

Anil Kumar Pradhan's October 2026 ePrint rebuts the Olejnik and Naskrecki (2026) key-recovery and plaintext-recovery attack on the Pradhan CRT-RLWE fully homomorphic encryption scheme. It argues the attack works only because the chosen error distribution lies in the kernel of the CRT encoding, which makes the effective error zero. It also argues that the intended centered-binomial errors make that event negligible at the reported parameters. This is the author's own response, not independent verification.

CRT-FHERLWE
Olejnik and NaskreckiAnil Kumar PradhanKey Recovery from Residue-Confined Errors in the Pradhan CRT-RLWE Construction+1

other· Added 26 Oct 2026, published 24 Oct 2026

eprint.iacr.orgpaper

Chosen Commitments and Certified Decoding Regions in the Adaptive Threshold Schnorr Attack

This IACR ePrint 2026/2632 paper by Demirtaş and Yayla analyses the Crites–Stewart adaptive forgery attack on threshold Schnorr signatures, which needs one call to a sparse linear search oracle (bounded distance decoding of a scaled Reed–Solomon code). It shows that choosing the commitment coefficient vector does not help much: a wrapper adversary with Q challenges succeeds with probability at most QM/p, even if its solvers decode every witness for free. For the six original (N, τ) pairs, M stays below 2^24, so the bound is under 2^-100 after 2^128 challenges at p = 2^252.

Schnorr signaturesReed–Solomon codesfolded Reed–Solomon codes
Crites and Stewart attackGuruswami–WangAshvinkumar–Habib–Srivastava+2

other· Added 26 Oct 2026, published 24 Oct 2026

arxiv.orgpaper

Ranking Is Not Deciding: Benchmark Shortcuts and Operating-Point Collapse in Query-Time RAG Poisoning Defenses

Ranking Is Not Deciding is an October 2026 arXiv paper showing that query-time RAG poisoning filters score near-perfectly because of how the poison set was built. PoisonedRAG's code prepends the target question to each passage. Removing that prefix takes RAGuard from AUROC 0.953 to 0.758 and its miss rate from 0.191 to 0.763. The authors release a script that profiles a poison set.

LLM
PoisonedRAGRAGuardTrustRAG+5

AI Security· Added 27 Oct 2026, published 24 Oct 2026

eprint.iacr.orgpaper

VeilDNS: Post-Quantum DNS Privacy from the First UDP Packet

VeilDNS is a DNS-native protocol that uses a post-quantum KEM and AEAD to encrypt DNS questions and answers and authenticate the resolver in one UDP exchange on port 53, preserving the DNS wire format. It has stateless and stateful modes plus optional forward secrecy from the second query. Against ML-DSA-authenticated DoT/DoH/DoQ it reports up to 3.5x higher cold-session throughput and 13.7x fewer bytes; Tamarin proves query confidentiality, response authentication and forward secrecy.

DNSML-DSATLS+1
VeilDNSTamarinDoT+3

other· Added 26 Oct 2026, published 24 Oct 2026

arxiv.orgpaper

Enhancing LLM-Based Vulnerability Detection via Representation-Aware Logical Ensemble

RALE (Representation-Aware Logical Ensemble) is a method for detecting vulnerabilities in C source code with LLMs trained on different code representations: raw source, Abstract Syntax Trees and Control Flow Graphs. The authors show the representations suit different vulnerability classes, and combine the models with explicit logical rules and majority voting. Single-representation models reach up to 73% F1, while the ensemble reaches 78%.

LLMC
RALERepresentation-Aware Logical EnsembleAbstract Syntax Tree+1

AI Security, AppSec· Added 28 Oct 2026, published 24 Oct 2026

arxiv.orgpaper

VulDec: Vulnerability Detection in Binaries via Neural Decompilation

VulDec is an arXiv paper (October 2026) presenting a dataset of real-world Assembly-C function pairs with CWE labels across multiple architectures, plus an end-to-end framework that uses neural decompilation for binary vulnerability detection. Tuned LLM decompilers reach about 56% Edit Similarity and 43% BLEU-4. Tuned LLM detectors reach macro F1 of 0.61 on a realistic test set with a 3% vulnerability rate.

LLM
VulDec

Malware & RE, AI Security· Added 28 Oct 2026, published 24 Oct 2026

eprint.iacr.orgpaper

Extraction meets Distillation - cryptanalytic techniques to recover parameters from a Deep Neural Network

Extraction meets Distillation is an IACR ePrint paper (2026/2628, CSCML 2026) that combines cryptanalytic weight-direction extraction with label-based distillation to reconstruct fully connected neural networks. It adapts a ReLU extraction implementation to Leaky ReLU and proves conditional bounds for direction recovery and sign selection. On CIFAR-10 victims, reconstructed models reach 56.40% and 58.29% agreement. It separates label requests from privileged access and notes that prediction agreement does not identify parameters.

ReLULeaky ReLU
CSCML 2026CIFAR-10

AI Security· Added 26 Oct 2026, published 24 Oct 2026

eprint.iacr.orgpaper

The Exact Bit Security of Hash-Based Signatures

The Exact Bit Security of Hash-Based Signatures is a 2026 IACR ePrint paper that analyses XMSS with 128-bit digests and SLH-DSA-128s in the random oracle model, with proofs formalised in Lean4. Strong unforgeability comes to 127 bits under most accounting modes but only 122 bits if just direct random oracle queries are counted. The authors give matching attacks, and show how resource accounting changes the result.

XMSSSLH-DSALean
Mikhail KudinovBenedikt WagnerEmile Wambsgans

other· Added 26 Oct 2026, published 24 Oct 2026

eprint.iacr.orgpaper

Provable Security of SHA-256-Based LMS Revisited in the Ideal-Cipher Model

Provable Security of SHA-256-Based LMS Revisited in the Ideal-Cipher Model is an October 2026 ePrint paper by Chun Guo, Hao Cheng, Bart Preneel and Meiqin Wang. It shows forgery attacks on LMS_SHA256_M32 and LMS_SHA256_M24 that exploit Merkle-Damgård structure, so the Katz and Fluhrer random-oracle bounds do not apply. It proves ideal-cipher-model bounds: about 256 minus log2 of the block count for M32, and a minimum of two terms for M24.

LMSSHA-256
KatzFluhrerLMS_SHA256_M32+4

other· Added 26 Oct 2026, published 24 Oct 2026

eprint.iacr.orgpaper

Faster Matrix Multiplication Leads to Faster Lattice Sieving

Gao and Hu's IACR ePrint 2026/2622 shows that if the matrix multiplication exponent satisfies ω ≤ 9/4 − η, heuristic lattice sieving runs in (3/2 − δ)^(n/2+o(n)) time under the spherical heuristic from the BDGL analysis. It builds on OpenAI's recent result that ω ≤ 9/4. With known matrix multiplication algorithms, the method already gives subquadratic search inside BDGL buckets. Only the abstract is available, so concrete parameters are not shown.

BDGLspherical heuristicmatrix multiplication exponent

other· Added 26 Oct 2026, published 24 Oct 2026

eprint.iacr.orgpaper

When Elliptic-Curve Semiprimality Certificates Reveal Factors

The paper formalizes elliptic-curve semiprimality certificates by adapting the Goldwasser-Kilian primality criterion. For certificates built with complex multiplication, a norm-lattice reconstruction factors N from (N, S, D) alone in expected polynomial time. The author uses it, plus public-point and quadratic-twist attacks, to factor Reble's 1084-digit and Broadhurst's 5061-digit moduli, and shows that hidden-cofactor, withheld-CM-map and private-isogeny repairs also fail.

Goldwasser-Kilian primality criterionReble modulusBroadhurst modulus+4

other· Added 26 Oct 2026, published 24 Oct 2026

arxiv.orgpaper

Deletion, Substitution, Repair and Transplant: Component Attribution in BARBICAN, a Layered Prompt-Injection Gateway for MCP

BARBICAN is a fail-closed prompt-injection gateway for MCP tool mediation. This paper shows its arbitration classifier ran on tokenizer-mangled text for a whole evaluation. Fixing it raised AUC from 0.392 to 0.855 while system recall fell from 80.67% to 80.34%. The routed band is 96.82% malicious, so deletion ablations mislead without substitution experiments and class-balance reporting.

Model Context ProtocolLLM
BARBICANprompt injection

AI Security· Added 27 Oct 2026, published 23 Oct 2026

eprint.iacr.orgpaper

Faster and Smaller Anonymous Credentials from Standardized Signatures

GordieHowe is a language, certifying compiler and zero-knowledge proof system for building anonymous credentials on standardized signatures (ECDSA, RSA, ML-DSA). It proves an ECDSA-signed mobile driving license presentation in 64.8 ms with a 276 KiB proof, 10.1x faster than Google's Longfellow, and an ML-DSA-44 signature in 87.3 ms with at least 116 bits of quantum security. Compiler output and security theorems are checked in Lean. It introduces series-parallel IOPs and extends the BCS transformation in the QROM.

ECDSAML-DSARSA+1
GordieHoweLongfellowBCS transformation+3

Identity & Access· Added 24 Oct 2026, published 23 Oct 2026

arxiv.orgpaper

On Task, Off Track: Benchmarking LLM and Agent Robustness to Near-Target Prompt Injection

NTBench (Near-Target Benchmark) tests LLM and agent robustness to near-target prompt injection, where injected instructions steer a response toward a plausible but incorrect or harmful outcome instead of abandoning the task. It builds reference-guided target-instruction pairs on existing datasets, with human validation, and evaluates seven LLMs on ten language datasets and two agent benchmarks. Attack success rose 9.3 to 35.8 points (incorrect targets) and 1.7 to 17.3 points (harmful targets) over fixed-target baselines.

LLM
NTBenchnear-target prompt injectionprompt injection

AI Security· Added 26 Oct 2026, published 23 Oct 2026

eprint.iacr.orgpaper

Tight Post-Quantum Multi-Key Security of the FX Construction

Rentaro Shiba and Tetsu Iwata prove a tight multi-key security bound for the FX construction (the DESX generalization) in the quantum ideal cipher model. Security holds up to about 2^((n+κ)/3) total classical and quantum oracle queries against fully adaptive adversaries, for any number of keyed instances μ≥1. This improves their ToSC 2026 bound and matches the offline Simon's algorithm attack in the exponent.

FX constructionDESXoffline Simon's algorithm+4

other· Added 24 Oct 2026, published 23 Oct 2026

eprint.iacr.orgpaper

Learning with Quantization and Worst Case Lattice Problems

Learning with Quantization and Worst Case Lattice Problems is an IACR ePrint paper (2026/2613) by Ziwei Hong and Zhongqiu Fang. It proves that search and decision learning with quantization (LWQ) with public dither is as hard as quantum GapSVP and SIVP on arbitrary lattices, using the randomized polar lattice quantizer of Lyu et al. It also shows that a complete reduction for interval uniform error LWE (MAMBA Frost) and hardness at concrete MAMBA parameters are not established.

LWE
MAMBAMAMBA FrostGapSVP+4

other· Added 24 Oct 2026, published 23 Oct 2026

eprint.iacr.orgpaper

For Thirty Pieces of Silver: Overcoming Non-IID via ZKP Sample-Level Auditing and Forcing Attackers into Traitors in Federated Learning

Preprint (IACR ePrint 2026/2611) proposing a federated learning defense that replaces gradient detection with zero-knowledge-proof sample-level audits of client datasets. A staking mechanism forces attackers to train on discovered poisoned samples with flipped labels, producing counter-gradients that remove the backdoor without knowing the trigger. ZKP commitments lock the training data, which blocks adaptive attacks and gradient tampering. On CIFAR-10 under Dir(0.1) non-IID, it holds attack success rate below 6% against distributed backdoor and edge-case attacks.

distributed backdoor attackedge-case attackadaptive attack+3

AI Security· Added 24 Oct 2026, published 23 Oct 2026

eprint.iacr.orgpaper

Pairwise Independence of Ten-Round AES

Pairwise Independence of Ten-Round AES (Zhongfeng Niu, Kai Hu, ePrint 2026/2608) proves that ten rounds of AES with independent uniform round keys and input/output whitening are within 3017/2^141 (below 2^-129) statistical distance of pairwise independent. The proof bounds the averaged difference-distribution matrix over five superbox layers, using Gram moments and MDS code constraints. Final-round MixColumns omission is retained.

AES
pairwise independencedifference-distribution matrixMDS code+1

other· Added 24 Oct 2026, published 23 Oct 2026

arxiv.orgpaper

Agentic AI Defense: Decode-Time Provenance Binding for MCP

Decode-time provenance binding is a defense for Model Context Protocol agent pipelines against cross-modal trust laundering, where instructions hidden in an email-signature image via LSB, DCT or metadata steganography get decoded by a tool. It combines HMAC-authenticated trust labels, a provenance ledger and context-taint tracking to block critical tool calls. On a real MCP testbed with 24 adaptive payloads, attack success fell from 100% undefended (62.5% for keyword and regex filters) to 0%.

Model Context Protocol
indirect prompt injectioncross-modal trust launderingsteganography+5

AI Security· Added 26 Oct 2026, published 22 Oct 2026

eprint.iacr.orgpaper

Mímir: A Stateless Private Search Engine

Mímir is a cryptographic protocol for stateless semantic private search over highly dynamic public databases. It uses homomorphic ciphertext switching, relies on (Ring) Learning with Errors, and needs no offline communication. Against Tiptoe it matches search quality with 84x less per-query communication (0.24 MiB). Against PACMANN it raises quality from 76% to 81% of non-private search, with a 9.54 MiB one-time cost instead of 2.68 GiB, but is 2.1x slower.

TiptoePACMANNLearning with Errors+1

other· Added 24 Oct 2026, published 22 Oct 2026

eprint.iacr.orgpaper

Balsamic: One-round Threshold UOV from GPU-Accelerated FHE

Balsamic is a complete homomorphic Unbalanced Oil and Vinegar (UOV) signer, used to build one-round threshold UOV signatures from a packed discrete-CKKS FHE circuit. A paired-pivot linear solver and pivot-success certificates allow encrypted retry selection. In 2-out-of-3 semihonest signing, each online partial signature takes 10.7 s on an RTX 6000 Ada and 7.77 s on a GB300, with 5.25 MB per response.

UOVCKKSFHE+2
Balsamicuniversal thresholdizerspaired-pivot solver+1

other· Added 24 Oct 2026, published 22 Oct 2026

eprint.iacr.orgpaper

Integer Coordinate Families and Threshold RSA Signatures for Any Prime Exponent

Paper by Shivansh Jaiswal and Somitra Sanadhya (IACR ePrint 2026/2601) on integer coordinate families for threshold RSA signatures with prime exponent e. It shows the CT-RSA 2026 Ng-Lau scheme admits trivial forgeries and has a flawed proof. It proposes repaired scheme PiIC and integer secret-sharing scheme PiZ for any prime e and any (t,n), both proven TS-UF-CMA secure under the standard RSA assumption. It also gives super-polynomial coordinate lower bounds for pairwise families.

RSA
Ng-Lau schemePiICPiZ+3

other· Added 24 Oct 2026, published 22 Oct 2026

eprint.iacr.orgpaper

Linear Cryptanalysis of TFHE-Friendly Cipher FRAST in the Average Key Setting

Linear cryptanalysis of FRAST, a TFHE-friendly stream cipher, in the average key setting. It fixes the false-positive problem left open in the earlier attack by Bak et al., showing key differences fall into five indistinguishable classes per round. The Contract algorithm recovers the master key for 10 rounds and, on weak keys of density 2^-11.8 to 2^-5.4, reaches full FRAST within the claimed security.

FRASTTFHE
Contract algorithmBak et al.linear cryptanalysis+1

other· Added 24 Oct 2026, published 22 Oct 2026

eprint.iacr.orgpaper

The Good, the Bad, and the Noisy: A Systematic Analysis of Ring-Oscillator-Based Noise Generators

This IACR ePrint paper (2026/2597) systematically compares ring-oscillator-based additive noise generators, a hiding countermeasure against side-channel attacks. Experiments show many existing designs ignore output amplification and the risk of the noise being filtered out, so they lower signal-to-noise ratio too little. The authors give a guideline on inverter chain length, output amplification and frequency randomization, and build a tailored generator for an AES implementation that outperforms prior designs.

AES
Florian StolzDina HesseJulius Hermelink+2

Hardware & RF· Added 24 Oct 2026, published 22 Oct 2026

arxiv.orgpaper

SecLog-Bench: A Scalable Benchmark for Cybersecurity Log Reasoning with Scaffolded Evidence

SecLog-Bench is a benchmark for LLM reasoning over cybersecurity logs, built on an extensible simulation platform covering 29 attack scenarios. It combines audit logs, application logs and network traffic, with attack-stage labels and step-by-step evidence chains. Eight LLMs were tested on post-detection attack-progress reasoning: the best reached 44.44% accuracy, 45.07% Macro-F1 and 54.87% Stage Reasoning F1.

LLM
SecLog-BenchStage Reasoning F1

AI Security, Blue Team & Detection· Added 23 Oct 2026, published 22 Oct 2026

eprint.iacr.orgpaper

Getting to the right root: radical isogenies of every degree

Thomas Decru's ePrint 2026/2595 proves a corrected version of radical isogeny formulae for every N≥4, odd and even, over fields of characteristic coprime to 2N. It settles the sign choice for even N so that 2-isogeny walks stay on the volcano surface. One radical step costs about 12.5N multiplications and one exponentiation, and the paper shows how to evaluate radical isogenies on points, so a CSIDH class group action needs no torsion point sampling.

CSIDH
radical isogeniesKronecker theta function2-isogeny volcano+3

other· Added 24 Oct 2026, published 22 Oct 2026

eprint.iacr.orgpaper

Efficient Laconic Oblivious Transfer with Malicious Security

Efficient Laconic Oblivious Transfer with Malicious Security is an ePrint paper (2026/2593, ASIACRYPT 2026 revision) giving the first maliciously secure laconic OT that uses its primitives only as black boxes. It adds equivocal vector commitments and maliciously secure witness encryption to the commitment-plus-witness-encryption paradigm. Security is proven in the UC model against malicious senders and in the context model against malicious receivers. Instantiations use LWE and bilinear Diffie-Hellman assumptions in the standard model.

laconic oblivious transferequivocal vector commitmentswitness encryption+3

other· Added 24 Oct 2026, published 22 Oct 2026

eprint.iacr.orgpaper

Sotto Maschera: Masking the Sota-Voce Fixed-Weight Vector Sampling

Sotto Maschera is a masked implementation of the Sota Voce sparse fixed-weight vector sampler (Sota support sampler and MWSupport conversion) for embedded devices, protecting against power side-channel attacks. It bitslices sorting, merging and compaction and masks only in the Boolean domain, avoiding slow conversions. TVLA evaluations show no leakage, and HQC runs up to 45x faster than previous masked work.

HQC
Sota VoceMWSupportTVLA+2

Hardware & RF· Added 24 Oct 2026, published 21 Oct 2026

eprint.iacr.orgpaper

Rerandomizable Garbling for Arithmetic Circuits

Rerandomizable Garbling for Arithmetic Circuits is an IACR ePrint paper (2026/2590) by Acharya, Meyer, Orlandi and Roy. It gives the first rerandomizable garbling scheme for arithmetic circuits, built on techniques from garbling via homomorphic secret sharing. Communication is O(|C| log B), with 17 group elements per multiplication gate and free additions. Security rests on subgroup-indistinguishability assumptions such as DCR and class groups.

Decisional Composite ResiduosityYao's garbled circuitshomomorphic secret sharing+4

other· Added 24 Oct 2026, published 21 Oct 2026

arxiv.orgpaper

Prompt Injection Through Forensic Evidence: A Taxonomy and Proof of Concept of Anti-Forensic Attacks on LLM-Assisted Digital Investigations

Paper on prompt injection delivered through forensic evidence, where the seized device's contents are attacker-controlled and the examiner must read them. It extends the anti-forensic model to cover manipulation of the reasoning layer and gives a taxonomy (objective, technique, payload location, concealment). Three proof-of-concept attacks on an LLM-assisted analysis pipeline change a reported conclusion, write attacker-chosen content to the analyst workstation, and trigger outbound network traffic. Mitigations are proposed.

LLM
indirect prompt injectionprompt injectionanti-forensics+1

AI Security, Blue Team & Detection· Added 24 Oct 2026, published 21 Oct 2026

eprint.iacr.orgpaper

RingTrace: Model-Free Spatio-Temporal Detection and Core Attribution for Cache Side-Channels

RingTrace is a monitoring framework that detects Flush+Reload cache side-channel attacks by combining per-core cache-miss counters with slice activity across uncore CBoxes. Its Joint Spatio-Temporal Attribution (JSTA) builds a joint-activity matrix without model training: the largest entry is the screening score and row sums point to a candidate core. The authors report detection before secret leakage, fewer false alarms under heavy memory load, and negligible runtime overhead on commodity processors.

Flush+ReloadJoint Spatio-Temporal AttributionJSTA+1

Hardware & RF, Blue Team & Detection· Added 24 Oct 2026, published 21 Oct 2026

arxiv.orgpaper

MPIDetector: Detecting Multi-modal Prompt Injection via LLM-based Reasoning

MPIDetector is a detection framework for multi-modal prompt injection that uses few-shot in-context learning so an LLM can reason about the semantic intent of text and image inputs, without fine-tuning. The authors built a benchmark of eight textual and seven visual attack categories plus benign sets. They report up to 90.91% accuracy on text, 99.28% on images, and up to 99.80% detection on 500 obfuscated WebInject web-agent injections, beating baselines.

GeminiQwenLLM
prompt injectionWebInjectMPIDetector

AI Security· Added 24 Oct 2026, published 21 Oct 2026

eprint.iacr.orgpaper

Modeling Modular Multiplication for Monomial Prediction and Impossible Differentials, with Application to MSX

This ePrint paper gives the first exact bit-level models of modular multiplication z=(x·y) mod 2^n. One model is for monomial prediction under 3SDP-woU, the other for impossible differential search. Applied to the MSX lightweight cipher, it yields a 7-round integral distinguisher (2^96 data) for MSX-128, key recoveries on 8 and 9 of 18 rounds at about 2^228 operations, and 1,984 seven-round impossible differentials. Both models are implemented in CLAASP.

MSXCLAASP
MSX-128monomial predictionthree-subset division property+5

other· Added 24 Oct 2026, published 21 Oct 2026

eprint.iacr.orgpaper

Verifiable Post-Quantum TLS Handshake: Recognizing Implementation Errors of Cryptographic Verification Steps

PQCD-TLS is a post-quantum TLS handshake that binds confirmation codes into chained key derivation, so a faulty signature or KEM verification step causes a key mismatch and handshake failure. The authors build confirmation-code frameworks for ML-DSA and Falcon signatures and for ML-KEM, HQC and DAWN, with unpredictability proofs. Across 48 configurations, handshake latency overhead stays below 1%.

TLSML-DSAML-KEM
goto failPQCD-TLSFalcon+3

AppSec· Added 24 Oct 2026, published 21 Oct 2026

eprint.iacr.orgpaper

SHAKEing SLH-DSA with Non-profiled SCAs

SHAKEing SLH-DSA with Non-profiled SCAs is an eShard ePrint paper (2026/2584) on correlation power analysis of SLH-DSA-SHAKE, the NIST-standardised hash-based signature scheme. It analyses PRF inputs and selection functions, then combines subtrace averaging, partial-then-total CPA and an efficient exhaustive search to recover the full secret seed, enabling universal forgery. On a 32-bit microcontroller the attack needs about 280 to 559 signatures, and the search finishes within 45 minutes on 72 cores.

SLH-DSASHAKEKeccak
NISTuniversal forgerySPHINCS+

Hardware & RF· Added 24 Oct 2026, published 21 Oct 2026

arxiv.orgpaper

Where AI Vulnerability Discovery Harnesses Go Quiet: Structural False Negatives and Hidden Vulnerabilities

Paper (arXiv, 21 October 2026) on structural false negatives in LLM vulnerability discovery harnesses. Starting from Knostic's OpenAnt and raptor, then 10 more open-source harnesses, the authors map 13 points where code selection, filtering, and finding storage or merging drop vulnerabilities. One file was dropped by six harnesses before the model saw it, five without notice. It covers attacker evasion, content-steered verdicts, prompt injection, and design principles and tests.

OpenAntraptorLLM
KnosticPtacek and Newshamprompt injection+1

AI Security, AppSec· Added 24 Oct 2026, published 21 Oct 2026

eprint.iacr.orgpaper

Rounded Gaussians are Discrete Gaussians

Rounded Gaussians are Discrete Gaussians is an IACR ePrint paper (2026/2583) by Corentin Jeudy. It shows that setting the rounded Gaussian parameter to sigma = s - 1/(24s) gives a distribution within Rényi divergence 1 + O(1/s^8) of a discrete Gaussian of parameter s. Lattice schemes can then use the simple, constant-time-friendly, low-memory rounded sampler while analyzing security against an ideal discrete Gaussian.

Rényi divergenceCorentin JeudyHülsing, Lange and Smeets

other· Added 24 Oct 2026, published 21 Oct 2026

eprint.iacr.orgpaper

SoK: Design-Level Backdoors in Block Ciphers Constructions, Detection, and Key Recovery

SoK on design-level backdoors in block ciphers. It places four published designs (Rijmen and Preneel, Paterson, Bannier and Filiol, Peyrin and Wang) in one taxonomy and gives a sound algorithm that recovers a partition trapdoor from S-box tables. It attacks KG-DES, BEA-1 and LowMC-M: KG-DES key recovery takes minutes, and the LowMC-M MALICIOUS backdoor yields the key from 35 to 409 queries. Trapdoors hidden in linear layers leave no trace, so the authors recommend deriving constants verifiably from a public seed.

KG-DESBEA-1LowMC-M+2
Rijmen and PreneelPatersonBannier and Filiol+5

other· Added 24 Oct 2026, published 21 Oct 2026

eprint.iacr.orgpaper

Table-Free Constant-Work BCH Decoding by Algebraic Index Elimination

Table-free constant-work BCH decoding by algebraic index elimination is an IACR ePrint paper (2026/2580) that replaces the table scans in Walters and Sinha Roy's constant-work BCH decoder with fixed circuits over public addresses. It proves correctness through radius t and trace regularity, removes 5.2 and 7.2 KiB of tables, and runs 35.7 to 82.4 times faster on an i7-13700. Ordinary C masks compiled to received-word-dependent branches under Apple Clang 21, so the authors use a compiler-opaque primitive and run timing screens on four platforms.

Apple ClangC
Walters and Sinha Royalgebraic index eliminationANSA-IBKEM1+3

Hardware & RF· Added 24 Oct 2026, published 21 Oct 2026

arxiv.orgpaper

Protection Is Not One Event: A Survey of RAG Protection Research by Measured Endpoint

Survey and human-coded evidence map of 118 RAG defense papers, organized by measured endpoint across a seven-family taxonomy (content disclosure, formal privacy proxies, access control, corpus-use detection, pipeline integrity). Only 17.8% of studies use disclosure or reconstruction as the primary endpoint, and most use non-adaptive attacks on general QA data. A testbed shows a normalized 8-gram guard cuts 20-token copying to 0.0%, yet a three-query adaptive attacker recovers 48.3% of hidden facts on Qwen3-8B.

QwenLLM
prompt injection

AI Security· Added 24 Oct 2026, published 21 Oct 2026

arxiv.orgpaper

PQ-Vault: Provably Quantum-Safe Asset Custody for Unmodified Ethereum

PQ-Vault is a custody design for unmodified Ethereum against quantum key recovery. It combines a quantum-safe vault contract, a proof-of-stake sidechain with compact certificates, and an optimistic dispute protocol. The paper proves that compact certificates with classically chosen parameters fall from 128 to about 60 bits against quantum attackers, and bounds a seed-update stake-steering attack. For 65,536 validators a certificate is 0.8 MB and verifies in about 20 ms, and the vault accepts a checkpoint for about 420,000 gas.

Ethereum
compact certificatesstake steering

Blockchain· Added 24 Oct 2026, published 21 Oct 2026

eprint.iacr.orgpaper

Active and Passive Attacks against TPM 2.0-based Full Disk Encryption

Active and Passive Attacks against TPM 2.0-based Full Disk Encryption is an ePrint paper by Freud, Hein and Klein (BSI). It shows SPI bus sniffing and interception against discrete TPMs on a mini PC and a notebook, plus a prototype UEFI firmware attack in QEMU that affects firmware TPMs. The attacks break BitLocker and all current Linux FDE implementations, including those using TPM parameter encryption.

BitLockerLUKSTPM 2.0+3
parameter encryptionTPM sealingBSI+3

Hardware & RF, Offensive Security· Added 24 Oct 2026, published 21 Oct 2026

eprint.iacr.orgpaper

HAETAE on a Diet: Less Stack, Less Time on Low-End Microcontrollers

This ePrint paper presents an optimized HAETAE implementation, a lattice-based post-quantum signature scheme, for Cortex-M4, Cortex-M3, MSP430 and AVR. It keeps polynomials in 16 bits, shares buffers between objects with disjoint lifetimes, and replays Gaussian samples instead of regenerating them. On an ATmega2560, HAETAE-2 key generation, signing and verification run in 8,070 B of SRAM. Stack use drops up to 34% and signing is 1.18-2.51x faster than Low-Stack HAETAE.

HAETAEML-DSAARM Cortex-M4+3
Low-Stack HAETAEHAETAE-2CHES 2026

Hardware & RF· Added 24 Oct 2026, published 21 Oct 2026

eprint.iacr.orgpaper

Reverse Engineering IVXV: A Specification and Security Analysis of Estonia’s Internet Voting System

Reverse Engineering IVXV is an October 2026 ePrint paper by Tingfeng Yu and Thomas Haines that reconstructs a specification of Estonia's IVXV internet voting system from public source code and documentation, with an executable TLA+ model checked in TLC. It analyses individual and universal verifiability, privacy, coercion resistance and eligibility, compares IVXV with Belenios and Swiss Post, and reports new vulnerabilities, some confirmed with proof-of-concept tests, plus mitigations.

IVXVTLA+TLC
EstoniaBeleniosSwiss Post+2

AppSec· Added 24 Oct 2026, published 21 Oct 2026

eprint.iacr.orgpaper

RDK-CKKS: A Framework for Rigorous Error Analysis for CKKS Computation

RDK-CKKS is a framework for rigorous probabilistic error analysis of CKKS homomorphic encryption. It injects randomization keys (encryptions of zero) at key-switching and rescaling so each operation's error has provable tail bounds, which noise flooding needs for IND-CPA^D and threshold settings. It gives a full rigorous analysis of binary bootstrapping, at about 3% extra modulus and 27% extra key communication over bootstrapping keys.

CKKS
IND-CPA^Dnoise floodingrandomization keys+1

other· Added 24 Oct 2026, published 21 Oct 2026

eprint.iacr.orgpaper

Broadcast and Trace from Lattices: Collusion-Resistant and Publicly Traceable

Broadcast and Trace from Lattices is a 2026 ePrint preprint by Jeffrey Champion. It builds collusion-resistant broadcast and trace with public tracing from attribute-based encryption with succinct ciphertexts and lockable obfuscation, both known from decomposed LWE. Ciphertexts are sqrt(N)·poly(λ, log N) in size, with poly(λ, log N) keys. It is the first such scheme based on a simple, instance-independent lattice assumption.

Jeffrey ChampionNassar, Waters and Wupositional witness encryption

other· Added 24 Oct 2026, published 21 Oct 2026

arxiv.orgpaper

Combining Long-Term Memory and LLMs Comes at a High Cost: From Prompt Injection to Persistent Compromise

Paper on memory injection, where prompt injection persists across sessions through the long-term memory of LLM-as-a-service platforms. It presents a general threat model and shows all NIST attack goals are achievable on ChatGPT Instant 5.3, Claude Sonnet 4.6 and Gemini 3 Flash. Vectors include personal memories, projects, skills, organization instructions and MCP resources. On Claude, shared memory lets an attacker compromise multiple users in an organization and exfiltrate prompts. Nearly half of the derived mitigations are unimplemented.

ChatGPTClaudeGemini+2
memory injectionprompt injectionNIST+2

AI Security· Added 24 Oct 2026, published 20 Oct 2026

eprint.iacr.orgpaper

DISCO*: DIstributed and SCalable Oblivious Joins and Oblivious Primitives

DISCO is a distributed, fully oblivious database system that combines hardware enclaves (TEEs) with oblivious primitives to hide access patterns from side-channel and leakage-abuse attacks. New distributed frameworks and communication optimizations let it run in parallel across servers. It reports 88x speedup over Jodes and 180x over SODA on non-foreign-key joins with 2^25 elements, and the first terabyte-scale results.

DISCO
JodesSODASOSP 2026

Hardware & RF· Added 21 Oct 2026, published 20 Oct 2026

arxiv.orgpaper

Sign Here: Attributing a Source for a More Trustworthy Software Supply Chain

Sign Here is an arXiv paper (October 2026) testing whether building packages from source, instead of pulling from registries, prevents malware. It aggregates 47,066 malicious npm and PyPI packages from five datasets and indexes 3.9 million npm and 764 thousand PyPI packages. Checking for an attributed source blocks 87.7 to 99.9 percent of malware depending on vetting level, but only 47.4 percent of benign packages attribute a buildable source.

npmPyPI
Shai-HuludAxios

Supply Chain· Added 24 Oct 2026, published 20 Oct 2026

eprint.iacr.orgpaper

A Spectral Theory of Local-to-Global Leakage

A Spectral Theory of Local-to-Global Leakage is an IACR ePrint paper (2026/2571) by Rei Ueno on additive secret sharing over finite abelian groups. It gives an exact leakage decomposition into local leakage magnitude and spectral alignment across shares. Two channels with identical local mutual information can have exponentially different global leakage. Automorphism-weighted sharing can cancel leakage perfectly with finitely many shares, which ordinary additive sharing cannot do.

Rei UenoMöbius inversion

Hardware & RF· Added 21 Oct 2026, published 20 Oct 2026

eprint.iacr.orgpaper

Membership Inference in Privacy-Preserving Vector Search

Membership Inference in Privacy-Preserving Vector Search is an IACR ePrint paper (2026/2570) that attacks backend-compatible protections for embedding databases using one snapshot and known plaintexts. It breaks the Scale-and-Perturb scheme of Fuchsbauer et al. (advantage 0.997 on MS-MARCO) and analyzes Rotate-and-Perturb, ideal DCRE and an encrypted HNSW index. It also tests shuffling and secret projection as mitigations.

HNSW
Scale-and-PerturbRotate-and-PerturbSAP-I+5

AI Security· Added 21 Oct 2026, published 20 Oct 2026

arxiv.orgpaper

After the Attacker Leaves: Benchmarking Carryover Attacks on LLM Agents

CarryoverBench is a benchmark of 12 personal-assistant scenarios and 101 attack tasks for carryover attacks, where a one-time indirect prompt injection planted in agent memory files or scheduled tasks re-fires in later sessions. Three trigger channels (Instant, Autonomous, Latent) are scored by a rule-based verifier with separate planting and triggering stages. Across five frontier models, payloads re-fire over five rounds without measurable decay. Porting the Latent channel to the Hermes runtime weakens the effect but does not remove it.

LLM
CarryoverBenchcarryover attacksindirect prompt injection+1

AI Security· Added 22 Oct 2026, published 20 Oct 2026

arxiv.orgpaper

Context-Aware Prompt Injection Detection via Small Language Models in RAG Pipelines: nokast-secureRAG

nokast-secureRAG is a roughly 0.5B-parameter small language model that works as a semantic firewall between retrieval and generation in local RAG systems. It classifies each query and context pair as safe, suspicious or malicious. It reaches 0.994 recall at a 0.026 false-positive rate in-distribution, beating Llama Guard 3 1B and Prompt-Guard-86M (0.900 recall, 0.690 FPR). Recall on PoisonedRAG falls to near zero, and single-request latency is 293-404 ms.

Llama Guard 3LLM
indirect prompt injectionretrieval poisoningPoisonedRAG+2

AI Security· Added 22 Oct 2026, published 20 Oct 2026

eprint.iacr.orgpaper

Efficient NTRU+ Implementations on Cortex-M

Efficient NTRU+ Implementations on Cortex-M presents NTRU+ KEM implementations built on 3-way NTTs for Arm Cortex-M0+, M3, M4 and M7. It adds omega-folded front layers that handle ternary inputs without modular reduction. The speed-optimized version cuts execution time by up to 52.43% against the official optimized C code. The memory-optimized version cuts peak stack use by up to 82.60%.

Cortex-MNTRU+

Hardware & RF· Added 21 Oct 2026, published 20 Oct 2026

eprint.iacr.orgpaper

A Systematic Evaluation of Fault Attacks and Countermeasures on ML-DSA Rejection Sampling

Systematic evaluation of fault attacks on ML-DSA (FIPS 204) rejection sampling and of proposed countermeasures. It proves the "third rejection test" of patent WO2025261784A1 re-verifies what check 2 already guarantees, and shows that 30,000 fault injections never detect a skipped z-norm check. The author fully recovers s1 against a third-check-protected implementation under randomized signing. Third check and sign-then-verify are complementary; overhead is 0.04–0.05% on x86-64 and 0.83% on Cortex-M4 for the third check.

Cortex-M4
ML-DSAFIPS 204WO2025261784A1+1

Hardware & RF· Added 21 Oct 2026, published 20 Oct 2026

eprint.iacr.orgpaper

Fault-Induced Nonce Repetition in Threshold Lattice Signatures: A Reveal-Structure Criterion, Cross-Scheme Analysis, and Detection Boundaries

Fault-Induced Nonce Repetition in Threshold Lattice Signatures is an ePrint paper (2026/2566, Yulong Meng) showing that faulting t devices in a t-of-n threshold ML-DSA deployment recovers the full signing secret, verified on Mithril with exact recovery in 96/96 scan groups. It gives a reveal-structure criterion across Quorus, TALUS and Trilithium, a threshold law m* = (ℓ-1)N+⌈N/K⌉ for imperfect faults, and two-layer transcript detection (305/305 hits, no false positives).

ML-DSA
MithrilQuorusTALUS+7

Hardware & RF· Added 21 Oct 2026, published 20 Oct 2026

eprint.iacr.orgpaper

Further Elaborations on the Provable Dual Attack

Further Elaborations on the Provable Dual Attack is an October 2026 ePrint paper by Kaveh Bashiri presenting a provable dual attack on LWE that recovers a subvector of the secret, with an explicit success-probability bound and no heuristic assumptions. It unifies the analyses of Pouly and Shen (EUROCRYPT 2024) and Bashiri and Wiemers (2025). Applied to ML-KEM it improves the first provable dual attack by 22 to 100 bits; it is also applied to ML-DSA and tested on small instances. The author states ML-KEM and ML-DSA are not threatened.

ML-KEMML-DSA
Pouly and ShenBashiri and WiemersQu, Tian, Wang, and Xu+1

other· Added 21 Oct 2026, published 20 Oct 2026

eprint.iacr.orgpaper

Regular Syndrome Decoding Is Easier Than Previously Estimated

Preprint by Jiseung Kim, Minkyu Kim, Changmin Lee and Hochang Lee on the Regular Syndrome Decoding (RSD) problem. It presents a hybrid-algebraic attack that balances zero-coordinate guesses and syndrome-based eliminations across regular blocks. Parameter sets in Ferret, Wolverine and committed VOLE fall below 128-bit targets by up to 67 bits, and the revised Liu et al. (EUROCRYPT 2024) PCG sets cost under 2^111 field operations.

Regular Syndrome DecodingFerretWolverine+4

other· Added 21 Oct 2026, published 20 Oct 2026

eprint.iacr.orgpaper

Regular Syndrome Decoding Is Easier Than Previously Estimated

Preprint 2026/2563 presents a refined hybrid-algebraic attack on Regular Syndrome Decoding (RSD) that balances zero-coordinate guesses and syndrome-based eliminations across all regular blocks. It puts at least one parameter set each from Ferret (CCS 2020), Wolverine (IEEE S&P 2021) and committed VOLE (CCS 2025) below the 128-bit target, with losses up to 67 bits. PCG attack costs improve by up to 29.77 bits (non-binary) and 25.91 bits (binary), and the revised Liu et al. (EUROCRYPT 2024) 128-bit sets fall below 2^111 field operations.

FerretWolverine
Regular Syndrome Decodinginformation-set decodingpseudorandom correlation generator+3

other· Added 21 Oct 2026, published 20 Oct 2026

eprint.iacr.orgpaper

Graphs and cycles in curve-based collision walks

Graphs and cycles in curve-based collision walks is an IACR ePrint paper (2026/2560) on van Oorschot-Wiener style collision attacks in the multi-user setting. It covers elliptic curve discrete logarithms and isogeny pathfinding on supersingular F_p^2 and F_p curves, and proposes new pseudorandom walks. For F_p^2 curves, L keys need about L + log(L) useful collisions with no infiltrator. For F_p curves, about 0.75L keys fall to L collisions with an infiltrator.

van Oorschot-Wienerisogeny pathfindinginfiltrator+1

other· Added 21 Oct 2026, published 20 Oct 2026

arxiv.orgpaper

Raise or Check? Predicting the Necessity of Additional Fuzzing for Continuous Fuzzing

RAISE (Risk-Aware Intensive Supplemental Execution Framework) is a just-in-time framework that predicts which project-days introduce a vulnerability, to decide where to spend extra fuzzing. The dataset joins OSV vulnerability-introducing commits with OSS-Fuzz coverage data for 15 C/C++ projects (15,210 project-days, 347 positive). A Random Forest using VCCFinder static features plus fuzzing features reaches ROC-AUC 0.74. In a simulation over 968 vulnerabilities, Simple-Regression needed 91.60 extra fuzzing sessions per detected vulnerability, against 171.89 for the Median heuristic.

OSS-FuzzOSVC
RAISEVCCFinderPatchCoverage+1

AppSec· Added 22 Oct 2026, published 20 Oct 2026

arxiv.orgpaper

KNOX: Hardware-assisted Regulatory Sandbox for Generative Models

KNOX is a regulatory sandbox for generative models built by running AI agent workloads inside TEEs. It derives an attested policy manifest (applicable regulations, expected tool calls, permitted system calls) from the user prompt, and an attested reference monitor allows an action only if it matches. Actions and verdicts go into an attested execution graph that regulators can verify. The paper reports detection of prompt-injection deviations and under 1% overhead.

LLM
prompt injectionattested policy manifestattested reference monitor+1

AI Security, GRC· Added 22 Oct 2026, published 20 Oct 2026

eprint.iacr.orgpaper

FN-DSA on Arm Cortex-M55: Revisiting a Floating-Point Lattice Signature with Native FP64 and Helium

FN-DSA on Arm Cortex-M55 is an ePrint paper presenting the first FN-DSA (NIST post-quantum signature) implementation on this core that reproduces the reference known-answer tests and runs in constant time. It uses the native FP64 FPU for signing and Helium (MVE) for NTT, key-generation FFT and Keccak, with SLOTHY rescheduling. Key generation, signing and verification are up to 1.23x, 1.93x and 1.30x faster than the reference, and four-signature batch verification up to 1.75x.

FN-DSAARM Cortex-M55Helium+2
NISTknown-answer tests

Hardware & RF· Published and added 20 Oct 2026

eprint.iacr.orgpaper

Energy Consumption of Post-Quantum Cryptography on Constrained and General-Purpose Architectures

Benchmark of the three NIST post-quantum standards, FIPS 203 (ML-KEM), FIPS 204 (ML-DSA) and FIPS 205 (SLH-DSA), measuring speed and energy for key generation, signing and verification. Tests ran on Raspberry Pi 1, Zero and 4 and on laptop hardware, using OpenSSL 3.5 and a FNIRSI FNB58 USB power meter. ML-KEM and ML-DSA match classical elliptic-curve cryptography, while SLH-DSA signing on 32-bit devices cost up to 243% more energy than on 64-bit.

OpenSSLRaspberry PiFNIRSI FNB58
ML-KEMML-DSASLH-DSA+5

Hardware & RF· Added 20 Oct 2026, published 19 Oct 2026

eprint.iacr.orgpaper

Registered ABE via Predicate Encodings, Revisited

Registered ABE via Predicate Encodings, Revisited is an ePrint paper by Junichi Tomida (October 2026) that gives a new definition of predicate encodings suited to registered attribute-based encryption. It yields the first Reg-ABE schemes for (non-)zero inner product and for conjunctions/disjunctions with O(log L)-size ciphertexts. It also gives a registered broadcast encryption scheme with O(log L)-size ciphertexts under the standard k-Lin assumption, not the generic group model.

Junichi TomidaHoeteck WeeZhu et al.+2

other· Added 20 Oct 2026, published 19 Oct 2026

eprint.iacr.orgpaper

Analysis of an AI based code distinguisher

Analysis of DeepDistinguisher, a transformer model that tells Goppa codes from random linear codes. Using saliency maps and attention visualization, the authors find a low-weight-row artifact in the random training instances that the model partly uses. They propose a pairwise-XOR rule on generator matrix rows that correlates strongly with the model's predictions. On random matrices meeting the minimum distance and XOR constraints, the model loses most of its accuracy, so it exploits general combinatorial properties rather than hidden algebraic structure.

DeepDistinguisherGoppa Distinguisher problemGoppa code

AI Security, other· Added 20 Oct 2026, published 19 Oct 2026

eprint.iacr.orgpaper

Post-quantum commutative group actions from oriented superspecial abelian varieties

Castryck, Dina, Kutas and Lorenzon study the Shimura class group action on superspecial principally polarized abelian varieties with a CM orientation, as a post-quantum commutative group action for key exchange. They give tools to represent CM orientations through higher-dimensional isogenies and to compute the action in the restricted effective group action model. These rely on a CM version of Kani's lemma and a trick that often halves the ambient dimension. The paper also gives a method for finding oriented superspecial abelian surfaces and analyses obstructions to transitivity.

Shimura class group actionKani's lemmaIbukiyama-Katsura-Oort correspondence+5

other· Added 20 Oct 2026, published 19 Oct 2026

arxiv.orgpaper

Concerns in Benchmarking Jailbreaks: An Empirical Study of Attack Success Rates

This arXiv paper tests eight jailbreak attacks against three open-weight language models under three evaluation procedures. Low-resource language attacks score 96.0% mean ASR under keyword matching but 2.7% under a Qwen3 judge using StrongREJECT instructions. At Ollama's default temperature of 0.8, 100 samples of an unchanged request give 100% ASR by keywords and 50% by the judge. The authors recommend explicit success definitions, matched response budgets, validated evaluators and cumulative-failure reporting.

OllamaQwenLLM
StrongREJECTDeepInceptionattack success rate+1

AI Security· Added 21 Oct 2026, published 19 Oct 2026

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