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319 results for β€œfal”

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  1. Appraisal by AI: Model-driven victim prioritization in the VOLTA infostealer

    VOLTA (VOLTA-AUTODOXER) is a self-deleting Windows infostealer that, after theft and live session-based enrichment, POSTs an evidence bundle to OpenRouter so an LLM can rank the victim's assets by monetization value. It falls back across a Claude, Kimi and Gemini chain when a model refuses. Talos covers the builder model, the Chrome App-Bound Encryption bypass, the volta_debug.txt artifact and countermeasures such as blocking Chrome --headless.

    blog.talosintelligence.comwriteupPublished and added 31 Oct 2026πŸ›‘οΈ Security

  2. Meta’s AI-distilled model detector catches 79% at a 0.1% false-positive rate

    WM-Basin is a Meta method for detecting student LLMs distilled from watermarked teacher models, described in "Watermark Basins: Black-Box Detection of Distilled LLMs" (arXiv:2610.37266, 27 October 2026). It feeds a suspect model's API text into a clean probe model and checks gradient alignment with a key-specific watermark basin. It reached 79% true-positive rate at 0.1% false-positive rate across 1,200 students, versus 29% for the prior token-level detector. Clean-data fine-tuning and paraphrasing weaken it.

    en.cryptonomist.charticlePublished and added 30 Oct 2026🧠 AI

  3. ERC draft: Independent Simulation Result for (STVA)

    ERC draft "Independent Simulation Result" (STVA) defines a canonical, content-addressed SimulationResult structure that wallets, hardware devices or third-party verifiers can recompute from the same VerificationPayload and state snapshot. It specifies fields, a keccak256 or EIP-712 result hash, and Basic, Standard and Strict compliance tiers. The goal is to close UI/calldata mismatch attacks where a compromised frontend serves a false simulation. Open questions cover stateDiff encoding and prestate proofs.

    ethereum-magicians.orgotherPublished and added 30 Oct 2026πŸ›‘οΈ Security

  4. dfbench β€” depthfirst

    dfbench is a held-out benchmark maintained by depthfirst that scores frontier LLMs on defensive security work: vulnerability detection, validation (precision) and differential analysis between commits. It reports recall, precision, F1 and cost per task by model and thinking level, split by application, low-level and smart-contract code and by single or multi-repo scope. Overall detection recall runs from about 21% to 69%, with the top figure at $99.19 per task for Mythos 5; validation precision mostly falls between 15% and 49%.

    depthfirst.comarticleAdded 29 Oct 2026πŸ›‘οΈ Security

  5. Polymarket Pauses Trading as Prediction Market Investigates Security Incident

    Polymarket put its exchange in cancel-only mode and paused relayer actions on 29 October 2026 after users reported funds withdrawn without permission. Hudson Rock says a DebugBear-hosted script holds wallet-draining code that sells a logged-in user's positions and hard-codes the suspected attacker's wallet (about $2.65 million in POL, per Arkham) as fallback recipient. Polymarket blames a compromised third-party provider and promises to make users whole. Root cause and victim count are unconfirmed.

    decrypt.coarticlePublished and added 29 Oct 2026πŸ›‘οΈ Security

  6. 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.

    arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026πŸ›‘οΈ Security

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

    TextSeal2 is a distortion-free watermark for LLM output that keeps its signal under speculative decoding. It merges two or more keys into one virtual key coupled to fresh noise through AutoMark's Gaussian copula, and verifies drafts with an extra exponential race. On three LLMs it detects 8 to 22 points more 100-token answers than TextSeal at a 10^-3 false-positive rate.

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

  8. Can Frontier Models See Past a Decoy? Elorian Tests Visual Reasoning

    DecoyCount is a benchmark from Elorian and Mercor with 1,660 items that tests whether models count objects or fall back on visual shortcuts. Frontier models scored below 50%: GPT-6 Astra led with 43.17%, ahead of Gemini-3.8-flash (32.71%), Qwen3.8-max (28.31%) and Claude-Fable-5.1 (25.22%). CEO Andrew Dai says Elorian's Glimpse model scored 50.48% in a single internal run without tools, and contrasts visual reasoning with world models such as Atlas and Genie 4.

    latent.spacearticleAdded 28 Oct 2026, published 29 Oct 2026🧠 AI

  9. Stop Calling Them Provers: The Case for Calling ProVerif and Tamarin Symbolic Protocol Analyzers

    Nadim Kobeissi's ePrint paper 2026/2683 argues that ProVerif and Tamarin should be called symbolic protocol analyzers, not provers. It audits their published soundness arguments, finding false statements, missing proofs and gaps between paper and implementation, and reproduces reported Tamarin bugs that accept false claims. It also covers model gaps in parsers and state machines, weak secrecy queries and unjustified primitive equations. The page is an abstract only.

    eprint.iacr.orgpaperAdded 31 Oct 2026, published 29 Oct 2026πŸ›‘οΈ Security

  10. 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.

    arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026πŸ›‘οΈ Security

  11. NIK C2: The new AI-enabled command-and-control framework

    NIK C2 is a newly observed C2 framework with a Go-based 64-bit Windows implant that embeds an OpenAI Chat Completions client (ai_generate command), falling back to the victim's OPENAI_API_KEY. Talos details its 52+ commands, AES-256-GCM over WebSocket with HTTP fallback, credential, wallet and keystroke theft, screen-lock ransomware, AMSI bypass and anti-debug. It also lists a live C2 at 87.120.196[.]120 and total-sitevv[.]lol.

    blog.talosintelligence.comwriteupPublished and added 29 Oct 2026πŸ›‘οΈ Security

  12. High Precision Noise Cleaning for CKKS with Application to Asynchronous Threshold CKKS

    High Precision Noise Cleaning for CKKS is an IACR ePrint preprint (2026/2675) by Zhihao Li, Cheng Hong and Tao Wei. It composes lower-degree Hermite polynomials to reach output noise bounds such as 2^-300 for noise flooding, and uses this to build an asynchronous threshold CKKS scheme with strong simulation security in the random oracle model. In OpenFHE, binary-message cleaning falls from 9.63 s to 1.54 s.

    eprint.iacr.orgpaperAdded 31 Oct 2026, published 29 Oct 2026πŸ›‘οΈ Security

  13. 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.

    arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026πŸ›‘οΈ Security

  14. Big Bull (@BIGBULLapp) on X

    clauth is a Rust terminal UI for Claude Code that combines multi-account switching with a live 5h / 7d usage monitor. A fallback chain moves the user off an exhausted account before Claude Code blocks. It supports Pro, Max, Team and Enterprise OAuth accounts and custom API endpoints on Linux, macOS and Windows. The post notes that auto-switching means the tool decides when accounts change.

    x.comtoolAdded 30 Oct 2026, published 28 Oct 2026🧠 AI

  15. Leak Exposes 41,000 Homeland Security Workers–Including Undercover ICE Agents

    Icepick is a leaked archive of records on more than 41,000 Department of Homeland Security employees and contractors, published by Distributed Denial of Secrets in 2026 and said to come from DHS's Okta login system. WIRED's analysis covers CBP, ICE, HSI, USCIS and CISA staff, plus over 55,000 permission groups that reference undercover programs, Palantir Falcon, PenLink, Signal and Mobile Fortify. Okta says it has no evidence of compromise.

    wired.comarticleAdded 29 Oct 2026, published 28 Oct 2026πŸ›‘οΈ Security

  16. From Leniency to Suspicion: How an Open Post-Training Recipe Changes Whom LLM Fact-Checkers Believe

    This paper measures job-based doubt in LLM fact-checkers: judging a claim false more often when the poster has a lower-status job. It compares base and post-trained checkpoints of six model families on fact-checked claims with randomised poster profiles. Only the open TΓΌlu-3 recipe (OLMo-2 32B, TΓΌlu-3 70B) creates the effect, under one percentage point but reliable. In OLMo-2 32B the flip comes from one residual-stream direction and appears at supervised fine-tuning, confirmed on 400 new claims. None of seven commercial models doubts lower-status posters more.

    arxiv.orgpaperAdded 30 Oct 2026, published 28 Oct 2026🧠 AI

  17. 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.

    arxiv.orgpaperAdded 30 Oct 2026, published 28 Oct 2026πŸ›‘οΈ Security

  18. Post-Training Large Language Models with LLMON

    LLMON (LLM Object Notation) is a framework that separates executable instructions from passive data and requires explicit identifier-based execution. The paper post-trains Granite-4.1 3B and 8B base models on a 4.6B-token corpus of general, RAG and tool-calling data with distractor variants, using SFT then RL. Attack success rates on indirect prompt-injection benchmarks fall from 53-100% to 0.02-5.6%, with general capabilities preserved. It also adds attention-based per-layer diagnostics.

    arxiv.orgpaperAdded 30 Oct 2026, published 28 Oct 2026🧠 AI

  19. Can LLMs Uncover Hidden Physical Laws through Free Exploration?

    LongChang is an automated framework that builds simulated worlds with altered physical laws, such as heavier objects falling more slowly, to test whether LLMs can find the law by free exploration. Explorer LLMs manipulate objects and build tools without tasks or hints, while separate LLM agents generate scenes, review tool designs and grade reports. Across 12 LLMs, GPT-6 Astra reached a 16.7% discovery rate and the other 11 scored 0%.

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

  20. OpenAI Proves ETH Is False, and Crypto Twitter Has Questions

    Decrypt reports that OpenAI published a 67-page paper (dated 17 October 2026, revised 25 October) claiming its AI found a deterministic subexponential-time algorithm for counting 3-SAT solutions, which would refute the Exponential Time Hypothesis. The proof was formalized in Lean. Impagliazzo, Paturi and Ryan Williams are reviewing it independently and say this is not certification. Anthropic posted a Claude-credited 3-SAT paper on 26 October.

    decrypt.coarticlePublished and added 27 Oct 2026🧠 AI

  21. 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.

    eprint.iacr.orgpaperAdded 28 Oct 2026, published 27 Oct 2026πŸ›‘οΈ Security

  22. 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.

    eprint.iacr.orgpaperPublished and added 26 Oct 2026πŸ›‘οΈ Security

  23. CoinDCX confirms $16 million loss from retired wallets days after CEO called breach reports a β€˜false alarm’

    CoinDCX confirmed on 25 October 2026 that 15.99 million USDT (about $16 million) was drained from retired deposit wallets after its automated sweeping service failed and user deposits sat at old, vulnerable addresses. The exchange absorbed the loss and says cold-wallet funds are safe. The report covers CEO Sumit Gupta's earlier "false alarm" denial, ZachXBT's challenge and withdrawal advice, and the July 2025 $44 million hack.

    theblock.coarticlePublished and added 25 Oct 2026πŸ›‘οΈ Security

  24. 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.

    arxiv.orgpaperAdded 28 Oct 2026, published 25 Oct 2026πŸ›‘οΈ Security

  25. 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.

    eprint.iacr.orgpaperAdded 26 Oct 2026, published 25 Oct 2026πŸ›‘οΈ Security

  26. The rise and fall of Jev hype

    The essay uses the launch of Jev, TypeSafe AI's "System One" general-purpose classifier trained with RLCD, to dissect AI marketing patterns: name dropping, jargon, ambiguity, inflated claims and drama. The author argues Jev's hype peaked and collapsed within about 33 days, while open-weight rivals beat it on cost and performance. It also lists incremental advances since ChatGPT and four unsolved problems: abstract reasoning, continuous learning, embodiment and the economics of running AI.

    blog.alexewerlof.comarticleAdded 24 Oct 2026, published 23 Oct 2026🧠 AI

  27. Why AI Compute Comes in Rectangles β€” Erik Bernhardsson, Modal CEO

    Latent Space interview with Modal CEO Erik Bernhardsson after the company's $750M Series D at a $16B valuation, with a transcript. He explains why GPU demand does not match rectangular fixed-term capacity contracts and how Modal pools demand across customers. He covers sourcing from nearly 25 clouds on multi-year deals, the risk of falling GPU prices, sandboxes reaching about a third of revenue, and non-NVIDIA accelerators.

    latent.spacetalkAdded 23 Oct 2026, published 22 Oct 2026🧠 AI

  28. Who Is Sycophantic to Whom? Confident LLMs, Human Deference, and the Collapse of Trust Calibration

    This paper studies reverse sycophancy: whether users bend toward a confident, consistent, wrong LLM. In a within-subjects experiment, 32 participants learned science topics from five GPT-5-mini assistants with 0 to 100% of facts replaced by falsehoods. Scores fell from 7.4 to 2.9 out of 10, planted falsehoods were chosen on 60% of falsified items against 11% of correctly taught ones, and confidence stopped tracking correctness. It introduces a baseline-corrected Human Deference Index.

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

  29. 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.

    eprint.iacr.orgpaperAdded 24 Oct 2026, published 22 Oct 2026πŸ›‘οΈ Security

  30. TRIAD: Benchmarking Omni-Modal Ambiguity in Multimodal Large Language Models

    TRIAD is a benchmark for omni-modal ambiguity resolution. It has 327 hand-written text-image-audio queries in 86 scene groups across 18 ambiguity categories, and removing any one modality makes the answer non-unique. Across 14 omni-modal systems, the best model trails humans by over 20 points in group accuracy. Without answer options, model group accuracy falls to single digits, and leave-one-out tests show audio cues are often underused.

    arxiv.orgpaperAdded 23 Oct 2026, published 22 Oct 2026🧠 AI

  31. Is Claude Code safe for the enterprise? What the official settings cover, and what they don't

    Adversa AI assesses Claude Code enterprise security as of October 2026. Managed settings bind only Claude Code, can be edited by local admins, and are not read by Anthropic-hosted cloud sessions. Auto mode misses 17% of risky actions in Anthropic's test set. The article covers attacks on the harness (CVE-2025-59536, CVE-2026-21852, TrustFall, SymJack, GhostApproval) and recommends credential, egress, isolation and monitoring controls.

    adversa.aiarticlePublished and added 22 Oct 2026πŸ›‘οΈ Security

  32. Disentangling Robustness and Sycophancy in Multilingual LLMs

    The SC-matrix is an evaluation framework for multilingual LLM sycophancy. It crosses a model's competence (correct answer with no pressure) with its sycophancy (keeping that answer under pressure), so agreeing with a false premise can be told apart from not knowing the answer in that language. Results: equal aggregate sycophancy rates hide different failure mixes, high competence does not always protect, and reasoning-oriented mitigations beat directive ones.

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

  33. Your AI agent fixed the bug, but what else did it change?

    Trail of Bits releases patching-bugs and regression-hunt, two agent plugins built with OpenAI through Patch the Planet. patching-bugs reproduces bugs, writes fixes and runs a three-arm proof; regression-hunt traces diffs to real interfaces, confirms with live PoCs and a fresh-context replay. A review of 130+ merged PRs found 21 regressions, and regression-hunt gave 25% fewer false positives than a baseline Codex prompt.

    blog.trailofbits.comarticlePublished and added 21 Oct 2026🧠 AI

  34. Your AI agent fixed the bug, but what else did it change?

    Trail of Bits releases patching-bugs and regression-hunt, two Codex plugins from the Patch the Planet initiative with OpenAI. A review of 130+ merged patches confirmed 21 regressions (none broke a security protection). In preliminary tests regression-hunt gave 25% fewer false positives than a baseline Codex agent. Design uses live PoCs, strict schemas, a three-arm proof, and project THREAT_MODEL.md and PATCHING_GUIDELINES.md files.

    blog.trailofbits.comarticlePublished and added 21 Oct 2026πŸ›‘οΈ Security

  35. 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.

    eprint.iacr.orgpaperAdded 24 Oct 2026, published 21 Oct 2026πŸ›‘οΈ Security

  36. 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%.

    eprint.iacr.orgpaperAdded 24 Oct 2026, published 21 Oct 2026πŸ›‘οΈ Security

  37. 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.

    arxiv.orgpaperAdded 24 Oct 2026, published 21 Oct 2026πŸ›‘οΈ Security

  38. 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.

    arxiv.orgpaperAdded 24 Oct 2026, published 21 Oct 2026πŸ›‘οΈ Security

  39. 0xMarioNawfal - The Roundtable Show (@RoundtableSpace) on X

    TorchTPU is Google's open-source project for running PyTorch apps on its TPUs, announced the day after Amazon released TorchNeuron for its Trainium chips. Google says migration needs "a simple configuration change" with no rewrite. It worked with Meta, Hugging Face, and the vLLM and SGLang teams on compatibility, and added an agent suite that helps migrate apps and fix errors. The post is brief and gives no benchmarks.

    x.comthreadAdded 21 Oct 2026, published 20 Oct 2026🧠 AI

  40. OpenAI Buys Orchestra Bio to Put AI Agents in Charge of Drug Development Grunt Work

    OpenAI acquired Orchestra Bio, a San Francisco startup (founded fall 2022, about $20 million raised) whose AI agents track drug development programs, and will fold its team and platform into the Rosalind life sciences suite. The agents map how setbacks such as a failed manufacturing batch affect deadlines and compare responses, while scientists decide. Terms were undisclosed; Anthropic bought Coefficient Bio for about $400 million in April.

    decrypt.coarticlePublished and added 20 Oct 2026🧠 AI

  41. 0xMarioNawfal - The Roundtable Show (@RoundtableSpace) on X

    Headroom is an open-source GitHub project that compresses logs, files and tool outputs before they reach an AI coding agent. The tweet by RoundtableSpace claims up to 95% fewer tokens for JSON and about 20% fewer overall, with the same answers and lower API bills. The tweet gives no method or benchmarks, and the repo link is truncated.

    x.comthreadAdded 21 Oct 2026, published 20 Oct 2026🧠 AI

  42. Beyond 4 bits: Data-Centric Post-training Quantization and Recovery

    This paper studies 2-bit post-training quantization (PTQ) of six dense and mixture-of-experts models from 3.8B to 32B parameters. It finds the quantization representation matters most: vector codebooks give usable models where scalar PTQ falls to chance. Calibration and recovery data must be chosen jointly. The recipe uses about 2.3 effective bits per weight, keeps 89 to 97% of full-precision QA accuracy, and needs 1.4 to 30x less compute than the strongest QAT baseline.

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

  43. Latest open artifacts (#25): DeepSeek V4.1 Flash 1017, American-made models, and new regulatory controls in the US & China

    Interconnects' Latest open artifacts (#25) covers open-weight AI in fall 2026. Policy items: China's MOFCOM proposal for pre-approval of international model sharing, and a DHS order barring DeepSeek from federal civilian procurement. DeepSeek released its internal inference stack DeepInfer. Picks include MiMo-V2.6-Pro-RL, DeepSeek-V4.1-Flash-1017 (552B-A16B, MIT), Clef, Nemotron-3.5-Super-VL and Reflection's Beam-1.0 (Apache 2.0).

    interconnects.aiarticlePublished and added 20 Oct 2026🧠 AI

  44. Code2Video-Compass: A Comprehensive Benchmark for General-Purpose Code-Based Video Generation across T2V, I2V, and V2V

    Code2Video-Compass is a benchmark of 2,104 tasks for code-based video generation, where multimodal LLMs write executable programs that produce complete videos from text (T2V), image (I2V) or video (V2V) inputs. Tasks span 10 categories and 24 subtypes. Scoring uses 12 objective metrics and five MLLM-judge metrics. Across 15 proprietary and open-weight models from nine families, performance falls as construction, dynamic animation and state-dependency complexity rise.

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

  45. 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.

    arxiv.orgpaperAdded 22 Oct 2026, published 20 Oct 2026πŸ›‘οΈ Security

  46. Is Sycophancy a Form of In-Context Updating?

    "Is Sycophancy a Form of In-Context Updating?" argues that factual sycophancy, a model's deference to a user's false beliefs, is a failure of in-context updating rather than only a bid for approval. Models also revise answers for claims attributed to external sources, more so when better supported, and deference persists when no user approval is at stake. The internal components behind deference also matter causally for general updating, so reducing sycophancy may reduce useful updating.

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

  47. 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* = (β„“-1)N+⌈N/KβŒ‰ for imperfect faults, and two-layer transcript detection (305/305 hits, no false positives).

    eprint.iacr.orgpaperAdded 21 Oct 2026, published 20 Oct 2026πŸ›‘οΈ Security

  48. 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.

    eprint.iacr.orgpaperAdded 21 Oct 2026, published 20 Oct 2026πŸ›‘οΈ Security

  49. 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.

    eprint.iacr.orgpaperAdded 21 Oct 2026, published 20 Oct 2026πŸ›‘οΈ Security

  50. 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.

    eprint.iacr.orgpaperAdded 21 Oct 2026, published 20 Oct 2026πŸ›‘οΈ Security

  51. MPS in PyTorch 2.15

    PyTorch 2.15 MPS release post from the Hugging Face PyTorch team, covering the Apple silicon backend. It adds float8_e4m3fn tensors with F.scaled_mm, a native grouped matmul that speeds MoE decoding 5 to 6.5x (Qwen3.6-35B-A3B from 9.4 to 61.3 tokens/s on an M3 Ultra), and an 8x faster softmax. Wan2.2 VAE decode peak memory falls from 270 GiB to 8 GiB. It previews 2.16 attention on Metal.

    huggingface.coarticlePublished and added 20 Oct 2026🧠 AI

  52. Privacy with Leakage from Falsifiable Assumptions

    Privacy with Leakage from Falsifiable Assumptions is an ASIACRYPT 2026 paper by Francesco Berti and Itamar Levi. It replaces simulatability with "secure refreshing", a key-refreshing assumption that evaluation laboratories can test directly, and adds "strongly protected secure refreshing". Using these, it proves privacy of the PSV encryption scheme without assuming a leak-free component.

    eprint.iacr.orgpaperAdded 20 Oct 2026, published 19 Oct 2026πŸ›‘οΈ Security

  53. Evasive Inner Product Functional Encryption Is Broken Too

    Evasive Inner Product Functional Encryption Is Broken Too is a 2026 ePrint paper by Agrawal, Modi, Yadav and Yamada. It gives a counterexample showing the evasive IPFE assumption of Hsieh, Lin and Luo (Eurocrypt 2024) is false in full generality. The attack extends the 2025 PRFE counterexample and needs only the weak inner product functionality, not pseudorandom function computation. The authors conclude that letting the adversary choose unrestricted private coins breaks the Evasive LWE family.

    eprint.iacr.orgpaperAdded 20 Oct 2026, published 19 Oct 2026πŸ›‘οΈ Security

  54. Saylor (@Kev96790724) on X

    G-Krusch is an MIT-licensed, local-first Google Workspace hub built on Node.js 22 and SQLite WAL. It runs a 12-tool MCP server (SSE and Stdio) plus a REST bridge on port 5446 for Drive, Calendar and Gmail. It includes a 1,024-dimension hybrid Drive RAG with an embedding cascade (Ollama bge-large, then Gemini, then offline fallback) and FTS5 BM25. PDF extraction returns page citations. Tokens are kept in an AES-256-GCM vault; 30 of 30 tests pass.

    x.comrepoAdded 21 Oct 2026, published 19 Oct 2026🧠 AI

  55. IISFA: Ineffective Instruction-Skip Fault Attacks on Bitslice Implementations

    IISFA (Ineffective Instruction-Skip Fault Attack) targets bitsliced block cipher implementations protected by redundancy countermeasures. Skipping one bitslice instruction leaves the result unchanged only when all m S-box inputs fall in an ineffective set, so each released ciphertext restricts all m subkeys. The authors give known- and chosen-plaintext key-recovery procedures and expected injection counts, and recover keys in every trial on GIFT, SKINNY and PIPO implementations on an 8-bit AVR microcontroller using clock glitches.

    eprint.iacr.orgpaperAdded 20 Oct 2026, published 19 Oct 2026πŸ›‘οΈ Security

  56. Putting models to the secure coding test: Security rules

    Datadog Security Labs tests whether Project CodeGuard v1.4.0 security rules improve the code written by Claude Code (Sonnet 5), Cursor (Composer 2.5) and Codex (GPT 5.5). Each model built the same document portal app once. Only GPT 5.5 closed the cross-user document IDOR and improved clearly. Sonnet 5 and Composer 2.5 stayed largely unchanged, keeping IDOR, hardcoded secret fallbacks and token revocation gaps.

    securitylabs.datadoghq.comwriteupAdded 29 Oct 2026, published 19 Oct 2026🧠 AI

  57. Putting models to the secure coding test: Security rules

    Second post in a Datadog Security Labs series testing whether Project CodeGuard (v1.4.0) security rules improve code written by coding agents. Sonnet 5 (Claude Code), Composer 2.5 (Cursor) and GPT 5.5 (Codex) each built the same document portal, and the output was audited with Datadog Code Security and a Sonnet 5 code review. Only GPT 5.5 closed the cross-user IDOR; Sonnet 5 and Composer 2.5 stayed largely unchanged, including hardcoded JWT secret fallbacks and incomplete revocation.

    securitylabs.datadoghq.comwriteupAdded 29 Oct 2026, published 19 Oct 2026πŸ›‘οΈ Security

  58. US Cybersecurity Job Postings Fall 26% as AI Security Engineer Demand Soars

    SecurityWeek summarises CyberSN's Cybersecurity Jobs Report. US cybersecurity postings fell 26.4% to 235,786 for January–September 2026, a four-year low. AI Security Engineer demand rose 268.3% and Cyber Data Scientist demand rose 203.5%. Penetration Tester (-45.9%), Threat Hunter (-40.0%) and CISO (-38.9%) postings dropped, and the CISO figure matches 2024 after an unusually strong 2025. Just under 15% of postings mention AI, peaking at 20.0% in September. The report counts postings by work required (CyberSN's 45-role taxonomy) rather than by job title, and it describes what changed, not why.

    securityweek.comarticlePublished and added 18 Oct 2026πŸ›‘οΈ Security

  59. [Draft ERC] Swarm AI Framework β€” registry and charter model for purpose-bound agent swarms

    Ethereum Magicians discussion of a draft ERC, the Swarm AI Framework. It proposes a registry and charter model in which accounts, including autonomous agents, form, bound, run and dissolve purpose-bound swarms. A hashed on-chain SwarmSpec (roles with eligibility modules, phases, decision authorities, fallback timers) is paired with an off-chain Swarm Pack charter. Two-sided signed admission (EIP-712 / ERC-1271), challenge and substitution, and minor versus material amendments are included. Phase posture is a coordinate: executed boundary and admission, plus declared payoff, topology and coordination terms from a write-once vocabulary. This lets cooperation, competition, tenders, debate, ensembles and pipelines be expressed. It integrates with ERC-8004 agent identity and ERC-8436 decision adapters. The reference implementation is a non-upgradeable registry with five eligibility modules and a task-tender adapter. The post asks reviewers specific design questions on vocabulary, amendment classes, roster snapshots and digest kinds.

    ethereum-magicians.orgthreadPublished and added 18 Oct 2026🧠 AI

  60. eliasbiondo/antirion

    Antirion is an open-source AI gateway shipped as one Rust binary with a built-in admin console. It sits between apps and providers such as OpenAI, Anthropic, Bedrock, Vertex and vLLM, translating between OpenAI, Anthropic, Gemini and Bedrock dialects. It covers routing with fallbacks and circuit breakers, budgets, guardrails, caching, MCP and A2A gateways, SSO, and a benchmark against Bifrost 2.2.4 and LiteLLM 1.103.1.

    github.comrepoAdded 21 Oct 2026, published 17 Oct 2026🧠 AI

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