319 results for “fal”

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 2026🛡️ Security

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

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 2026🛡️ Security

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 2026🛡️ Security

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put its exchange in cancel-only mode and paused relayer actions on 29 October 2026 after users reported funds withdrawn without permission.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 2026🛡️ Security

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 2026🛡️ Security

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

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

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 2026🛡️ Security

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 2026🛡️ Security

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 2026🛡️ Security

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 2026🛡️ Security

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 2026🛡️ Security

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

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 2026🛡️ Security

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 Tülu-3 recipe (OLMo-2 32B, Tülu-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

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 2026🛡️ Security

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

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

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

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 2026🛡️ Security

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 2026🛡️ Security

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 2026🛡️ Security

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 2026🛡️ Security

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 2026🛡️ Security

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

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

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

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 2026🛡️ Security

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

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 2026🛡️ Security

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

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

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 2026🛡️ Security

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 2026🛡️ Security

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 2026🛡️ Security

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 2026🛡️ Security

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 2026🛡️ Security

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

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

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

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

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

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

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 2026🛡️ Security

"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

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

eprint.iacr.orgpaperAdded 21 Oct 2026, published 20 Oct 2026🛡️ Security

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 2026🛡️ Security

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 2026🛡️ Security

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 2026🛡️ Security

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

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 2026🛡️ Security

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 2026🛡️ Security

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

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 2026🛡️ Security

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

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 2026🛡️ Security

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 2026🛡️ Security

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

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

Forum announcement of a Zenodo preprint on post-quantum migration for censorship-resistant P2P steganographic tunnels. It argues that ML-KEM's prime modulus (q=3329) makes naive bit-packed ciphertexts statistically distinguishable from uniform noise, which gives a cheap passive DPI distinguisher. It also argues that composite PQ 0-RTT envelopes over 4.4 KB force fragmentation, which requires stateful reassembly before AEAD verification and reopens memory-exhaustion DoS in eBPF/XDP filters. Proposed fixes are algebraic uniformization (LWR lattices or inverse rejection sampling), sub-MTU hybrid or pure-PQ envelopes (Falcon-512, signcryption), and Fujisaki–Okamoto implicit rejection for constant-time silent drops. Aimed at Ethereum validator, libp2p and RPC transports facing harvest-now-decrypt-later threats.

ethereum-magicians.orgpaperPublished and added 17 Oct 2026🛡️ Security

Decrypt guide to "tokenmaxxing" reframed as maximizing value per token rather than burning tokens. It gives tiered tips: pick smaller models for simple jobs, write one clear prompt, start new chats, cap output length, and use free models (beginner); Claude Code commands like /model, /clear, /compact, /context, /mcp, /effort and plan mode (intermediate); and prompt caching via cache_control, 50% batch discounts, and agent budget limits like --max-budget-usd (advanced). Includes context on Meta, Amazon and Uber token leaderboards and spend, a worked invoice-processing example where routing cut cost from $30 to $3.90, and the Jevons paradox in falling token prices.

decrypt.coarticlePublished and added 17 Oct 2026🧠 AI

Presents a fixed-point C implementation of the Mitaka signing algorithm, a simpler, parallelizable Falcon (FN-DSA) variant. It replaces MitakaZ's wide integral Gram root decomposition with a fixed-point square Cholesky decomposition, which cuts the cost of integer Gaussian sampling, and proves bounds on intermediate values and representation errors without empirical assumptions. Signing averages 361 kcycles (Mitaka-512) and 707 kcycles (Mitaka-1024) on AVX2, and 4.0 and 7.8 Mcycles on an STM32F411 Cortex-M4F. This makes floating-point-free lattice signatures practical on constrained devices.

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

Post summarizing independent researcher Sammy Azdoufal's report on EnergizeLab's Eilik companion robots, which are marketed mostly to kids. Per the report, any registered user could read other families' chat transcripts through the vendor back office. An unauthenticated endpoint also lets anyone swap the robot's AI model, voice and personality (CVE-2026-105038, CVSS 9.8, PoC listed by the CNA). At the Oct 13 retest, 32 of 40 remotely testable findings were still open. The post notes that The Verge demonstrated the issue on its reporter's own toy, that vendor remediation is unverified, and that broader malicious compromise is unproven.

x.comthreadAdded 18 Oct 2026, published 17 Oct 2026🛡️ Security

Mercor's Benchmark Map tags prompts from 29 selected AI benchmarks to O*NET tasks with an LLM judge, following Wang et al. It covers 923 occupations and 18,797 tasks. It finds only 208 occupations have a task with at least 5 benchmark prompts, and about 90% of US working hours fall on tasks with little or no benchmark coverage. Coverage skews toward AI-exposed, high-wage-bill, high-importance tasks such as software engineering and law, and it leaves out smaller middle-income knowledge work and physical work. The page also tests O*NET-weighted occupation scores on the APEX benchmarks for four occupations, and lists the limits of the method: sparse items, saturation, quality weighting, and augmentation versus automation.

mercor.comarticleAdded 17 Oct 2026, published 16 Oct 2026🧠 AI

a16z crypto announces Aerie, a lattice-SNARK system that aggregates Falcon-512/1024 signatures into one ~66 KiB proof. On an M4 Max laptop it handles 32,768 signatures in 0.65 s (~50k/s), verifies in 54 ms, and costs ~42 bytes per signature. It benchmarks against Orthus and Ethereum's leanVM hash-based XMSS aggregation, and argues that recursion-free lattice aggregation is simpler than hash-only designs. It also covers Falcon's hardware-wallet and side-channel constraints and why private payments need lattice encryption such as ML-KEM.

a16zcrypto.comarticlePublished and added 16 Oct 2026🛡️ Security

Aerie is an a16z crypto and LayerZero Labs system that aggregates Falcon-512 and Falcon-1024 lattice signatures into one lattice SNARK. On an Apple M4 Max it aggregates 32,768 Falcon-512 signatures in 0.65 seconds, with 54 ms verification and about 42 bytes per signature. The post compares it with Ethereum's hash-based leanVM and XMSS plan and Orthus, and covers Falcon signing limits on hardware wallets.

a16zfrontier.comarticleAdded 22 Oct 2026, published 16 Oct 2026🛡️ Security

Predictable Scaling (PS) is a framework that predicts full-scale recommendation model performance from scaled-down proxies. It builds proxies with composable scaling functions along separate resource axes, then projects metrics to target scale by curve fitting with calibrated uncertainty. Of three predictors, even the raw proxy falls within repeated-run noise, and a Gaussian Process gives 15% lower relative MAE. On a task-specific ranker and a foundation ranker, PS ranks hypotheses correctly at 79-88% compute reduction.

arxiv.orgpaperAdded 20 Oct 2026, published 16 Oct 2026🧠 AI

ePrint paper presenting safeRNSgcd, which computes the single Bézout coefficient needed at the deepest level of Falcon's NTRU solver while keeping large integers in a residue number system. Centered explicit CRT recovers the exact low bits needed by SafeGCD batches using single-word fixed-point arithmetic. A C implementation integrated into ntrugen reduces inversion and private-key basis-generation cost on a Raspberry Pi 5 and two x86-64 CPUs, versus the original ntrugen and a variant that skips the unused coefficient.

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

Presents a modular, fully onboard UAV navigation pipeline that closes the "human-aware safety gap" of geometry-only planners. A shared BLIP encoder drives captioning and text-conditioned segmentation, which is fused with depth for 3D obstacle localization. Qwen-2.5-0.5B, stabilized with RAG and grammar-constrained JSON decoding, infers per-category risk once per class and caches the verdict. Perception runs at 10 Hz on a Jetson Orin NX, and fallback LLM queries take about 0.8 s off the control path. In Gazebo it gives roughly 3x fewer collisions than a geometric planner and raises semantics-aware landing success from 34% to 96%. The 224-pixel encoder input limits small-object perception at range.

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

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

Decrypt reports that developer Brandon Thomas released WordCraft, GridCraft and DeckCraft, MIT/Apache-2.0 open-source clones of Word, Excel and PowerPoint. They were written in Rust with Anthropic's Claude (Opus 5.5) as a clean-room rebuild and run natively on Windows, macOS, Linux and BSD, and in a browser. Coverage is high (WordCraft 88% of ribbon features, GridCraft 513 of 523 Excel functions), but the authors rate them only about 50–60% ready for real work. Every button is also an MCP command, so agents like Claude can drive the apps. The article is a useful data point on what AI-assisted "vibe coding" can produce in under two weeks, and on where it still falls short (file fidelity, stability).

decrypt.coarticlePublished and added 14 Oct 2026🧠 AI

Evaluates a native probabilistic decision model (Jev), Llama Prompt Guard 2 (22M and 86M) and an LLM judge on 47,611 held-out examples covering direct/indirect prompt injection, hard-benign inputs, obfuscation and distribution shift. The LLM judge has the best AUROC (0.897), followed by Jev (0.871), Prompt Guard 2 86M (0.757) and 22M (0.714). Jev's native probabilities do not consistently beat post-hoc calibrated classifier scores, and temperature scaling improves calibration but not discrimination. At a 1% false-negative-rate target, every system needs over 91.8% escalation, so probabilistic outputs alone do not give reliable security decisions under distribution shift.

arxiv.orgpaperAdded 17 Oct 2026, published 14 Oct 2026🛡️ Security

Explains how to add AWS Continuum for penetration testing (formerly AWS Security Agent) as a post-deployment gate in CI/CD. Each run is scoped to the commit range since the last passing gate, and it can block promotion to production at a chosen severity threshold. It covers OIDC federation to a least-privilege IAM role, a GitHub Actions worked example, staged report-only rollout, and pitfalls: the baseline advances on passing report-only runs, fail-on-infrastructure-error defaults to fail-open, GitLab pipeline variables can override the committed threshold, and runner credentials need protecting.

aws.amazon.comarticlePublished and added 14 Oct 2026🛡️ Security

Describes a scam-detection model built by Google DeepMind with GovTech Singapore that runs entirely on the user's device. A low-power message classifier screens incoming messages, then a Gemma model fine-tuned on local scam conversations (impersonated institutions, banks, regional schemes) judges the wider conversation to confirm a threat or discard a false alarm. Fine-tuning ran in a GovTech-managed GCP environment on anonymised scam reports and intelligence feeds, with no PII. Chat access needs user consent, and the system gives real-time warnings. It shows a practical pattern of cascaded small models for battery-efficient, privacy-preserving local inference.

en.cryptonomist.charticlePublished and added 14 Oct 2026🧠 AI

Draft ERC from Quantova Inc proposing a "Quantum Bridge Shield" for Ethereum bridges. A committee signs the Merkle root of each message batch with RFC 8554 LMS hash-based signatures instead of ECDSA/BLS keys that Shor's algorithm can break. The guard contract requires a strict majority of distinct unfrozen keys, records used leaves, freezes any key that signs a leaf twice, binds digests to domain, chain, guard and epoch, and applies a 60-second delay. The post gives gas costs (LMS W4 height-10 verification about 205k gas, a LayerZero packet 128,683 gas, worst-case rotation 12.44M gas under the EIP-7825 cap) and cites a NioLabs assessment with no critical or high findings. It is relevant as a worked post-quantum migration design for bridge key custody, including hybrid ECDSA+LMS mode and stateful-signature pitfalls such as leaf reuse and rollback.

ethereum-magicians.orgarticlePublished and added 14 Oct 2026🛡️ Security

Trail of Bits tested 25 popular package managers with a Docker and mitmproxy harness that simulates a compromised package repository injecting malware into legitimate packages. Fewer than half enforce lockfile hashes by default, only two verified every download, and only Go verifies signatures by default. The post covers lockfile hash pitfalls (Pub, pnpm, Conan, CocoaPods, Composer), repository, developer and Sigstore signing, and Go's checksum database. It also proposes lockfiles that commit to a signing identity plus a transparency log.

blog.trailofbits.comwriteupPublished and added 14 Oct 2026🛡️ Security

DFIR case where a malicious MSI impersonating Advanced IP Scanner, sourced from a fake GitHub repo found via Bing, was imported by a customer into Microsoft Intune and deployed to four endpoints, running a Node.js-based EtherRAT chain. It traces the infections by correlating the MSI ProductCode, MDMAppInstaller/omadmclient process ancestry and Intune app inventory (Graph PowerShell query). It also covers renamed node.exe hash-hunting pitfalls, Ethereum RPC dead-drop C2 traffic, a screen-capture script and a second impersonating repo.

dfir.chwriteupAdded 14 Oct 2026, published 13 Oct 2026🛡️ Security

Open-source Python CLI (`tra`) for autonomous trading desks in which LLM analysts (technical, macro, on-chain, sentiment) and validators only give opinions on figures the system computed. Fixed rules do the arithmetic: pricing the round-trip cost, applying risk limits, sizing, cost gates, and sending a single order with stop attached via ccxt (Bybit and OKX demo accounts tested). It supports multiple model providers with per-role models, effort settings and fallbacks. Every answer is parsed against a closed schema, every refusal is logged with the figure behind it, and models can tighten but never loosen controls. This makes it a concrete reference for keeping LLM agents away from arithmetic and money.

github.comrepoAdded 18 Oct 2026, published 13 Oct 2026🧠 AI

News report on Anthropic's October 12, 2026 blog post saying new defenses cut reasoning-token extraction from Claude by 10x to 100x. The defenses are a two-stage extraction classifier (reported false positives under 0.1%), restrictions on reasoning transcripts, and account bans. It notes that training on full Claude Opus 4.8 reasoning transcripts scored 80.4% on SWE-bench Verified against 71.8% for summarized ones. It also covers the API changes: preserved thinking on Claude Fable 5.1 and Opus 5.5 for accounts created on or after August 31, 2026, plus Sonnet 5.5 transcripts limited to the generating organization. The article also covers alleged distillation by Zhipu (GLM-5.3) and Moonshot's Kimi, and calls for cross-industry cooperation.

en.cryptonomist.charticlePublished and added 13 Oct 2026🧠 AI

Reports Anthropic's disclosure that new anti-distillation defenses cut reasoning-token extraction from Claude by 10–100x. The defenses are preserved thinking (API accounts created on or after Aug 31, 2026 can't edit prior context), per-organization transcript access limits, a two-stage extraction classifier with under 0.1% false positives, and escalating limits and bans. It also covers attacker tradecraft (hundreds of thousands of fraudulent accounts, proxy networks, stolen payment details, hidden-reasoning extraction), attribution of Zhipu's GLM-5.3 and Moonshot's Kimi traffic, and the national-security argument for cross-provider cooperation.

en.cryptonomist.charticlePublished and added 13 Oct 2026🛡️ Security

Introduces Sauron, an evidence-first agentic verifier that checks rubric criteria for long-horizon agent tasks by investigating both environment state and execution trace, and trusts a claim (including an agent's self-reported success) only after validating it against its source. Bounded queries and joint investigation of related criteria cut context use, and each verdict carries an auditable evidence receipt. On 2,586 human-labeled criteria from 100 personal-assistant episodes it has the best F1 of five verifiers across eight backbones (0.96 vs 0.92 for Gandalf with GPT-5.6 Sol, at 23% lower cost). It detects 97% of injected failures across 13 fault families, including reward-hacking simulations, with 2% false flags on clean controls, and leads on the TRAIL agent-error benchmark. It matters because unreliable rubric verdicts used as RL rewards can reinforce bad behavior.

arxiv.orgpaperAdded 14 Oct 2026, published 13 Oct 2026🧠 AI

Anthropic describes its layered defenses against distillation attacks, in which fraudulent-account networks harvest Claude's reasoning transcripts to train rival models. The defenses are reasoning summarization, "preserved thinking" (new API accounts cannot edit prior context), restricted access to reasoning transcripts, a two-stage constitutional-classifier system with under 0.1% false positives, stricter usage limits and account bans, and charging for blocked requests. Anthropic reports 10–100x fewer extracted reasoning tokens, and a SWE-bench Verified drop from 80.4% to 71.8% when a model trains on summarized rather than full transcripts. It also argues that distilled models such as GLM-5.3 ship without proportionate safeguards and pose national-security risks, and that platforms and other labs must act too.

anthropic.comarticlePublished and added 13 Oct 2026🧠 AI

Anthropic describes how it countered industrial-scale distillation attacks on Claude, in which proxy networks of hundreds of thousands of fraudulent accounts (stolen payment details, false identities) tricked models into revealing hidden reasoning. Defenses include a two-stage constitutional-classifier system (<0.1% false positives), "preserved thinking" that blocks edits to prior context for new API accounts, restricting reasoning transcripts to the originating organization, stricter limits, bans, and charging for blocked requests. It reports 10–100x fewer reasoning tokens extracted, cites Zhipu's GLM-5.3 and Moonshot Kimi forwarding as examples, and discusses trade-offs and the need for platform-wide action.

anthropic.comarticleAdded 14 Oct 2026, published 13 Oct 2026🛡️ Security

Explainer on Static Application Security Testing. It covers how SAST builds an AST and runs taint analysis from sources to sinks, which flaw classes it catches (SQLi, XSS, hardcoded secrets, weak crypto) and which it misses (IDOR and other access-control bugs). It compares SAST with DAST and SCA, cites false-positive and false-negative figures (91% false positives in a 2025 study of about 3,000 repositories; 47–80% of vulnerabilities missed), and argues for reachability analysis and reasoning-based AI SAST. It ends with evaluation criteria and a rollout plan; the vendor's own benchmark claims are preliminary.

endorlabs.comarticlePublished and added 12 Oct 2026🛡️ Security

BrowseSafe++ extends BrowseSafe to 38,675 paired attacked/clean web pages, most with prompt injections observed in the wild on production sites. Pages cover twelve site types, 24 attack types and 18 injection locations, each given as HTML, Markdown, accessibility tree and screenshot with a user task and expected answer. The authors train BrowseSafe-Guard, two 0.8B detectors (text and screenshot) that beat a frontier-model-based detector on F1 with low false positives and low inference cost. BrowseSafe-Adapt rewrites injections using browser-agent feedback, raising attack success from a few percent to up to 95.41%.

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

Decrypt reports on REA (Reverse Engineer Anything), an open-source toolkit that uses MCP to connect AI coding agents such as Claude Code and Codex to reverse-engineering tools like Ghidra. It went from under 10,000 to over 100,000 GitHub stars in a week. The article describes AI-decompiled game ports and mashups, and ArtCraft, a set of Rust-built Photoshop-style apps that Brandon Thomas made with Claude Opus 5.5 as a clean-room rebuild. It also covers the copyright and takedown fallout (Activision, Bethesda) and what cheap agent-driven decompilation means for software protection.

decrypt.coarticlePublished and added 12 Oct 2026🧠 AI

WIRED reports that federal agents obtained warrants in Minnesota and Pennsylvania to use cell-site simulators (Stingrays/IMSI catchers) to locate Jerome Richardson, a producer for Don Lemon charged over the Cities Church protest. Agents also applied for simulator warrants and pen register orders targeting journalist Georgia Fort and others. The piece notes that simulators collect data from bystanders' devices, that affidavits contained a false claim about chanting, and that WIRED used EFF's detection software to find signs of a simulator near the 2024 DNC in Chicago.

wired.comarticlePublished and added 12 Oct 2026🛡️ Security

Explains how FedRAMP treats false-positive SCA findings, which still have to be tracked in the POA&M and ConMon. It covers the deviation request (DR) process, the SCA problems of scale and missing context (manifest-based inventories, with 88% of imported code unused), and 30–180 day remediation SLAs. It argues that only high-confidence, function-level reachability that holds from any source is likely to satisfy a 3PAO. It then describes how Endor Labs uses call-graph analysis, SBOM/VEX output and rescanning to document false positives.

endorlabs.comarticlePublished and added 12 Oct 2026🛡️ Security

Anthropic's post on defenses against illicit distillation of Claude, which it says cut reasoning tokens harvested by distillers 10 to 100 times. The methods are preserved thinking (no editing of prior context for accounts created on or after 31 August 2026), a two-stage classifier with under 0.1% false positives, and stricter limits, bans and charges for blocked requests. It also covers trade-offs and the GLM-5.3 and Kimi cases.

anthropic.comarticleAdded 29 Oct 2026, published 12 Oct 2026🧠 AI