82 results for “NIST”

world2vec is a method for learning mechanistic world models from observations and actions alone, without reward information. Its latent dynamics reproduce the true system over long prediction horizons using at least one order of magnitude fewer parameters than DreamerV3, TD-MPC2 and LeWM. The authors report state-of-the-art control of continuous environments from pixels and accurate system identification across a benchmark of 71 attractors.

arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026🧠 AI

Rewindable interactive proofs (RIPs) are a new model of relativizing interactive proofs for scalable oversight, in which a weak verifier can rewind an AI prover to an earlier saved state. The paper builds an RIP for computations robust to changes in a small fraction of oracle answers. The honest prover runs in linear time, the verifier runs in nearly linear time in the input length after one-time preprocessing, and no cryptography is used. A preliminary MNIST experiment shows an RIP can be faster than a deployed proof system.

arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026🧠 AI

OpenGray is a benchmark that adds tasks with known correct decisions to the OpenKBP-Opt head-and-neck dataset, including two overlap contradictions with provably incompatible dose goals and a feasible control. Four planning systems, from a rule-based script to a full LLM agent, were tested on 30 patients with Terra and Ministral 3 8B. Decision accuracy reached 95.4% and 92.1%, yet only 50% and 25% of overlap contradictions were escalated. SAGE logs of 39 radiosurgery runs showed an agent that lacked an action for stopping.

arxiv.orgpaperAdded 28 Oct 2026, published 27 Oct 2026🧠 AI

SymLift is a compile-free vulnerability detection framework for code fragments that lack project context. A fine-tuned LLM reconstructs control-flow, data-flow, memory and resource relations as a constrained LLVM-like IR, and a deterministic parser turns it into facts for Datalog rules that give findings with derivation traces. SymLift-Qwen-7B reaches 94.41% Target-F1 on FormAI and 91.66% micro-averaged Target-F1 on MegaVul.

arxiv.orgpaperAdded 28 Oct 2026, published 25 Oct 2026🧠 AI

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.

eprint.iacr.orgpaperAdded 26 Oct 2026, published 25 Oct 2026🛡️ Security

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.

eprint.iacr.orgpaperAdded 26 Oct 2026, published 25 Oct 2026🛡️ Security

The Geometry of Metaphor is an October 2026 arXiv preprint that uses mechanistic interpretability to find causal subspaces for metaphor in LLMs of different architectures and sizes. The authors steer output on classification tasks across parts of speech. They also steer generation tasks, showing the metaphoricity of model output can be controlled. The abstract gives no model names or metrics.

arxiv.orgpaperAdded 24 Oct 2026, published 22 Oct 2026🧠 AI

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.

eprint.iacr.orgpaperAdded 24 Oct 2026, published 21 Oct 2026🛡️ Security

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.

arxiv.orgpaperAdded 24 Oct 2026, published 20 Oct 2026🛡️ Security

DAR-MGSM (Dialectal Arabic Multilingual Grade School Math) is a manually curated benchmark for mathematical reasoning in Dialectal Arabic. It covers five major Arabic dialects plus Modern Standard Arabic, in a translated-only version and a translated and culturally localized version. Eleven Arabic-centric and multilingual LLMs were tested: accuracy generally drops on the localized version, and a mechanistic interpretability analysis shows the two variants induce distinct internal reasoning trajectories.

arxiv.orgpaperAdded 22 Oct 2026, published 20 Oct 2026🧠 AI

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.

eprint.iacr.orgpaperPublished and added 20 Oct 2026🛡️ Security

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.

eprint.iacr.orgpaperAdded 20 Oct 2026, published 19 Oct 2026🛡️ Security

ASTOR is an inference-time framework that has an LLM map a natural-language decision problem to a grammar-guided abstract syntax tree, then deterministically compiles it into executable optimization code. The paper also introduces SoftOR, a benchmark of natural-language problems with soft constraints. On SoftOR, ASTOR has the best aggregate accuracy among comparable single-request and multi-agent LLM methods, and it stays competitive on hard-constraint-only autoformulation benchmarks.

arxiv.orgpaperAdded 21 Oct 2026, published 19 Oct 2026🧠 AI

The paper presents a fault attack on deterministic CSIDH and OSIDH-LD. Forcing the lane-selection mask to zero (for example by skipping one instruction) makes output changes reveal whether a secret exponent reaches a threshold. Binary search then recovers the full key in at most 297 queries for OSIDH-LD and 222 for deterministic CSIDH with CSIDH-512-sized keys. Full OSIDH-LD keys were recovered in software fault simulation, and a ChipWhisperer-Lite skipped the target instruction with probability at least 0.94. The authors argue fault resistance requires giving up determinism and propose randomization countermeasures.

eprint.iacr.orgpaperAdded 20 Oct 2026, published 19 Oct 2026🛡️ Security

Provable Lattice Reduction in Nearly the Time of QR Factorization (IACR ePrint 2026/2541, October 2026) presents a deterministic lattice-reduction algorithm with running time Õ(n^ω(1+log κ_col(B))), free of heuristic assumptions. Its implementation used fewer instructions than flatter (CRYPTO 2023) in all 153 runs on q-ary, NTRU-like, scaled q-ary and Coppersmith inputs. Median flatter-to-new instruction ratios are 1.55 for q-ary and 1.86 for NTRU-like inputs.

eprint.iacr.orgpaperAdded 20 Oct 2026, published 19 Oct 2026🛡️ Security

This ePrint paper (2026/2525, October 2026) by Brendan Funk and Jiafeng Xie presents the first hardware accelerator for FAEST, an MPC-in-the-head post-quantum signature in NIST's Round 3 additional-signature process. It analyses FAEST's compute-heavy operations, builds them into hardware blocks, and adds an L1-EM-fast variant. The authors report at least 98% lower equivalent area-delay product than the recent complete SDitH design at the same security level.

eprint.iacr.orgpaperAdded 19 Oct 2026, published 18 Oct 2026🛡️ Security

Presents the first DPA-style power side-channel attack framework against VOLE-in-the-Head signature schemes, targeting the secret witness whose recovery enables forging signatures on arbitrary messages. It analyzes leakage from sensitive intermediate values in VOLE correlations and proposes six attack classes (two vertical, four horizontal) on FAEST and SDitH, both in NIST's third round of additional signatures. Attacks are validated with simulated leakage under varying noise and real measurements on three ARM Cortex-M4 devices.

eprint.iacr.orgpaperPublished and added 17 Oct 2026🛡️ Security

Cryptanalysis of the Eevee forkcipher-based AEAD modes Umbreon and Espeon, which claim online AE security under nonce reuse. Associated-data correlations give probability-one non-empty-message forgeries with three encryption queries and one verification query. The paper adds an affine treatment of partial final blocks (n-r+3 queries, or n-r+2 with adaptive choices). It also checks the published Umbreon attack with the official ForkSkinny primitive and reports a two-query attack accepted by the unmodified public C modes.

eprint.iacr.orgpaperPublished and added 17 Oct 2026🛡️ Security

Presents a language- and leakage-model-agnostic framework for provably secure compilation of probabilistic side-channel countermeasures. It uses a deterministic leakage-preservation relation that implies preservation of d-NI, d-SNI and cryptographic constant-time without probabilistic proof obligations. The authors prove in Rocq that a model of the Jasmin compiler's core pipeline and several optimizing passes preserve security in the value-probing model with glitches. They also add source-level annotations to harden against transition leakage and release libmasking, an arbitrary-order masked gadget library in Jasmin that compiles to ARM and RISC-V, with C bindings and hardware benchmarks.

eprint.iacr.orgpaperAdded 17 Oct 2026, published 16 Oct 2026🛡️ Security

ePrint paper identifying five side-channel vulnerabilities in the signing procedure of Round-3 SQIsign, the isogeny-based signature scheme in NIST's additional post-quantum signature process. It gives polynomial-time algebraic algorithms that recover the secret key from leaked quaternion/ideal intermediate values, including cases where only partial bits leak. It also demonstrates power analysis on the SQIsign source code to extract the needed leakage, which earlier work on Round-1 or toy parameters did not do.

eprint.iacr.orgpaperAdded 17 Oct 2026, published 16 Oct 2026🛡️ Security

ePrint paper cryptanalysing Eevee (Umbreon, Jolteon, Espeon), forkcipher-based AEAD modes proposed at CCS 2023 for IoT-to-cloud computation. It gives a two-encryption AD-free prefix distinguisher, a four-encryption nonce-misuse distinguisher, a deterministic AD-only forgery, and nonce-respecting forgeries on Jolteon and Espeon (fresh one-block forgery reusing the tag; arbitrary AD substitution). It traces these to proof flaws (online-prefix consistency, domain separation, checksum freshness), derives design requirements, and concludes the failures are in the mode design, not the C implementation.

eprint.iacr.orgpaperPublished and added 15 Oct 2026🛡️ Security

The paper shows that symmetric aggregation of a primary reward (correctness) and auxiliary rewards (brevity, efficiency) in LLM post-training can raise aggregate reward while primary-task performance falls. It proves that deterministic conditional-mean GRPO converges to auxiliary-favoring behavior when auxiliary rewards are more reliably obtained. It proposes Trust-Anchored Gating (TAG), which elects an anchor channel by policy drift and gates auxiliary credit on anchor satisfaction. On Qwen3-4B with a brevity reward, TAG reaches 0.581 pass@4 versus 0.220 for additive aggregation, and shortens responses by 44% relative to correctness-only training. Experiments on Qwen and Llama models cover math and program synthesis.

arxiv.orgpaperAdded 17 Oct 2026, published 15 Oct 2026🧠 AI

Presents fault injection attacks on BIKE and HQC decapsulation that target instructions outside the Fujisaki-Okamoto transform, achieving full key recovery with only valid ciphertexts at NIST Level 1 (17392 queries for HQC, about 3 million for BIKE). It also gives a general method for finding effective fault locations by analysing decoder behaviour under perturbed conditions. Attacks were validated with laser fault injection on an STM32H7 microcontroller, showing a wider attack surface for code-based post-quantum KEM implementations.

eprint.iacr.orgpaperPublished and added 15 Oct 2026🛡️ Security

Proposes a cost model and metric for an adversary who collects side-channel traces classically and finishes the key search on a quantum computer. Shows any quantum algorithm needs Omega(sqrt(r)) cipher evaluations for key rank r, and that the quadratic advantage holds only up to a rank bound set by the NIST MAXDEPTH budget (about 2^58.6 for AES-128 at D=2^40). Defines a quantum-aware key rank computable from existing rank estimators, with simulated-leakage experiments showing a depth-limited quantum adversary is worth about 22 traces at SNR 0.125.

arxiv.orgpaperAdded 16 Oct 2026, published 14 Oct 2026🛡️ Security

Presents the first blind signature in which the issuer runs unmodified NIST-standardized ML-DSA, so it works with certified secure elements. Issuance is an ML-DSA signature on a commitment. The blind signature is a VOLE-in-the-head zero-knowledge proof of knowledge of that signature, about 1 MB, under 1 s to produce and 0.5 s to verify. Security reduces to ML-DSA EUF-CMA and the proof system. Issuer-hiding and selective disclosure add a few tens of KB. The paper also introduces edaBitE, a batch consistency check between binary and prime-field commitments that replaces the costly edaBits checks.

eprint.iacr.orgpaperPublished and added 14 Oct 2026🛡️ Security

DPF-SGD is a federated SGD algorithm that stays robust to Byzantine agents while satisfying ϵ-differential privacy. It combines private step sizes with a DP noise-decay schedule and adds a privacy-preserving comparative elimination (PPCE) filter that suppresses Byzantine updates during aggregation. The authors prove almost-sure convergence to the global optimum despite persistent noise and adversaries. On synthetic and MNIST data, final optimization error is one to two orders of magnitude lower than DP baselines.

eprint.iacr.orgpaperPublished and added 14 Oct 2026🧠 AI

Introduces SA-CUA, a dual-LLM framework that gives Computer Use Agents a trust boundary against indirect prompt injection. It derives conservative deterministic rules from the accessibility tree to unmask trusted screen regions for the privileged LLM, and adds an endorsement channel that moves values from untrusted to trusted domains by verification. Human input is needed only at task specification. It reports much higher utility than CaMeL-CUA with a zero attack success rate.

arxiv.orgpaperAdded 15 Oct 2026, published 13 Oct 2026🛡️ Security

Introduces SA-CUA, a dual-LLM framework for Computer Use Agents (CUAs) that defends against indirect prompt injection. It builds a trust boundary by deriving conservative deterministic rules from the accessibility tree, which unmask trusted screen regions in the privileged LLM's screenshot and keep untrusted content separate. An endorsement channel lets values move from the untrusted to the trusted domain through verification over trusted channels. This removes the need for per-action user confirmation and the confirmation fatigue it causes. SA-CUA is reported to keep much higher utility than CaMeL-CUA with a 0% attack success rate.

arxiv.orgpaperAdded 15 Oct 2026, published 13 Oct 2026🧠 AI

Kairos is a reference monitor placed at the isolation boundary of an unmodified, opaque LLM agent, where tool calls, shell commands and agent-written scripts all appear as the same file and network operations. A declarative trust policy decides most effects deterministically and defers the rest; deferred effects are held while the agent continues speculatively, and a bounded-authority decision oracle (an LLM or a human) releases or refuses them based on the trace. Across three benchmarks and three agent models it beats existing defenses on the attack-success/utility trade-off; on AgentDojo it cuts attack success from 47.0% to 2.7% with no loss of benign utility.

arxiv.orgpaperAdded 15 Oct 2026, published 13 Oct 2026🛡️ Security

The paper builds explicit ReLU neural-network realizations of Camellia-128/192/256 from exact Boolean gates, S-box selectors and bit permutations, and reports known-answer-test agreement for Camellia-128. It shows that whitening and round-key quantities leaked from internal activations determine the master key through public key-schedule identities. Under a synthetic internal-oracle model, symmetric real-valued perturbations recover subkey bits with 128 queries (Camellia-128) or 256 (Camellia-256). Camellia-192 is handled by deterministic key-schedule inversion from direct access to round keys. All 3,000 trials (1,000 keys per variant) recovered the key exactly. The authors state this is not a plaintext/ciphertext-only attack on standard Camellia.

eprint.iacr.orgpaperAdded 14 Oct 2026, published 13 Oct 2026🛡️ Security

ePrint paper showing that FIPS 204 Table 1's expected iteration counts for the ML-DSA signing loop cover only the line-23 validity checks (z and r0 norms). They omit the two line-28 encoding-correctness checks (‖c·t0‖∞ and hint weight). It accounts for all four conditions: z by exact counting, c·t0 by an Irwin-Hall tail, and hint weight by a closed-form conditioned per-coefficient probability with a Monte Carlo tail estimate. Corrected expected iterations are 4.36, 5.14 and 3.91 for ML-DSA-44, -65 and -87, within 0.14% of an end-to-end measurement and consistent with NIST's FIPS 204 errata.

eprint.iacr.orgpaperAdded 14 Oct 2026, published 12 Oct 2026🛡️ Security

StableJudge is a defense framework against score-hijacking prompt injection in LLM-as-a-Judge pipelines (e.g. paper review, recommendation). A compact 0.13B "Sentry" model localizes injected spans and sanitizes them before the judge scores the content, trained on adversarially evolving attacks, and deterministic fine-grained scores are derived from the judge's output distribution. It improves score recovery under attack on held-out scientific abstracts and out-of-distribution attack variants while preserving general performance, decoupling safety from judge model scale. Code and data are promised but not yet released.

arxiv.orgpaperAdded 15 Oct 2026, published 12 Oct 2026🛡️ Security

ePrint paper presenting a vectorized implementation of the MQOM v2.1 post-quantum signature scheme (a NIST additional-signature candidate). It uses a transpose-enabled paired-matrix trick to cut wasted SIMD work and memory traffic. It benchmarks key generation, signing, verification and memory on Arm NEON, x86 AVX2 and AVX-512, with peak dynamic memory down by up to 39.43%. Supplementary experiments check how the matrix-layout optimization carries over to the Round-3 MQOM v3 code. Useful for practitioners assessing the deployment cost of post-quantum signatures.

eprint.iacr.orgpaperAdded 14 Oct 2026, published 10 Oct 2026🛡️ Security

Presents the first fixed-point FN-DSA (Falcon) signer for microcontrollers, using 32.64 arithmetic in constant-time Cortex-M4 assembly for Falcon-512 and Falcon-1024. Techniques that keep reciprocals, inverse square roots and small constants wide and round once at the consumer restore the precision lost by naive fixed-point. Measured precision supports about 2^99.7 (Falcon-512) and 2^96.7 (Falcon-1024) signing queries per key, against about 2^61.5 and 2^58.7 for double precision and the 2^64 target. The signer needs about 45% fewer cycles than double-precision emulation, at the cost of signing RAM rising from 59n to 83n bytes. The paper also shows which implementation choices lift double-precision c-fn-dsa above 2^64, derives Falcon-1024 key-generation bounds (72.3% of keys accepted vs 8.5% with the Falcon-512 values), and gives recommendations for the fixed-point FN-DSA NIST plans.

eprint.iacr.orgpaperAdded 12 Oct 2026, published 9 Oct 2026🛡️ Security

ePrint preprint extending the Ducas–Engelberts–Loyer provable subexponential Gaussian sampler (built on Wagner's generalized birthday algorithm) to module matrices over power-of-two cyclotomic rings. It gives provable 2^{O(n/lnln n)}-time algorithms for Module-SIS and for decision and search Module-LWE using only the k+ℓ ring samples provided, plus sample-preserving scalar search-LWE and narrow Module-LWE variants. Separate heuristic estimates suggest these Wagner-style attacks do not reach the NIST security targets of ML-KEM and ML-DSA.

eprint.iacr.orgpaperAdded 12 Oct 2026, published 8 Oct 2026🛡️ Security

OmniCapBench is a benchmark of 786 densely annotated videos that evaluates audio-visual captioning in multimodal LLMs. Instead of scoring free-form captions, it asks models for sets of atomic, verifiable units across three tracks (entity references, visual shots, audio events). These are scored with deterministic constraint checks plus localized LLM-based semantic comparisons, which gives coverage, localization and stable scoring together. Tests on frontier MLLMs show strong local perception but weak long-horizon audio-visual reasoning, especially identity drift and cross-modal misalignment.

arxiv.orgpaperAdded 9 Oct 2026, published 8 Oct 2026🧠 AI

The paper reimplements Q-FLAIR, which grows a quantum feature-map circuit gate by gate until the training loss stops improving. It runs the method on 784-pixel MNIST 3-vs-5 classification at five training-set sizes (N = 2000 to 10000), then fine-tunes each circuit to count Caro et al.'s active gates K. It finds no predictable link between training-set size and the circuit size Q-FLAIR converges to, and seed variance is nearly as large as any trend. The Caro et al. generalization bound holds in 14 of 15 runs, but the gap correlates only weakly with the bound (r = 0.12), so K explains little of the variation. This is a useful negative result for anyone hoping to jointly optimize circuit depth and data size.

arxiv.orgpaperAdded 9 Oct 2026, published 8 Oct 2026🧠 AI

ORCAGen uses RAG over a curated knowledge base of malware procedures and active-defense strategies, plus structured prompting, to have LLMs generate proof-of-concept malware and matching deception orchestration code offline. Strategies are validated against the PoC malware before being added to a runtime playbook that enforces only the verified, deterministic logic. It is evaluated on GPT-4o, GPT-5.5, Gemini 3.5 Flash, Qwen3-Coder and Claude Sonnet 4.5 over synthesized scenarios and 150 real keylogger, infostealer and ransomware samples, measuring execution success, hallucination rate, refinement effort, deception effectiveness and runtime overhead.

arxiv.orgpaperAdded 9 Oct 2026, published 8 Oct 2026🛡️ Security

Theoretical analysis of greedy search on a hierarchy of proximity graphs built from n points on the d-dimensional torus. It gives a deterministic coverage condition guaranteeing a (1+ε)-approximate nearest neighbor for any query. The condition holds w.h.p. for homogeneous Poisson, Hermitian determinantal and bounded-density Cox point processes when d = o(log n / log log n), and the expected hop count is O(exp(½ d log d + O(d)) log n), so logarithmic in fixed dimension. It gives formal grounding for the hierarchical ANN indexes used in RAG and recommendation retrieval.

arxiv.orgpaperAdded 9 Oct 2026, published 8 Oct 2026🧠 AI

Proposes "study contracts" that bind an AI-generated study's declared experimental choices, run obligations and claim scope to recorded execution evidence, defining contract-relative verification as distinct from scientific truth. In a diagnostic with eight self-authored clean/mutated pairs, a deterministic fault-specific checker caught all eight mutations, while eighteen LLM judge aliases given metadata-filtered packages flagged 104 of 144 mutated cases (32 abstentions, 8 terminal failures). The authors stress the setting is deliberately information-asymmetric, not a verifier-quality comparison or reward-hacking result, and call for full-information comparisons, legitimate-adaptation controls and closed-loop agent evaluations.

arxiv.orgpaperAdded 9 Oct 2026, published 8 Oct 2026🧠 AI

Proposes making the verifier the evolving object in self-improving agent loops. The verifier is an inspectable expression over small, mostly deterministic drawback detectors, synthesized from clustered failures, gated at birth, and selected for agreement with a ten-item anchored reference set plus consensus over unlabeled outputs, never for the agent's score. On MBPP+ it gains +0.21 held-out agreement over the hand-authored seed and ends ahead of the bare LLM judge it contains. Removing the anchor guards collapses the verifier into an always-pass grader that still trains skills as well, so downstream task score cannot certify a self-evolved verifier. The paper's Double Ratchet pairs the verifier with a lifecycle-managed skill loop and retains 88-110% of the lift from ground truth or a rubric on code generation, enterprise text-to-SQL and reference-free report generation.

arxiv.orgpaperAdded 9 Oct 2026, published 8 Oct 2026🧠 AI

This paper studies where tool-using LLM agents break down in the chain from gathering evidence to taking consequential actions, finding that strong static judgment of whether to act often coexists with much weaker interactive execution, and that failures arise from incomplete investigation, acting before evidence is established, or unresolved prerequisites in multi-action workflows. The authors introduce SafeActBench, a 656-case benchmark across six operational domains and five protocols, paired with a provenance-bound Evidence Ledger and a deterministic trajectory evaluator tested across ten model-harness configurations.

arxiv.orgpaperAdded 7 Oct 2026🧠 AI

An IACR ePrint paper by Yiming Gao, Xuyuan Han, and Honggang Hu presenting provable classical subexponential algorithms (running in roughly 2^((1/2+o(1))n/ln ln n) time/space) for recovering short secrets in growing parameter families tied to all seven NIST third-round lattice candidates: Kyber/ML-KEM, FrodoKEM, SABER, NTRU LPRime, Dilithium/ML-DSA, Falcon, and cyclic NTRU-HPS/HRSS. The approach extends the Wagner-style Gaussian sampling framework of Ducas, Engelberts, and Loyer (CRYPTO 2025) and a low-error decision-LWE algorithm, using an exact squared-Euclidean-norm gap to binary-search each secret coordinate, and an "affine slice search" over the public lattice for NTRU/Falcon-type quotient relations. The authors explicitly note the subexponential complexity applies to growing/weakened parameter regimes and does not reduce the concrete security of the currently specified NIST parameter sets.

eprint.iacr.orgpaperAdded 8 Oct 2026, published 6 Oct 2026🛡️ Security

This IACR ePrint paper (published TCHES 2027) presents a new cryptanalysis technique for the Lattice Isomorphism Problem that embeds LIP into a shortest-vector-problem instance on a different lattice than the one used in Hawk's specification, allowing attackers to integrate "hints" — partial information on the secret key obtained via side-channel attacks or other leakage. Using the LeakyLWEEstimator tool, the authors show Hawk signatures themselves leak exploitable information about the secret key, eroding Hawk-1024's security by roughly 11 bits, and apply the framework to resolve an open side-channel problem from TCHES 2024 plus discuss further fault-injection attack paths. Hawk is a lattice-based signature scheme submitted to NIST's second post-quantum signature call, making this a concrete key-recovery cryptanalysis relevant to PQC migration planning.

eprint.iacr.orgpaperAdded 8 Oct 2026, published 6 Oct 2026🛡️ Security

This IACR ePrint paper proposes and benchmarks a non-interactive Proof of Possession (PoP) for the code-based post-quantum KEM HQC, built using the VOLE-in-the-Head (VOLEitH) zero-knowledge paradigm, to solve the practical problem of issuing KEM-based certificates needed by protocols like KEMTLS. The authors integrate their HQC PoP into the ACME certificate-issuance protocol and compare it against existing PoP schemes for Kyber and FrodoKEM, showing Kyber issues certificates faster but at the cost of protocol or NIST-standard compatibility, while their HQC-based PoP keeps compatibility and achieves smaller proof sizes, which matters under unstable-network conditions due to larger KEM-based CSRs.

eprint.iacr.orgpaperAdded 8 Oct 2026, published 6 Oct 2026🛡️ Security

An IACR ePrint paper presenting K-LMS, an experimental variant of the NIST-standardized LMS hash-based post-quantum signature scheme in which the underlying hash is swapped for Korean primitives: the LSH-256 hash function (reference and vectorized) and a Tandem-DM double-block-length construction built from the CHAM, LEA, and ARIA block ciphers. The authors implement a non-invasive backend-swapping bridge over the reference LMS code and benchmark keygen/sign/verify latency, key/signature sizes, memory, and parameter sweeps, finding that hash substitution doesn't change key/signature sizes but that two measurement pitfalls (hash dispatch overhead, and software vs. hardware-accelerated SHA-256 baselines) can shift performance comparisons by an order of magnitude or 6x respectively. They report LSH-256 K-LMS signing on par with SHA-256 LMS in software, and 3.3-3.9x faster than a prior K-XMSS implementation because LMS needs fewer hash calls per Winternitz step than XMSS.

eprint.iacr.orgpaperAdded 8 Oct 2026, published 6 Oct 2026🛡️ Security

This IACR eprint paper presents a resource-efficient FPGA hardware architecture for the NIST-selected HQC post-quantum KEM that defends against power-based side-channel attacks by reusing otherwise-idle KECCAK hardware to inject scrambling dynamic power during decoding, adding less than 0.5 percent area overhead compared to masking/shuffling countermeasures. The fully parameterized design supports HQC-128/192/256 and was prototyped on a Xilinx Artix-7 FPGA (139 MHz, 11,489 LUTs, 6,785 FFs, 4 DSPs), with functional correctness verified via NIST Known Answer Tests and leakage suppression confirmed via Test Vector Leakage Assessment.

eprint.iacr.orgpaperAdded 8 Oct 2026, published 5 Oct 2026🛡️ Security

Agentic-ZTA is a multi-agent architecture that operationalizes the NIST SP 800-207 Zero Trust Architecture control loop using coordinated AI agents. A Policy Enforcement Point intercepts access requests, enriches them with context, and routes them to a policy-engine agent that invokes domain-specialized core and supporting agents; policies are retrieved via RAG and embedded into agent prompts at inference time, with trust scores aggregated by a trust algorithm to produce the final access decision. The authors implement and evaluate the framework on a testbed, reporting 95.0% accuracy, 93.9% precision, and 96.3% recall on representative access-control scenarios.

arxiv.orgpaperAdded 6 Oct 2026, published 5 Oct 2026🛡️ Security

An IACR ePrint paper presenting an optimized ARMv8 NEON assembly implementation of MAYO Round 3 (one of NIST's post-quantum signature candidates) for Apple M1, generated to be byte-identical to upstream intrinsics but 2–2.6x faster for signing and verification across all four parameter sets. The authors also run a constant-time testing campaign with matched null runs and find that while linear-algebra operations are statistically indistinguishable from constant-time nulls, verification (on public data) exhibits a measurable key-fixed timing effect present in both their implementation and the upstream code.

eprint.iacr.orgpaperAdded 8 Oct 2026, published 5 Oct 2026🛡️ Security

This paper evaluates whether Korean post-quantum crypto candidates (HAETAE, AIMer, SMAUG-T, NTRU+) and NIST PQC standards (ML-KEM, ML-DSA, SLH-DSA) can replace classical ECDSA/ECDH in the authentication and key-establishment path of ROS2/DDS-Security for UAV/UGV command channels. The authors build a feasibility envelope mapping each algorithm's key/signature size and handshake latency against real command-link constraints (message rate, MTU, latency deadline, bandwidth), then validate it with authentication-handshake measurements over emulated constrained links on a two-node testbed, producing a classical→NIST→KpqC comparison and per-channel-budget application guidance.

eprint.iacr.orgpaperAdded 8 Oct 2026, published 5 Oct 2026🛡️ Security

This paper presents an automated pipeline that uses a vision-language model to annotate leaf midlines in rendered orthographic views of maize point-cloud scans, then applies deterministic geometric algorithms and differentiable NURBS fitting to reconstruct editable, organ-level procedural 3D plant models without manual tuning or species-specific segmentation training. Evaluated on 100 field-grown maize plants from the MaizeField3D dataset, it achieves a median whole-plant Chamfer distance of 5.4 mm and recovers 99.4% of curated reference leaves at IoU ≥ 0.5, outperforming an earlier semi-automated pipeline. It demonstrates that VLM annotations can become reliable quantitative measurements when paired with correcting geometric post-processing, enabling scalable generation of 3D plant assets for high-throughput phenotyping and in silico breeding.

arxiv.orgpaperAdded 5 Oct 2026, published 2 Oct 2026🧠 AI

Patch-to-Prune (P2P) is a training-free framework that repurposes activation patching from mechanistic interpretability into an inference-time compute bypass for vision-language models, replacing unnecessary visual-token projections in certain decoder layers with fixed neutral proxy vectors while preserving sequence length, token order, and residual pathways. Tested on Qwen2.5-VL and LLaVA family models across seven multimodal benchmarks, P2P at 3 percent tolerance retains about 94 percent of dense accuracy while cutting FLOPs by 55 percent, and reveals that intermediate decoder layers do most of the task-relevant visual integration while early and late layers need little token-specific visual computation.

arxiv.orgpaperAdded 5 Oct 2026, published 2 Oct 2026🧠 AI

This arXiv preprint extends the concept of reward hacking to four distinct "proxy" layers in a staged RL training pipeline for legged robots: the reward itself, the curriculum gate, the evaluation statistic, and the reference motion. Using measurements from a continuous PPO policy lineage trained on a simulated 1.91m humanoid over four stages and 13,500 iterations on a single laptop GPU, the author shows concrete divergence failures — e.g., a curriculum gate built on averaged error that advanced at its rate limit while the gated skill was absent, and a batched push test whose synchronized resets aliased gait phase and misranked push magnitudes by danger. For each layer it proposes a reformulation that closes the divergence, including L1 costs, peak/outcome statistics, gate reachability checks, deterministic/phase-desynchronized evaluation, and function-preserving input widening for growing a single policy instead of retraining.

arxiv.orgpaperAdded 5 Oct 2026, published 2 Oct 2026🧠 AI

This paper shows that intervention-defined faithfulness metrics used to evaluate automated circuit discovery in mechanistic interpretability can favor a worse circuit over a better one, an objective-level recovery gap. Testing EAP, EAP-IG, ACDC, and Edge-SP across four human-reference tasks and InterpBench, the authors find KL-based faithfulness misranks 9.4%-41.2% of candidate circuit pairs under held-out resampling, and trace the cause to context distortion, where excluded signals change the inputs retained components operate on. Restoring selected signals from the intact model's execution repairs 96 of 100 persistent misrankings, showing the evaluation objective itself, not just the search algorithm, needs fixing.

arxiv.orgpaperAdded 2 Oct 2026, published 1 Oct 2026🧠 AI

Mimir is a physics-grounded LLM agent for long-horizon irrigation control that pairs a fast-timescale loop — where a structured physical interface and deterministic simulator verify, revise, and bound LLM-proposed actions before execution — with a slow-timescale loop that consolidates recurrent failure patterns into persistent contextual principles, while keeping the physical model, evaluator, and execution constraints immutable. Evaluated across multiple sites, crops, and years with a common retrospective evaluator, Mimir achieves the lowest aggregate control cost among tested baselines and uses about 51% less irrigation than historical schedule replay; ablations show forward simulation, verified revision, and persistent context are all necessary, and scaling LLM size or switching model families gives no monotonic improvement.

arxiv.orgpaperAdded 2 Oct 2026, published 1 Oct 2026🧠 AI

This paper names "LLM Parkinsonism" - the tendency of autonomous LM agents to keep acting (over-verifying, over-refining, repairing self-created complexity) after a task's goal is already met - and traces it to proposal generation, scope interpretation, progress assessment, and stopping authority all being concentrated in the same self-conditioned loop. It introduces Global Executive Control (GEC) v0.2, an uncertainty-aware governance layer that separates action generation from project-level control (scope, evidence, resource use, stopping), and evaluates it in a 24,000-episode matched-candidate benchmark under a 40,000-token ceiling: a first-candidate baseline hits 67.42% hard-goal success, a candidate-set control reaches 96.53%, and GEC matches that success (96.57%) while cutting mean token use about 36%. The results are from mechanistic simulations only; the authors flag live-model validation as still needed.

arxiv.orgpaperAdded 28 Sep 2026🧠 AI

Proposes a doubly-spectral stochastic (DSS) expansion for graph neural networks that unifies calibration, out-of-distribution detection, and distribution-shift robustness in a single representation: graph Fourier filters capture structural variation while an orthogonal-polynomial chaos coordinate captures latent stochastic variation. DSS-GNN (standalone) achieves the lowest Brier score across 14 node classification benchmarks without post-hoc correction, and DSS-Hybrid (a residual branch beside a deterministic encoder) achieves the best AUROC on most node-OOD settings and strongest shifted accuracy on all 7 GOOD concept-shift benchmarks under standard ERM. A capacity theorem shows the method matches chaos coefficients of Gaussian-latent random graph signals under full-rank assumptions with exponentially decaying truncation error.

arxiv.orgpaperAdded 29 Sep 2026, published 28 Sep 2026🧠 AI

EvE (Evolutionary Explorer) is a steady-state, population-of-four differential evolution optimizer with a targeted Adam fallback, proposed as an alternative to Adam for cheap, early ranking of configurations in hyperparameter and architecture search. Under a fixed evaluation-cost-matched budget it wins or ties Adam on 76% of 70 (problem, dimension) cells across seven scalable benchmarks up to one million variables, and on real tasks (MLP on MNIST, LoRA fine-tuning of a 1.5B-parameter LLM on two datasets) it finishes 1.7-3.9x faster at a modest quality cost. Inside successive halving on UCI Adult it completes hyperparameter/architecture searches 3.1-3.5x faster while ranking configurations nearly as consistently as Adam does with itself across seeds (Kendall's tau 0.66-0.69).

arxiv.orgpaperAdded 29 Sep 2026, published 28 Sep 2026🧠 AI

This arXiv paper proposes a certifier for structured, privileged agent actions such as paying an invoice, assembled from potentially corrupted documents and tool outputs, formalizing when multi-source corroboration can be trusted under indirect prompt injection. It uses a corruption-radius rule counted via minimum hitting sets over corruption-distinct evidence classes so laundered or re-published copies cannot fake a quorum, plus deterministic reconciliation and trusted anchors for single-sourced fields. Evaluated on 70,966 sanctions entities and 450 software-supply-chain provenance records, and against five LLM agents where a realistic injection fools all but one model and existing action-gating or provenance baselines are broken while the certifier admits no unsafe action.

arxiv.orgpaperAdded 2 Oct 2026, published 28 Sep 2026🛡️ Security

Aray is a deterministic-first YARA interpreter and positive-fixture synthesizer that generates benign, YARA-matching ELF/PE/generic artifacts to validate detection rules without storing or distributing live malware samples. Conventional code (not a generative model) canonicalizes rules, derives witnesses from regex/hex declarations, and performs extraction, layout, and binary serialization; an LLM is only permitted to propose constructive rule normalizations or residual-semantics judgments, never backend source or binary structure, and the pipeline supports a zero-inference execution path. Evaluated against 416 public YARA rules, it achieved 406/416 (97.6%) matches to the original upstream rule, with the design explicitly motivated by containment concerns raised by the July 2026 OpenAI–Hugging Face agent incident.

arxiv.orgpaperAdded 26 Sep 2026🛡️ Security

Introduces "skilder," a framework that bundles LLM agent capabilities into roles (skills, tools, instructions, and limits) delivered progressively through a single MCP server, so an agent starts with a minimal catalog and only gains tool access as it learns the roles a task requires. This structural approach enforces access control deterministically at the server layer rather than relying on prompt-based policy, addressing context bloat and governance gaps in enterprise tool-using agents. Evaluated against flat-context tool selection and multi-agent orchestration across 13 tasks and six models, showing zero unauthorized tool calls or parameter violations when agents completed the discovery protocol.

arxiv.orgpaperAdded 26 Sep 2026🧠 AI

This preregistered study audits whether black-box LLM judges give stable, reproducible readings on shared serving endpoints, running two campaigns across 52,988 request attempts. Same-window repeat rankings only reached Spearman 0.400 against a required 0.90, and byte-identical next-day replays agreed at 0.78 against a required 0.99, showing that a model name on a shared endpoint is not a frozen measurement instrument. The authors trace the failure to label-to-meaning mapping bias, tiny candidate gaps relative to instrument noise, and non-deterministic outputs on identical inputs, and propose a three-level snapshot-identity ladder plus design rules and a reporting checklist for anyone freezing eval gates on LLM judges.

arxiv.orgpaperAdded 26 Sep 2026🧠 AI

UnderSpecBench is a benchmark of 69 task families and 2,208 prompt variants testing whether coding agents (Claude Code, Codex, OpenCode) overstep action boundaries when given benign but underspecified DevOps instructions. It uses deterministic, side-effect-based oracles to classify outcomes as Safe Success, Wrong Target, or OverScope, finding that 55.8-67.8% of runs violate at least one action boundary — agents tend to guess rather than clarify or refuse, especially when the target is uncertain.

arxiv.orgpaperAdded 26 Sep 2026🧠 AI

This paper studies how open-source projects (SymPy, LLVM, matplotlib, OpenInfra, Apache Software Foundation, Linux Foundation) are adapting contribution policies to govern AI agent contributors — bots that plan changes, edit files and submit pull requests with limited human oversight. Using Most-Similar Systems Design and process tracing, the authors build a six-dimensional taxonomy (disclosure, responsibility, human oversight, licensing, enforcement, maintainer workload) and an ordinal Policy Maturity Score, then map documented agent incidents against these dimensions and against regulatory frameworks like the EU AI Act, NIST AI RMF's Agentic AI Profile, and ISO/IEC 42001/23894.

arxiv.orgpaperAdded 26 Sep 2026🧠 AI

This paper evaluates authentication code generated by five prominent AI coding assistants, combining static code analysis and dynamic penetration testing mapped against NIST SP 800-63B guidelines. It tests four prompting strategies (Basic, Secure, NIST-Based, and iterative Reprompting) and finds that basic and generically "secure" prompts consistently miss critical protections like brute-force resistance, session management, and password handling, while even a single-shot NIST-context prompt is structurally inadequate — only an iterative self-auditing reprompting loop achieves defense-in-depth. The authors argue enterprises must shift from single-shot prompt engineering to continuous, standards-driven verification pipelines for AI-generated auth code.

arxiv.orgpaperAdded 26 Sep 2026🛡️ Security

UnderSpecBench is a benchmark of 69 task families (2,208 prompt variants) grounded in real incidents and CVEs that tests whether coding agents (Claude Code, Codex, OpenCode) safely handle underspecified DevOps instructions rather than guessing at intent, target, or blast radius. Using deterministic side-effect oracles, the study finds 55.8–67.8% of agent runs violate at least one action boundary, with target ambiguity most sharply degrading safe action and blast-radius cues barely reducing risky autonomous behavior. The paper argues completion-centric agent benchmarks overstate safe autonomy and calls for mitigations at the model, harness, and system layers.

arxiv.orgpaperAdded 26 Sep 2026🛡️ Security

This paper compares AI-contributor policies across six open-source organizations (SymPy, LLVM, matplotlib, OpenInfra, Apache Software Foundation, Linux Foundation) using Most-Similar Systems Design and process tracing, deriving a six-dimensional taxonomy (disclosure, responsibility, human oversight, licensing, enforcement, maintainer workload) and an ordinal Policy Maturity Score. It then maps documented AI-agent incidents (nuisance PR volume, platform-level shutdowns) onto the dimensions each policy fails to govern, and cross-references the resulting gaps against the EU AI Act, NIST AI RMF (with the UC Berkeley Agentic AI Profile), and ISO/IEC 42001/23894 to show where regulatory and project-level policy leave the same holes unaddressed.

arxiv.orgpaperAdded 26 Sep 2026🛡️ Security

AutoMUD is a source-code-driven tool that generates Manufacturer Usage Description (MUD) network access-control profiles for IoT devices by statically analyzing firmware/source code rather than relying on live traffic observation. It combines static and syntactic extraction with retrieval-grounded LLM reasoning and deterministic validation to recover rarely-exercised or conditional communication paths, link each generated rule to its source-level provenance, and record excluded findings with explicit reasons for review. Evaluated on a Linux-based repository plus a controlled semantic fault-injection campaign, it produced structurally valid, traceable MUD profiles that let analysts detect, localize and correct propagated errors.

arxiv.orgpaperAdded 28 Sep 2026, published 25 Sep 2026🛡️ Security

Analyzes a common-mode collapse failure mode in Direct Feedback Alignment training and proposes mitigations, tested on MNIST and CIFAR-10.

arxiv.orgpaperAdded 28 Sep 2026, published 25 Sep 2026🧠 AI

This arXiv paper proposes checkability - whether a task has a cheap, deterministic intrinsic check that can reject incorrect outputs - as the deciding factor for whether local small language models (SLMs) can be trusted for network-automation tasks instead of sending sensitive configs, topologies and logs to a third-party frontier LLM. The authors build Touchstone, a local-first pipeline that runs seven off-the-shelf SLMs (1-8B params) to generate candidates, uses task-specific intrinsic checks to reject bad outputs, and escalates only unresolved cases to a frontier model, reaching 98.6 percent and 93.8 percent end-to-end accuracy on conflict-detection and intent-translation tasks while escalating just 16-17 percent of inputs. On TeleQnA, a knowledge-only benchmark lacking task-specific checks, Touchstone fails to match the frontier baseline, showing the escalation strategy only works when precise correctness checks exist.

arxiv.orgpaperAdded 28 Sep 2026, published 25 Sep 2026🧠 AI

NIST has published the initial public draft of Special Publication 800-82 Revision 4, "Guide to Operational Technology (OT) Security," updating the long-standing OT/ICS security guidance to cover a broader scope of programmable physical-world systems (industrial control systems, building automation, physical access control, transportation, and environmental monitoring/measurement systems). The draft revises the overview of OT topologies, common threats, typical vulnerabilities, and recommended safeguards/countermeasures, and is open for public comment until November 30, 2026.

nist.govpaperAdded 26 Sep 2026, published 21 Sep 2026🛡️ Security

NIST SP 800-82 Revision 4 is the initial public draft of the agency's core guide to Operational Technology (OT) security, covering industrial control systems, building automation, physical access control, and environmental monitoring/measurement systems. It updates OT threat models, typical topologies, and vulnerability descriptions, and provides recommended security safeguards and countermeasures for organizations running cyber-physical systems, with a public comment period through November 30, 2026.

csrc.nist.govpaperAdded 26 Sep 2026, published 21 Sep 2026🛡️ Security

APort Vault is a benchmark that replays 4,371 human-written CTF attacks against a live AI payment agent across 14 models from 8 labs, five policy configurations, and two replay tracks — with and without a deterministic pre-action check implementing the Open Agent Passport (OAP) specification. Across 225,964 evaluations, unauthorized transfers to non-allowlisted recipients occurred 140/76,842 times with the model alone versus 0/69,297 times behind the OAP layer, while the layer still allowed 25,370 legitimate payments through, showing a policy-enforcement layer can materially close the authorization gap in agentic payment flows without just refusing everything. The authors release all evaluations, level passports, scoring code, and analysis scripts.

arxiv.orgpaperAdded 21 Sep 2026, published 18 Sep 2026🛡️ Security

NIST has issued the initial public draft of SP 800-82 Revision 4, "Guide to Operational Technology (OT) Security," updating its long-standing guidance for securing industrial control systems, building automation, transportation, and physical access/monitoring systems. The draft covers OT system topologies, common threats and vulnerabilities affecting energy, manufacturing, and transportation sectors, and recommended security safeguards, with public comments open through November 30, 2026.

csrc.nist.govpaperAdded 28 Sep 2026, published 18 Sep 2026🛡️ Security

NIST IR 8587 is a final NIST report giving federal agencies and cloud service providers implementation guidance for protecting identity tokens, access tokens, and assertions from forgery, theft, and misuse. It builds on NIST SP 800-53 (Release 5.1.1) with architectural recommendations for identity providers and authorization servers covering key management, token verification, and lifecycle controls, aimed at securing SSO, federation, and API access scenarios following recent high-profile token-forgery attacks.

csrc.nist.govpaperAdded 3 Oct 2026, published 15 Sep 2026🛡️ Security

NIST IR 8587 is a finalized interagency report, developed with CISAs Joint Cyber Defense Collaborative under Executive Order 14306, giving federal agencies and cloud service providers implementation recommendations to protect identity tokens and assertions from forgery, theft, and misuse. It builds on NIST SP 800-53 Revision 5 to detail architectural guidance for identity providers and authorization servers, plus enhancements to key management, token verification, and token lifecycle controls covering SSO, federation, API, and workload access scenarios, informed by threats seen in recent high profile token theft attacks.

csrc.nist.govpaperAdded 26 Sep 2026, published 14 Sep 2026🛡️ Security

Programmable World Model decouples persistent world-state evolution from visual rendering in video world models: an agent compiles natural-language instructions into executable programs governing entity states and transition rules, which a lightweight engine executes and maintains as explicit global state (including off-screen entities and non-visual attributes). State-augmented 3D oriented bounding boxes plus camera trajectory are deterministically compiled into pixel-aligned conditioning signals fed to a pretrained video model that renders the scene, enabling playable games with predefined mechanics and direct entity control. On the paper's new CombatStateBench benchmark it achieves 94% Count Accuracy and 98% State Accuracy, beating existing interactive video world models on long-horizon coherence.

arxiv.orgpaperAdded 22 Sep 2026, published 9 Sep 2026🧠 AI

RegionFed is a federated learning framework for personalized retail search query understanding that operates at the gradient level rather than parameter level, using the ℓ2 conflict between regional and global gradients to diagnose heterogeneity and route regions to personalization strategies. Unlike existing parameter-level personalized FL methods that collapse below 10% accuracy on transformers like T5, RegionFed deploys unchanged across T5-Small, T5-3B, RoBERTa, and CNN architectures. Evaluated on Amazon ESCI, Amazon Reviews, and LEAF-FEMNIST, RegionFed-Meta reaches 92.27% accuracy, closing to within 0.23pp of a privacy-violating centralized upper bound while providing (ε≈0.60)-differential privacy.

arxiv.orgpaperAdded 22 Sep 2026, published 4 Sep 2026🧠 AI

A preregistered audit of whether identical requests to the same-named LLM API return stable outputs over time, finding they largely do not: across 52,988 audited requests, same-window repeat rankings hit Spearman 0.400 against a required 0.90, and next-day byte-identical replays hit 0.78 against a required 0.99. The authors trace the failure to label-mapping bias, candidate gaps far below the instrument's noise floor, and non-deterministic outputs for identical inputs, tested across four providers and self-hosted batch-invariant kernels, concluding a model name on shared infrastructure is not a frozen measurement instrument and that evaluations must characterize instrument noise before freezing any gate on it.

arxiv.orgpaperAdded 22 Sep 2026, published 3 Sep 2026🧠 AI

OWASP's 2026 update to the Top 10 for LLM Applications, developed by hundreds of AI security experts and grounded in real-world AI security incidents. It provides updated risk rankings, attack scenarios, and mitigations for prompt injection, model/data poisoning, and other LLM-specific threats, and maps each risk to NIST, MITRE ATLAS, CWE, and the OWASP Top 10 for Agentic Applications.

genai.owasp.orgpaperAdded 26 Sep 2026, published 4 Aug 2026🛡️ Security

This paper presents the first systematic evaluation of package-install-time supply-chain attacks delivered through ordinary project-setup documentation (README, requirements files, Makefiles) against production AI coding-agent harnesses. Testing frontier models across twelve scenarios in five attack classes grounded in real incidents, the authors find install-time security depends on the harness-model pairing rather than the model alone: agents reliably catch blatant typosquats but miss plausible separator-confusion names (e.g. azurecore for azure-core) and almost universally miss registry-redirection attacks, with the source blind spot recurring on npm and Cargo. A deterministic pre-install check that verifies package names, sources, and versions before code execution closes most of the gap.

arxiv.orgpaperPublished and added 18 Jul 2026🛡️ Security

WSO2 CTO Asanka Abeysinghe's architectural thesis argues that agentic AI systems break specification-based governance and instead require a control system spanning discovery, first-class agent identity and delegation, parameter-aware boundary authorization, runtime safety (prompt injection, jailbreaks, tool misuse, data exfiltration), deliberate human oversight, centrally-authored/distributedly-enforced policy, evidentiary observability, and economic (cost/budget) controls. It distinguishes inline governance (embedded in agent code) from infrastructure-enforced governance (gateways, proxies, service meshes, model/API gateways) and proposes a control-plane/data-plane split as the load-bearing pattern, referencing EU AI Act, NIST AI RMF, ISO 42001, and MCP registries as systems of record.

github.compaperAdded 3 Sep 2026, published 14 Jul 2026🛡️ Security