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theblock.coarticle🛡️ Security

North Korean hackers launder $242 million of Binance loot via Tron as FBI presses THORChain: analyst

The Block reports that North Korean hackers (TraderTraitor) laundered about $242 million of funds stolen from Binance through Tron in two days, according to analyst SomaXBT. Relay, THORChain, Chainflip and Symbiosis moved about $140 million off Tron. Elliptic counts $2.85 billion frozen or seized, 44% of $6.43 billion stolen, and $3.25 billion in assets no issuer can freeze. The FBI urged THORChain and others to block listed addresses.

TronTHORChain
TraderTraitorDPRKBinance+6

Blockchain, Threat Intel· Published and added 1 Nov 2026

bleepingcomputer.comarticle🛡️ Security

Alpine Linux rebuilds GitLab after attempted RCE attack

Alpine Linux rebuilt its GitLab server and reset all passwords after attackers tried to exploit CVE-2026-97229, a maximum-severity integer overflow in the Onigmo regex engine bundled with Ruby, on October 20-21. Eight worker crashes occurred and four were partially successful. Missing logs and outbound connection records meant compromise could not be ruled out. Alpine had run GitLab 19.3.4, then 19.3.6, which lacked the Ruby patch; the fixed image is alpinelinux/gitlab:19.3.6 with Ruby 3.3.13.

GitLabAlpine LinuxDocker+1
CVE-2026-97229integer overflowOnigmo

Supply Chain, Blue Team & Detection, DevSecOps· Published and added 1 Nov 2026

decrypt.coarticle🧠 AI

How to Run an AI Model Locally—And Why You Might Want To

Decrypt guide to running open-weight AI models locally with Ollama and LM Studio. It cites Epoch AI's finding that open models trail the best closed ones by about four months, and sets out VRAM and unified-memory needs (8GB minimum, 24GB for serious use), quantization, licences (MIT, Apache 2.0), install commands and Gemma 4 download sizes. It also notes that the largest open models, such as Qwen3.8-Max, exceed consumer hardware.

OllamaLM StudioHugging Face+7
DecryptEpoch AIGemma 4+11

inference, models· Published and added 1 Nov 2026

galaxy.comarticle🛡️ Security

Weekly Research Brief: Binance Hacked; Hyperliquid on Wall Street; Prediction Markets’ Brazil ‘Miss’

Galaxy Research's weekly brief of 30 October 2026 opens with the Binance hack: about $6.3b drained across 10 blockchains, attributed by TRM Labs and Chainalysis to TraderTraitor (Lazarus-linked). The attacker used EIP-7702 with 50 pre-signed authorizations on Ethereum, and Binance's preliminary finding is a compromised DevOps laptop reaching a service container. Tether and Circle froze about $2.6b. The other sections cover Hyperliquid and prediction markets.

EthereumBitcoinUSDC+2
TraderTraitorLazarus GroupEIP-7702+7

Blockchain, Threat Intel· Added 30 Oct 2026

galaxy.comarticle🛡️ Security

Here We Go Again: Binance Loses $6.3b in Largest Robbery in History

Galaxy Research newsletter on the roughly $6.3b drained from Binance across 10 blockchains, which TRM Labs and Chainalysis attribute to TraderTraitor. On Ethereum the attacker used EIP-7702 to turn a hot wallet into a sweeper contract backed by 50 pre-signed authorizations. Binance's preliminary finding is a compromised DevOps laptop, with no wallet key leak. Tether, Circle, Ripple and World Liberty froze about $2.7b; Galaxy also assesses Binance's ability to cover losses.

EthereumBitcoinTether+3
TraderTraitorLazarus GroupBinance+7

Blockchain, Threat Intel· Added 30 Oct 2026

x.comthread🧠 AI

Artificial Analysis (@ArtificialAnlys) on X

Hyperflow H3 is Video Rebirth's 8-step LoRA for MiniMax H3, released in September 2026 with open weights. Artificial Analysis ranks it #5 on AA-Video-I2V v2.1 and #3 on AA-Video-Editing v1.1, ahead of MiniMax H3 (768p). It costs $9.00 per minute for Image to Video and $18.00 for Video Editing at 1088p, under half of Dreamina Seedance 2.5 ($34.12 and $40.82). The thread gives per-capability and per-use-case breakdowns.

LoRAdiffusion model
Artificial AnalysisVideo RebirthHyperflow H3+6

models, evals, multimodal· Added 31 Oct 2026, published 30 Oct 2026

interconnects.aiarticle🛡️ Security

Was I wrong about open models & cyber risks?

Interconnects post in which Nathan Lambert revisits his claim that an open-weight release of Claude Mythos in April 2026 would have been survivable. He argues GLM-5.3 already crosses that capability threshold with little visible harm. He cites Epoch AI's GLM-5.3 Firefox file-exfiltration exploit and Joshua Saxe's trend data, and says recent vulnerability waves come mostly from closed models and general AI diffusion.

GLMFirefoxGitLab+1
MythosProject GlasswingPHP2Shell+9

AI Security, other· Published and added 30 Oct 2026

bleepingcomputer.comarticle🛡️ Security

CISA says max severity GitLab flaw now exploited in the wild

CVE-2026-97229 is a maximum-severity GitLab flaw in the CI/CD Regular Expression Compiler, caused by an integer overflow, that lets unauthenticated attackers run code via a crafted regular expression. CISA added it to the KEV Catalog and ordered federal agencies to patch under BOD 26-04. GitLab fixed it in CE/EE 19.4.2, 19.3.5 and 19.2.8, and Shadowserver tracks about 2,800 exposed CE instances.

GitLab
CVE-2026-97229CVE-2026-0723CVE-2026-110264+10

AppSec, DevSecOps, Threat Intel· Published and added 30 Oct 2026

securityweek.comarticle🛡️ Security

Max-Severity GitLab Vulnerability Exploited Against Alpine Linux

CVE-2026-97229 is a CVSS 10 code execution flaw in Onigmo, Ruby's regular expression engine, reachable through crafted CI/CD configuration in GitLab. Attackers used it against Alpine Linux's GitLab on 20 and 21 October 2026 and failed; Alpine rebuilt the instance and found no tampering with aports or packages. Self-managed installs with their own Ruby need Ruby 3.3.13, 3.4.12 or 4.0.9, not just GitLab 19.3.6. CISA added it to KEV.

GitLabRubyOnigmo+2
CVE-2026-97229CISA KEVBOD 26-04+1

AppSec, Threat Intel, DevSecOps· Published and added 30 Oct 2026

github.comrepo🧠 AI

rikugan: LLM reverse-engineering agent for IDA Pro and Binary Ninja

Rikugan is a reverse-engineering agent that runs inside IDA Pro and Binary Ninja. It has its own generator-based agent loop, context management, plan mode and 60+ tools, and does not depend on an external MCP server. An orchestrator spawns parallel subagents to analyze a binary. It supports Anthropic, Gemini, MiniMax, Kimi, OpenAI-compatible endpoints and Ollama, with per-model notes.

IDA ProBinary NinjaHex-Rays+6
RikuganClaude Opus 4.6Claude Sonnet 4.6+6

agents, coding-agents· Added 30 Oct 2026

github.comrepo🛡️ Security

rikugan: LLM reverse-engineering agent for IDA Pro and Binary Ninja

Rikugan is an open-source reverse-engineering agent that runs inside IDA Pro 9.0+ and Binary Ninja, with its own agent loop instead of an MCP server. It has 60+ tools (decompiler, xrefs, strings, types, IL/microcode), parallel subagent exploration, an experimental /modify natural-language patching command and an experimental Binary Ninja deobfuscation skill for control flow flattening and opaque predicates. It supports Claude, Gemini, MiniMax, Kimi, OpenAI-compatible endpoints and Ollama.

IDA ProBinary NinjaLLM+3
control flow flatteningopaque predicatesMBA expressions+1

Malware & RE, AI Security· Added 30 Oct 2026

x.comthread🧠 AI

Artificial Analysis (@ArtificialAnlys) on X

Artificial Analysis launched an HLE-Diamond leaderboard in v5 of its Intelligence Index, covering the refined 1,000-question Humanity's Last Exam from CAIS and Scale AI. Each question runs once without tools, graded by GPT-5.6 Luna (medium) as pass@1. Gemini 4 Carbon (high) leads at 69%, Claude Opus 5.5 (max) scores 68%, and the top open weights model, Kimi K3.1 Pro, reaches 37%.

Artificial AnalysisArtificial Analysis Intelligence IndexHLE+9

evals, models· Published and added 30 Oct 2026

simonwillison.netarticle🧠 AI

API credits benefit for eligible ChatGPT subscriptions

Simon Willison's 29 October 2026 link post says OpenAI now gives ChatGPT subscribers on $100, $200 and $500 plans an equal amount of monthly API credits for one API organization. It matches the benefit Anthropic announced earlier in October 2026 for Max and Team plans, where the credits expire. Willison holds both subscriptions and says he may ship public demos funded by the credits.

ChatGPTOpenAI API
OpenAIAnthropicSimon Willison

ai-policy· Published and added 29 Oct 2026

bleepingcomputer.comarticle🛡️ Security

Fake crypto app on Apple App Store linked to $23K wallet theft

Padre Terminal, a fake Solana meme-coin trading app on the Apple App Store, drained about $23,000 from 27 Solana wallets after users imported private keys, per blockchain investigator Iris. The app has been removed, but the drainer stayed active; Iris traced funds to two attacker wallets holding 229.66 SOL. Iris also flagged four other suspected impersonator apps (Axiom Pro: Focus, GMGN AI, HyperTerminal-HyperliquidTools, Pump Fun Tokens & Analitycs).

iOSSolanaUSDC
Padre TerminalIrispump.fun+8

Mobile Security, Threat Intel· Added 30 Oct 2026, published 29 Oct 2026

bleepingcomputer.comarticle🛡️ Security

Hackers exploit Cisco SD-WAN flaw to deploy custom KeyDrift malware

UAT-11473, a newly tracked APT cluster, exploits CVE-2026-20127, a max-severity authentication bypass in Cisco Catalyst SD-WAN Controllers (patched February 2026), to deploy the KeyDrift malware framework. KeyDrift's PolyFlame runs inside vdaemon processes, and LittleFilch hooks SSL_read to extract AES-256 IPsec keying material, saved to /var/tmp/vdaemon.bin and sent over UDP. Targets include space, defense and policy organizations. Talos sees overlap with Volt Typhoon's Silent Train network but makes no definitive link.

Cisco Catalyst SD-WAN
CVE-2026-20127UAT-11473UAT-8616+8

Threat Intel, Malware & RE· Added 30 Oct 2026, published 29 Oct 2026

latent.spacearticle🧠 AI

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.

vision-language model
ElorianGlimpseDecoyCount+17

evals, multimodal, models· Added 28 Oct 2026, published 29 Oct 2026

arxiv.orgpaper🧠 AI

Decompose, Estimate, Select: Coverage-Aware Context Construction for Long-Form RAG

Decompose, Estimate, Select is a coverage-aware retrieval pipeline for long-form RAG. It splits a query into subquestions, ranks candidates with a coverage-trained bi-encoder, predicts a document-by-subquestion coverage matrix with a cross-encoder, and picks documents by greedy maximum-marginal coverage. On TREC RAG 2024, α-nDCG@10 rises from 0.625 to 0.702 (gold-nugget bound 0.718). A grounded self-feedback loop raises V_strict by 0.086 over two passes.

RAGbi-encodercross-encoder+1
TREC RAG 2024α-nDCG@10V_strict

llm-apps, research· Added 31 Oct 2026, published 29 Oct 2026

arxiv.orgpaper🧠 AI

M-PFT: Angular Margin for Calibrated Prompt-Tuning of Fine-Tuned Vision-Language Models

M-PFT is an angular-margin method for prompt tuning of vision-language models that fixes base-to-novel dual miscalibration (underconfidence on base classes, overconfidence on novel classes). It adds two losses: minimizing the maximum cosine similarity between tunable class embeddings, and minimizing angular distance to each zero-shot embedding. Tests on 9 prompt-tuning methods and 15 datasets show lower novel-class calibration error at comparable accuracy and negligible overhead.

vision-language modelprompt tuning
arXiv

research, multimodal, training· Added 31 Oct 2026, published 29 Oct 2026

opensourcemalware.comtalk🛡️ Security

The OpenSourceMalware Show #27

The OpenSourceMalware Show #27 (28 October 2026) is a podcast episode with transcript. It covers the Brotli decoder bug (CVE-2026-111497) vendored in C code across Python, Rust and PHP, and how to find copies via decode.c. It also covers the LiteLLM v1.107.0 compromise from an unrevoked admin key and a relaxed release control, and the MALFEX npm campaign hiding payloads in PNG-header files, plus an AGENTS.md lure and DPRK fake fonts in TTF/OTF.

BrotliLiteLLMnpm+3
CVE-2026-111497Node2ShellPHP2Shell+10

Supply Chain, Threat Intel, DevSecOps· Published and added 29 Oct 2026

huggingface.coarticle🧠 AI

Introducing AnySpeechRecognizer and AnyDecisionModel: Open Models for Speech and Decisions on Apple Platforms

AnySpeechRecognizer and AnyDecisionModel are two Swift packages from Hugging Face. The first mirrors Apple's SpeechAnalyzer API with swappable engines (NVIDIA Parakeet, Alibaba Qwen3-ASR on Core ML) and adds Sortformer speaker diarization. The second returns typed yes/no, choice and score answers with probabilities via MLX, Core AI, llama.cpp, Jev or Ollama. The post gives M4 Max timings, model sizes and calibration options.

SwiftCore MLMLX+10
AnySpeechRecognizerAnyDecisionModelAnyLanguageModel+17

multimodal, inference, models· Published and added 29 Oct 2026

x.comtool🧠 AI

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.

Claude CodeRustOAuth+4
clauthAnthropic

coding-agents, ai-infra· Added 30 Oct 2026, published 28 Oct 2026

endorlabs.comwriteup🛡️ Security

Endor Labs AI SAST Finds Two Apache Kafka Zero-Days: Unbounded Memory Allocation from Brokers to Kafka Streams | Endor Labs

Endor Labs AI SAST found three unbounded memory allocation flaws in Apache Kafka, fixed under CVE-2026-114349 (DefaultRecord decoder, a ~90-byte compressed batch that kills consumers, brokers and the log cleaner) and CVE-2026-111551 (ListDeserializer and Kafka Streams AssignmentInfo decoding). The post gives code, reproducers and payload bytes. Remediation: upgrade to 4.2.2, 4.3.2 or 4.4.0, set max.decompressed.message.bytes, restrict write and group ACLs, and alert on DeadThreadCount.

Apache KafkaKafka StreamsJava+1
CVE-2026-114349CVE-2026-111551denial of service+4

AppSec· Published and added 28 Oct 2026

github.blogarticle🧠 AI

GitHub Universe 2026: Evolving every layer of the stack

GitHub Universe 2026 recap in which GitHub presents its agentic software delivery vision and new Copilot products: the Copilot app, Copilot Fusion multi-model routing, Copilot projects, session continuity, automations that learn from outcomes, and code review Max. GitHub Enterprise customers can use all Copilot features without a separate subscription. GitHub also reports added capacity, a multi-region Azure migration and a redesigned Git architecture.

GitHub CopilotGitHubGit+4
MicrosoftJay ParikhCopilot Fusion+4

coding-agents, agents, ai-infra· Added 29 Oct 2026, published 28 Oct 2026

surgehq.aiarticle🧠 AI

Dayjob: Tax – evaluating AI agents on 50 professional tax assignments

DAYJOB: Tax is Surge AI's benchmark of 50 professional tax assignments across eight practice areas, with 1,789 workspace files such as returns, K-1s, ledgers and IRS notices. Claude Sonnet 5.5 leads at a 10.8% pass rate (pass@1, 95% rubric threshold), ahead of Claude Fable 5.1 (9.6%) and Claude Opus 5.5 (9.2%). Case studies show agents missing deadlines and unverified marital-status assumptions.

Claude
Surge AIDAYJOBDAYJOB: Tax+7

evals, agents· Added 29 Oct 2026, published 28 Oct 2026

latent.spacearticle🧠 AI

[AINews] Anthropic ends Coding Interviews: "Hunger beats tenure"

AINews issue of 28 October 2026 from Latent Space. It leads with Felix Rieseberg's post on why Anthropic dropped coding interviews ("Hunger beats tenure"). It then recaps Genie 4, Axiom's Lean formalization of CFSG, claimed ETH refutations by OpenAI and Anthropic, Artificial Analysis Index v5, FrontierCode 2.0, Liquid LFM3, the Qwen3.8 phone-home dispute, and Anthropic's S-1. Reddit recaps are included; the page was truncated before the end.

LeanQwen3.8-27BvLLM+11
AnthropicFelix RiesebergGoogle DeepMind+40

models, evals, ai-policy· Published and added 28 Oct 2026

wiz.ioarticle🛡️ Security

PHP2Shell: Exploitation Attempts and Remediation Trends

Wiz Research follow-up on PHP2Shell (CVE-2026-109618, CVE-2026-109619) after the 21 October 2026 disclosure. Honeypot data shows two variants of an open source exploit kit, one stopped by post_max_size and the other by failed memory leaks and worker pinning, plus PHP2Shell-branded tools that rely on session poisoning and LFI. Daily exposed vulnerable machines fell about 67%.

PHPApacheRoundcube
CVE-2026-109618CVE-2026-109619PHP2Shell+7

Threat Intel, Offensive Security· Published and added 27 Oct 2026

securityweek.comarticle🛡️ Security

HPE Patches Dozens of Critical Flaws in Networking Products

HPE released patches for 72 vulnerabilities in the AOS-8 and AOS-10 wireless operating systems of its Aruba networking products, including 33 critical flaws. Eight max-severity bugs (CVE-2026-79844 to CVE-2026-79851) allow unauthenticated RCE, authentication bypass and arbitrary command execution. Fixes are in AOS 8.10.0.24, 8.13.3.1, 10.4.1.14, 10.7.2.7 and 10.8.1.2. HPE reports no exploitation in the wild and advises restricting management interfaces to a dedicated VLAN.

HPE Aruba NetworkingAOS-8AOS-10
CVE-2026-79844CVE-2026-79845CVE-2026-79846+5

Cloud & Infra· Published and added 27 Oct 2026

arxiv.orgpaper🧠 AI

AxisQ: Depth-Adaptive Channel--Frequency Quantization for Camouflaged Object Detection

AxisQ is a post-training quantization framework for camouflaged object detection (COD) that allocates activation bits by feature depth. It uses the channel domain for shallow features and the local-frequency domain for deep features, under a fixed per-layer average bit budget. It adds a boundary-aware Hessian approximation for reconstruction. On CAMO at W2A2, weighted F-measure improves 12.7% for CFRN and 33.3% for CamoFormer-P over the strongest baselines.

CNNTransformer
AxisQCFRNCamoFormer-P+1

research, inference, multimodal· Added 28 Oct 2026, published 27 Oct 2026

arxiv.orgpaper🛡️ Security

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

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

DiscordModel Context ProtocolLLM
BotLensDeBERTa

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

decrypt.coarticle🧠 AI

OpenAI Launches GPT-6.1 Terra, Its Half-Good AI Model at Half the Price

GPT-6.1 Terra is OpenAI's mid-tier model, released 26 October 2026 with standard API prices 50% below GPT-5.6 Terra. At low reasoning effort its factual error rate on an internal test fell from 53.6% to 16.7%, and at maximum effort it solved 50.3% of Terminal-Bench 4.0 tasks versus 21.5%. It is available in ChatGPT Work and Codex and as gpt-6.1-terra. All figures are OpenAI's own.

ChatGPTCodexOpenAI API
OpenAIGPT-6.1 TerraGPT-5.6 Terra+11

models, evals· Published and added 26 Oct 2026

x.comthread🧠 AI

The SI Maximalist (@thesimaximalist) on X

The SI Maximalist posts on X that OpenAI says GPT-6.1 Terra matches GPT-6 Astra on Agents' Last Exam, OpenAI's test of workplace software tasks, at one tenth of the token price. The model is available in ChatGPT Work, Codex and the API. The post only relays OpenAI's claim and gives no benchmark scores, exact prices or method.

ChatGPTCodexOpenAI API
OpenAIGPT-6.1 TerraGPT-6 Astra+2

models, evals· Added 27 Oct 2026, published 26 Oct 2026

minimaxir.comarticle🧠 AI

OpenAI and Anthropic cut their LLM prices by up to 80% within a few months. Why?

Max Woolf's post (minimaxir.com, October 2026) gives a dated timeline of OpenAI and Anthropic price cuts from June to September 2026, including GPT-5.6 Luna down 80%, Opus 5.5 at $4 / $20 / $0.20 and GPT-6.1 Sol at $2 / $10 / $0.10. It argues the cuts come from commodity models, open-weight competition (DeepSeek V4.1 Flash, Kimi K3.1 Pro, 29 OpenRouter providers) and possibly IPO positioning. It notes cache reads make up 96-99% of coding-agent token spend.

OpenRouterCodexClaude Code+3
OpenAIAnthropicGPT-5.6 Sol+16

ai-policy, coding-agents, models· Added 26 Oct 2026, published 25 Oct 2026

eprint.iacr.orgpaper🛡️ Security

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

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

Gabidulin codes
Philippe GaboritGuruswami-Vardy theoremTwisted Square Membership+2

other· Added 26 Oct 2026, published 25 Oct 2026

eprint.iacr.orgpaper🛡️ Security

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

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

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

other· Added 26 Oct 2026, published 25 Oct 2026

x.comarticle🧠 AI

huiwenhan (@huiwenhan) on X

PRAXO-CORE 2.5.0 is a Go agent kernel that owns model calls, tool authorization, context, checkpoints, events and human-in-the-loop decisions, and leaves graph execution, memory storage and tenant policy to RHEOVELA or the host product. The release adds pkg/conformance, with checks for VFS, memory, sandbox, event, policy, model and tool contracts. It also adds stricter Windows path rejection and a plugin trust/SBOM handoff, and it states which adapters are only offline-tested.

GoOllamaModel Context Protocol+6
PRAXO-CORERHEOVELARHEOVELA-ee+4

agents, ai-infra· Added 27 Oct 2026, published 25 Oct 2026

arxiv.orgpaper🧠 AI

Sliding Networks: A Family of Residual Structures Preserving Feature Learning and Feature Diversity

Sliding Networks is a family of residual network structures with a joint width and depth scaling recipe that keeps both locally maximal feature learning and feature diversity in the residual stream. The key quantity is the ratio N_flat/(N_sharp L) tending to a constant alpha, and Half Copy correlated initialization can relax the shape constraints. Residual-MLP experiments support an SDE limit, but language-model experiments show performance differences under regrouping at fixed parameter count.

Transformer
arXiv

research· Added 27 Oct 2026, published 24 Oct 2026

arxiv.orgpaper🧠 AI

Learning What to Share: Expert Specialization for Time-Series Forecasting

Persistent Closed-Form Routing (PCR) is a plug-and-play method for multivariate time-series forecasting. It alternates exact conditional estimation of channel-specific mixture weights with gradient training of low-rank residual experts around a frozen pretrained forecaster. Across eleven datasets and three backbones, PCR-K4 cuts dataset-balanced MSE by 3.86-14.25% and beats competing specialization methods with fewer trainable parameters. The paper also introduces GalaxyTS, a synthetic dataset with exact shared and channel-specific references.

Mixture of ExpertsTransformer
GalaxyTSPCRPCR-K4+1

research· Added 27 Oct 2026, published 24 Oct 2026

decrypt.coarticle🛡️ Security

Sweden's Government Offices Block ChatGPT and Claude, Keep Microsoft Copilot

Sweden's Government Offices will block ChatGPT and Claude on staff computers from 26 October 2026 and leave Microsoft Copilot as the only approved AI tool, citing information security. Digitalisation director Mikael Wettercrantz said unvetted AI use had involved sensitive inputs and poorly handled outputs. The Tax Agency and National Board of Institutional Care have similar bans, and the European Parliament disabled AI features in February 2026. Whether Copilot has Claude models enabled is unconfirmed.

ChatGPTClaudeMicrosoft Copilot
Swedish Government OfficesMikael WettercrantzSveriges Radio+5

GRC· Published and added 24 Oct 2026

decrypt.coarticle🧠 AI

Sweden's Government Offices Block ChatGPT and Claude, Keep Microsoft Copilot

Sweden's Government Offices will block ChatGPT and Claude on staff computers from 26 October 2026 and keep Microsoft Copilot as the only approved AI tool, after a security review. Director of digitalisation Mikael Wettercrantz cites sensitive data entered into open services and tools used without a formal contract. The Tax Agency and the National Board of Institutional Care have similar bans. The article notes Copilot can include Claude models, and the Government Offices has not said whether that is enabled.

Microsoft CopilotChatGPTClaude
Sweden's Government OfficesMikael WettercrantzSveriges Radio+7

ai-policy· Published and added 24 Oct 2026

arxiv.orgpaper🛡️ Security

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

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

LLMC
RALERepresentation-Aware Logical EnsembleAbstract Syntax Tree+1

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

arxiv.orgpaper🧠 AI

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

RALE (Representation-Aware Logical Ensemble) is a method for LLM-based vulnerability detection in C code. The authors train LLMs on raw source code, Abstract Syntax Trees and Control Flow Graphs, and find each representation works best for certain vulnerability classes. Combining the models with explicit logical rules and majority voting raises F1 from at most 73% for a single model to 78%, with gains in accuracy, precision and recall.

LLMstatic analysis
arXivRALE

research, training· Added 28 Oct 2026, published 24 Oct 2026

coindesk.comarticle🧠 AI

Block's new voice AI sounds eerily human, sparking awe and scam fears

Dessa is a voice AI model from Block, trained from scratch on human speech only, with no text stage. It listens while speaking, so it handles interruptions, laughter and tone changes. Block says it trained on one Nvidia GB200 NVL72 system and that it runs locally on a MacBook Pro with M4 Max or better. Model size, benchmarks and release date are undisclosed. Early access goes to a small group of AI safety researchers. Reactions split between praise and scam fears.

Nvidia GB200 NVL72MacBook ProApple M4 Max
BlockDessaJack Dorsey+7

models, multimodal· Published and added 24 Oct 2026

galaxy.comarticle🛡️ Security

Weekly Research Brief: PHP Vulnerability; Objections to OKX-ICE’s Stock Tokenization; Solana Alpenglow Ships

Galaxy Research's weekly brief includes a section on PHP2Shell, two decade-old PHP remote code execution bugs affecting versions back to 5.4, patched in an emergency release. It reports an Amazon honeypot exploit attempt four days before disclosure, thousands of attempts in the 10 hours before the patch per Cloudflare's Matthew Prince, and NSA and FBI offline advice. The author argues the bugs were found with GPT-5.6 Sol and that defence must become agentic. It also lists the week's other incidents, including a CVSS 10.0 GitLab bug and eMudhra's guessable private keys.

PHPWordPressOpenAI+3
PHP2ShellPatch the PlanetCalif+7

Threat Intel, AI Security· Added 24 Oct 2026

x.comadvisory🛡️ Security

Xavier Rivera (@XavierRiveraX) on X

CVE-2026-115560 is a PHP code execution bug reported two days after the PHP2Shell emergency patches. The post says those releases do not fix it and no emergency fix is planned. Only apps that switch session.serialize_handler to php via ini_set() before session_start() are exposed. The mitigation is session.upload_progress.enabled=0, which also covers anyone who applied it for the 21 October advisory. The post gives no technical root-cause detail.

PHP
CVE-2026-115560PHP2Shell

AppSec· Added 25 Oct 2026, published 23 Oct 2026

latent.spacearticle🧠 AI

[AINews] Black October

AINews issue for 21-22 October 2026, built from 12 subreddits and 544 Twitter accounts. It leads with "Black October", a 48-hour run of AI-found vulnerability disclosures (PHP2Shell, a GitLab CVSS 10 flaw, a LiteLLM 1.107.0 password stealer, eMudhra CA keys). It also covers MiniMax M3.1 Flash, Carbon-X and Flint releases, Artificial Analysis coding-agent and CritPt v2 results, and a METR/Redwood audit of OpenAI monitoring.

vLLMLiteLLMPHP+14
Latent SpaceAINewsAnthropic+43

models, evals, ai-safety· Published and added 23 Oct 2026

arxiv.orgpaper🧠 AI

SCI-AGENT-EXAM: Benchmarking Agents on Scientific Research Tasks

SCI-AGENT-EXAM is a workflow-oriented benchmark of 120 expert-curated tasks across 11 scientific fields and 7 task types from the Scientific Workflow Task Taxonomy (SWTT). Tasks need both executable and textual artifacts, scored by programmatic checks plus an expert-calibrated LLM judge. Ten frontier agents were tested: GPT-6 Astra scored highest at 80.9, but only 26.0% of its runs passed the 0.95 success threshold.

LLM
SCI-AGENT-EXAMScientific Workflow Task TaxonomyGPT-6 Astra+1

evals, agents, research· Added 26 Oct 2026, published 23 Oct 2026

decrypt.coarticle🧠 AI

Major Banks Find Rogue AI Agents Inside Customer Accounts—And They’re 'Horrified'

Decrypt summarizes an Axios report that major U.S. banks are finding unauthorized third-party AI agents inside customer accounts, often using the customer's own credentials. Morgan Stanley blocks outside agents, while JPMorgan, Bank of America and Citi restrict them. Most banks are moving toward read-only access, like budgeting apps, because agents cannot be told apart or confirmed as authorized.

Morgan StanleyJPMorganBank of America+5

ai-policy, agents· Published and added 22 Oct 2026

x.comthread🛡️ Security

Nagli (@galnagli) on X

Tweet by Gal Nagli (galnagli) saying a Gemini model turned the GitLab advisory for CVE-2026-110264 into a working heap exploit in 17 minutes, with the full chain done in about another hour. The flaw is a CVSS 10.0 unauthenticated RCE on self-managed GitLab servers, affecting 12 years of releases, found by joaxcar. The post links a The Hacker News article and gives no technical details of the exploit.

GitLabGeminiCVSS
CVE-2026-110264Gal Naglijoaxcar+1

Offensive Security, AI Security, AppSec· Added 23 Oct 2026, published 22 Oct 2026

arxiv.orgpaper🧠 AI

IFC-MCQ: Automatically Generating Multiple-Choice Benchmarks for Evaluating LLM Agents on IFC Data Retrieval

IFC-MCQ is a method that automatically generates multiple-choice benchmarks from Industry Foundation Classes (IFC) building-model files, so answers can be graded by exact option-set match instead of human or LLM review. Its taxonomy has 15 categories and 36 subtypes in four groups, with answer keys from the file and distractors from file values or rules. Two agentic setups, tool-based and code-based retrieval, showed category-specific failures and variation by IFC model and interface.

LLMIndustry Foundation Classes
IFC-MCQarXiv

evals, agents, research· Added 23 Oct 2026, published 21 Oct 2026

securityweek.comarticle🛡️ Security

‘Context Bombs’ Cut AI Attack Success by Misleading Agents With Fake Targets

Tracebit's research "Making attacking agents pay" describes nine "context bombs", hidden prompts planted in a target that misdirect attacking AI agents with fake targets and endless problems. They stopped all attacks by GPT 5.6 Cyber, Kimi K3, Qwen 3.8 Max and DeepSeek V4 Pro, cut GPT-6 Astra successes by 54% and Claude Opus 5 successes by 91%. The best bomb was a fake pen test report; surviving attacks cost 23x more.

GPT-6 AstraKimi K3Qwen+3
TracebitMaking attacking agents paycontext bombs+4

AI Security, Blue Team & Detection· Published and added 21 Oct 2026

arxiv.orgpaper🛡️ Security

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

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

LLM
indirect prompt injectionprompt injectionanti-forensics+1

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

arxiv.orgpaper🧠 AI

Monitorability Is Trainable: Post-Training for Chain-of-Thought Monitorability

Monitorability Is Trainable proposes an unsupervised post-training objective that maximizes mutual information between a model's chain of thought and its output. On three model organisms with degraded CoT (from compression, monitor optimization, and synthetic-document generalization), it recovers most or all lost monitorability. On undegraded policies it improves CoT monitor and activation probe prediction of unsafe behavior and raises consequential reasoning.

LLM
arXiv

ai-safety, research, training· Added 23 Oct 2026, published 21 Oct 2026

aikido.devarticle🛡️ Security

Software supply chain security best practices for 2026

Aikido's guide to software supply chain security controls for 2026, tied to real incidents. It covers a 48-hour package cooldown, ignore-scripts, lockfile enforcement, SHA and digest pinning, scoped tokens, FIDO2, developer endpoint protection, extension allowlists, agent sandboxing, MCP server vetting, slopsquatting, signed SBOMs and rotation drills. Examples include the March 2026 axios compromise and the March 2025 tj-actions/changed-files attack.

npmpnpmGitHub Actions+3
tj-actions/changed-filesCanisterWormGlassWorm+7

Supply Chain, DevSecOps, AI Security· Added 22 Oct 2026, published 21 Oct 2026

hirundo.ioarticle🛡️ Security

Qwen3-Coder writes less secure code when told it's for a US persona

Hirundo's case study on Qwen3-Coder-30B-A3B-Instruct, tested with the BaxBench SecretStorage task in Flask. Apps for a US defense contractor were 19% more likely to be hackable than for a Chinese one, and Hong Kong democracy group apps leaked secrets 28% more often. A security instruction did not close the gap, but Hirundo's weight-edited "Westernized" model did. Semgrep with PurpleLlama rules flagged 2 of 1,840 apps; BaxBench attacks broke 1,144.

QwenDeepSeekCrowdStrike+3
HirundoBaxBenchBooz Allen+5

AI Security, AppSec· Added 22 Oct 2026, published 21 Oct 2026

hirundo.iowriteup🧠 AI

Qwen3-Coder writes less secure code when told it's for a US persona

Hirundo case study on Qwen3-Coder-30B-A3B-Instruct using the BaxBench SecretStorage task. Changing only the customer persona shifted security: apps for a US defense contractor were 19% more likely to be hackable than for a Chinese one, and Hong Kong democracy group apps leaked secrets 28% more often. Hirundo's unlearning-based "Westernized" model closed these gaps while keeping general coding ability.

Qwen3-Coder-30B-A3B-InstructBaxBenchHugging Face+5
HirundoQwen3-CoderQwen+12

evals, models, ai-safety· Added 22 Oct 2026, published 21 Oct 2026

securityweek.comarticle🛡️ Security

Chinese AI Model Writes More Hackable Code When Told It’s for US Contractor

Hirundo tested Alibaba's Qwen3-Coder-30B-A3B-Instruct by having it build 1,840 web apps for a US defense contractor, a Chinese defense contractor, a Hong Kong advocacy group and a neutral club. BaxBench broke into 1,144 apps; 70% of US contractor apps were hackable versus 59% for the Chinese one, and 74% when told to write secure code. Hirundo says removing the model's CCP alignment from its weights closes the gap.

QwenSemgrepLLM
HirundoBaxBenchPurpleLlama+5

AI Security, AppSec· Published and added 21 Oct 2026

securityweek.comarticle🧠 AI

Chinese AI Model Writes More Hackable Code When Told It’s for US Contractor

Hirundo tested Alibaba's Qwen3-Coder-30B-A3B-Instruct by having it build 1,840 web apps for a US defense contractor, a Chinese defense contractor, a Hong Kong advocacy group and a neutral club, scored with Semgrep, PurpleLlama rules and BaxBench. 70% of apps for the US contractor were hackable versus 59% for the Chinese one, and a security instruction did not close the gap. Hirundo says its unlearning of CCP alignment removed the bias.

Qwen3-CoderSemgrepLLM+1
HirundoAlibabaQwen+9

evals, ai-safety, training· Published and added 21 Oct 2026

eprint.iacr.orgpaper🛡️ Security

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

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

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

other· Added 24 Oct 2026, published 21 Oct 2026

arxiv.orgpaper🧠 AI

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

Protection Is Not One Event is a survey and human-coded evidence map of 118 RAG defense papers, grouped by measured endpoint into a seven-family taxonomy (kappa=0.867 across 32 annotators). It finds that only 17.8% of studies use content disclosure as their primary endpoint, and that most evaluations use general QA data and non-adaptive attacks. In a testbed on Qwen3-8B, an 8-gram guard cut copying to 0.0%, yet a three-query adaptive attacker still recovered 48.3% of hidden facts. Taxonomy, dataset, coding protocols and testbed are released.

RAGLLMQwen3
Qwen3-8BarXiv

research, evals, llm-apps· Added 24 Oct 2026, published 21 Oct 2026

arxiv.orgpaper🛡️ Security

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

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

QwenLLM
prompt injection

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

en.cryptonomist.charticle🧠 AI

GPT-6 legacy programming improves as GPT-6.1 Sol scores 97.9% on COBOL test

OpenAI reports gains in GPT-6 family coding for COBOL, Fortran and Visual Basic on two evaluations. On MultiLangBench (build a SQLite-compatible database engine from scratch), GPT-6 Astra averages 87.4% across 20 languages at maximum reasoning effort, versus 37.9% for GPT-5.6 Terra. On a COBOL migration benchmark, GPT-6.1 Sol reaches 86.6% at low effort and 97.9% at higher effort, versus 5.4% for GPT-5.6 Sol.

SQLiteC++Rust+1
OpenAIGPT-6 AstraGPT-6.1 Sol+4

models, evals, coding-agents· Published and added 20 Oct 2026

bankless.comarticle🛡️ Security

ZachXBT Flags $20M XMR Laundering Ring on Hyperliquid

FreedomXMR (FXMR) is a centralized Monero swap service on Hyperliquid Core that appeared in August 2026. ZachXBT's manual review of every inflow above $10K traced over $20M, more than 87% of volume, to ransomware, malware and exploits including DCENT Wallet, Fetch.ai, Axelar and Gamdom. The admin sources XMR liquidity from KuCoin and won the FXMR ticker in an auction for 518.28 HYPE.

HyperliquidMonero
ZachXBTFreedomXMRDCENT Wallet exploit+7

Threat Intel, Blockchain· Published and added 20 Oct 2026

latent.spacearticle🧠 AI

[AINews] not much happened today

AINews issue for 16 to 19 October 2026 from Latent Space, a digest of Twitter and Reddit AI news. It covers DeepSeek V4.1 Flash 1017 (552B total, 16B active MoE, AA Intelligence Index 45), MiniMax M3.1 Flash, Mercury 3, Meta Muse, Google's Harness², vLLM v0.32.0 and a Terminal-Bench audit. Only the first 40,000 of 47,045 characters were available.

Mixture of ExpertsGGUFllama.cpp+12
Latent SpaceDeepSeekDeepSeek-V4.1-Flash+42

models, evals, inference· Added 30 Oct 2026, published 20 Oct 2026

latent.spacearticle🧠 AI

[AINews] not much happened today

AINews issue covering 16-19 October 2026 from Latent Space, summarising 12 subreddits and 544 Twitter accounts. It leads with DeepSeek V4.1 Flash 1017 (552B total, 16B active MoE, 1M context, MIT license, AA Intelligence Index 45), plus MiniMax M3.1 Flash, Mercury 3 and Meta Muse. It also covers vLLM v0.32.0, InferenceX results, Harness² and Terminal-Bench audit findings.

Mixture of ExpertsvLLMSGLang+11
Latent SpaceDeepSeek-V4.1-FlashDeepSeek+43

models, evals, inference, agents· Published and added 20 Oct 2026

huggingface.coarticle🧠 AI

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.

PyTorchMetalMPSGraph+9
Hugging FaceAppleQwen3.6-35B-A3B+6

inference· Published and added 20 Oct 2026

arxiv.orgpaper🧠 AI

OpenVLHarness: Real World Visual Agentic Tool-Use with Multimodal Memory

OpenVLHarness is a multimodal reasoning harness for MLLMs built on a capability layer (task-level tool interfaces plus evidence rendering) and persistent multimodal memory that stores images, structured data and web references as addressable artifacts. A coding interface runs generated programs over stored data. Across 22 benchmarks and eight backbones it adds 9.7-12.6 points over no-tool baselines, and GPT-6 Luna at medium effort beats Codex and Visual Sketchpad at maximum effort using at most 37% of their tokens.

vision-language modelQwen3-VLCodex+1
OpenVLHarnessKimi K3GPT-6 Astra+3

agents, multimodal, research· Added 21 Oct 2026, published 19 Oct 2026

arxiv.orgpaper🧠 AI

Where is Physical RSI capability from? An Observational Scaling Law of LLM-as-policy

The paper introduces PhysRSI-eval, a five-axis metric for physical recursive self-improvement: first-attempt performance, efficiency, success, budget and improvement from failure. Several VLMs are tested on 18 manipulation tasks under a fixed interaction budget. It proposes the Physical Barrel Hypothesis and studies observational scaling. Workspace interventions show that removing history lowers late-round success, while frozen workspaces still help on unseen layouts.

vision-language modelLLM
PhysRSI-evalPhysical Barrel HypothesisarXiv

research, evals, multimodal· Added 21 Oct 2026, published 19 Oct 2026

arxiv.orgpaper🧠 AI

ASTOR: Benchmarking and Improving Autoformulation for Soft-Constraint Optimization with a Formal Grammar

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.

LLM
ASTORSoftORarXiv

research, evals· Added 21 Oct 2026, published 19 Oct 2026

arxiv.orgpaper🧠 AI

Assisted Turbulence Modeling via Data Assimilation and Machine Learning for Turbomachinery Flows

This paper presents a hybrid framework for axial compressor flow that couples a Multi-Fidelity Ensemble Kalman Filter (MFEnKF) with machine learning. The filter merges PIV experiments with steady RANS and unsteady hybrid RANS/LES simulations. A neural network trained on the enriched data predicts Navier-Stokes volume forcing terms from velocity, velocity gradients and turbulent viscosity. A Mixture of Experts fixes local errors near blade tips, giving lower experimental discrepancy than baseline RANS.

Mixture of Expertsneural networkMulti-Fidelity Ensemble Kalman Filter+3
MFEnKF

research· Added 21 Oct 2026, published 19 Oct 2026

wiz.ioarticle🛡️ Security

Supply Chain Zero Days: Closing the Gap Between Publication and Detection

Wiz describes its pipeline that analyzes every new npm package version at publication, combining static analysis, an AI classifier, sandbox dynamic analysis and runtime sensor observation, then pushes IOCs to Wiz Defend before a CVE exists. It cites supply chain attacks rising from about 10% of significant incidents in H2 2025 to 25% in H1 2026, and the Axios compromise (v1.14.1, v0.30.4). The keyv case shows C2 domains fetched from an Ethereum smart contract, which only runtime monitoring caught.

npmWizEthereum
Axioskeyvcacheable+3

Supply Chain, Blue Team & Detection· Published and added 19 Oct 2026

heymaxwell.aiarticle🧠 AI

Maxwell: A new kind of model that sits between code and hardware

Maxwell (Maxwell's Daemon) is doubleAI's first "code execution model" (CEM). It runs inside a live program, finds bottlenecks and emits faster machine code for the exact CPU or GPU, leaving the source untouched. Each rewrite ships with a machine-checked proof of semantic equivalence, built on a formalisation of Python. Early access is announced; the post gives no benchmark figures.

PythonPyTorchRust+6
doubleAIMaxwellAlan Turing+3

models, inference, research· Added 20 Oct 2026, published 19 Oct 2026

artificialanalysis.aiother🧠 AI

DeepSeek V4.1 Flash 1017 (Max)

DeepSeek V4.1 Flash 1017 (Max) is an open-weights reasoning MoE model from DeepSeek with 552B total and 16B active parameters, a 1M-token context window, text and image input, and an MIT license. Artificial Analysis scores it 45 on its Intelligence Index (open-weights median 19), at $0.30 input and $1.20 output per 1M tokens, 216 tokens per second, and 210M tokens used in the evaluation. It is available through 10 API providers.

DeepSeekMixture of ExpertsLLM
DeepSeek-V4.1-FlashArtificial AnalysisArtificial Analysis Intelligence Index

evals, models· Added 20 Oct 2026, published 19 Oct 2026

securityweek.comarticle🛡️ Security

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.

CyberSNJobSpikrCyberSN Taxonomy

other· Published and added 18 Oct 2026

anthropic.compaper🧠 AI

How employment is changing at Anthropic

"How employment is changing at Anthropic" is an October 2026 technical report by Nathan Wilmers, Regina Catipon, Maxim Massenkoff and Peter McCrory. It uses internal employment, agent telemetry, output, survey, calendar and hiring data plus 17 interviews. Junior technical hiring fell from 27% to 9%, agent hours reached six times employee hours by August 2026, and adopters' output rose. Employees increasingly do meta-work managing agents.

ClaudeClaude CodeSlack+1
AnthropicNathan WilmersRegina Catipon+5

ai-policy, agents· Added 19 Oct 2026, published 18 Oct 2026

arxiv.orgpaper🛡️ Security

SoK: PIAtlas: Decomposing the Unbounded Prompt Injection Attack Space

PIAtlas is a taxonomy of prompt injection attacks organized by how the injected instruction subverts the model, with six mechanism classes as roots of a technique and sub-technique hierarchy. The authors release PICorpus, a license-clean collection of public prompt-injection datasets, and map thousands of records to PIAtlas under a human-verified protocol. Results show attacks combine several techniques from few mechanisms, agent benchmarks cover only part of the space, and adaptive attackers favor mechanisms that curated benchmarks underrepresent.

LLM
PIAtlasPICorpusprompt injection

AI Security· Added 21 Oct 2026, published 18 Oct 2026

github.comrepo🛡️ Security

OWASP/MCP-Security-Testing-Guide

OWASP MCP Security Testing Guide is a living, GPL-3.0 collection treating the Model Context Protocol as a security boundary from user through model, MCP client, MCP server and tool to the target system. It covers threats, secure development, host/client controls, supply chain, enterprise gateways, detection, incident response, taxonomy, public incidents, case studies and review checklists, with 79 tests in Chapter 3 (sections 3.1–3.19). It includes a finding template, and it links the MCP Goat lab for safe practice. It is useful to AppSec, red team and SOC people assessing MCP deployments.

Model Context ProtocolLLM
OWASPMCP Goat

AI Security, AppSec· Added 17 Oct 2026

github.comrepo🧠 AI

alex09x/kyb

KYB (Know Your Business) is a Rust/axum server that stores agent-written knowledge, incident reports and tasks as Markdown files in Git, one commit per change. Search is hybrid: Tantivy BM25 fused by reciprocal rank with local multilingual-e5-small ONNX vectors, and it can query historical versions or "as of" a date. It ships a kyb CLI, a native MCP endpoint (Claude Code, Codex, Antigravity, Gemini CLI), an installable agent skill, token auth with per-write attribution trailers, secret scanning on writes, and a web console. It targets persistent shared operational memory for multi-agent, multi-machine fleets.

RustGitModel Context Protocol+10
KYBAlexander Panasenkomultilingual-e5-small

agents, mcp, coding-agents· Added 17 Oct 2026

decrypt.coarticle🧠 AI

TokenMaxxing: How to Get the Most Out of Your AI Models

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.

Claude CodeClaudeChatGPT+8
DecryptAnthropicOpenAI+14

ai-infra, coding-agents, ai-policy· Published and added 17 Oct 2026

securityweek.comarticle🛡️ Security

Israeli Ad Firm Doubled as Candiru’s Zero-Click Spyware Delivery Channel

SecurityWeek summarizes Citizen Lab's AdFection report: Israeli ad firm Discover-Tech, via its Controlium platform, used targeted ads in RTB auctions to de-anonymize, fingerprint and zero-click infect devices with Candiru spyware. At least 45 Al Jazeera devices were targeted in 2024–2025, and an exposed server held four billion bid records spanning ~200,000 sites and apps. Google, IAB Europe, Beeswax and Eskimi cut off the firm; Citizen Lab recommends blocking targeted ads at the gateway.

AndroidiOS
CandiruDiscover-TechControlium+9

Threat Intel, Mobile Security· Published and added 17 Oct 2026

huggingface.copaper🧠 AI

OpenGCUA: Toward a Fully Open Stack for Generalist Computer Use

OpenGCUA, from Alibaba's MAI-UI team, is an open stack for generalist computer-use agents (GCUAs), where the model chooses how to observe, act and organize work across GUI, accessibility-tree, API and shell interfaces. Its design combines code execution (GUI actions written as programs with loops and branches) with harness-to-model decision transfer. On OSWorld-v2 it raises mean partial score by +19.6 points across eight models, including GPT-6 Astra and Claude Opus 5, and cuts reported steps per task by 53%. The release includes the harness, prompts, evaluation trajectories, a macOS real-device harness, a cross-device SDK and an interactive lab. It also shows large efficiency gaps between models: Qwen3.8-Max used 19.4x the reasoning tokens of GPT-6 Astra on real macOS tasks.

macOSGitHubHugging Face
OpenGCUAMAI-UIAlibaba+6

agents, research, evals· Added 17 Oct 2026

eprint.iacr.orgpaper🛡️ Security

Zippel: A Language, Compiler, Runtime, and Analyzer for ZK Proof Systems

Zippel is a language, compiler, runtime and analyzer for writing zero-knowledge proof systems in syntax close to the pseudocode in cryptography papers. Its type system and runtime remove vulnerability classes by construction, for example by synchronizing transcripts automatically and applying the Fiat–Shamir transform correctly. Its static analyses check completeness and soundness from the protocol description alone. The authors implemented 35 proof systems, including Sumcheck, Schnorr, KZG, Groth16, Bulletproofs, Hyrax, Spartan, Dory, HyperPlonk, DeKART and Pari. They report performance competitive with hand-written multi-core implementations.

ZippelRust
Fiat–Shamir transformSumcheckSchnorr+9

AppSec· Added 17 Oct 2026, published 16 Oct 2026

galaxy.comarticle🛡️ Security

Proving Humanity

Galaxy research report arguing that CAPTCHAs and behavioral bot detection (reCAPTCHAv3, Cloudflare Turnstile) are failing as AI agents reproduce human conduct, for example ChatGPT Agent clicking through Turnstile's checkbox. It shows that Web Bot Auth signatures and Google's AP2 mandates identify the platform or account key but not a distinct person. It proposes reframing "proving humanity" as ensuring every agent traces to one person counted once, covering Sybil, one-person-one-share, accountability and public-count harms. It lays out requirements for a proof-of-personhood credential: strong, private, portable, delegable and accessible. It deliberately does not evaluate specific projects.

CloudflareCloudflare TurnstilereCAPTCHA+3
proof of personhoodSybil attackliar's dividend+4

AI Security, Identity & Access· Added 16 Oct 2026

galaxy.comarticle🛡️ Security

Weekly Research Brief: Ledger’s $91M Theft, Papertrade

Galaxy Research's weekly brief leads with the roughly $91M theft from Ledger devices sold via the reseller CryptoBilis. A hidden hardware implant read the 24-word recovery phrase off the screen during setup and sent it over LTE through an eSIM, leaving the Secure Element untouched so Genuine Check still passed. Galaxy's onchain tally covers 474 victim addresses, 88% of the value moved in one hour on Oct. 9, and about $56.6M was still parked as of Oct. 15, with Tornado Cash use and a $10M Tether freeze. It places the theft alongside the Coldcard weak-seed, Liquid peg-out and Bitget compromises, and ends with buyer and custody advice. The Papertrade and OCC debanking sections are unrelated to security.

LedgerColdcardBitcoin+2
CryptoBilisGenuine CheckTornado Cash+8

Blockchain, Hardware & RF, Supply Chain· Added 16 Oct 2026

galaxy.comarticle🧠 AI

Proving Humanity

Galaxy Research essay arguing that as AI agents become the main way people use the web, the key question shifts from "is this a machine?" to "is a distinct real person behind it, counted once?". It traces CAPTCHA history (distorted text, image puzzles, reCAPTCHAv3 and Turnstile behavioral scoring) and notes ChatGPT Agent passing Cloudflare's checkbox. It reviews Web Bot Auth signatures and Google's AP2 payment mandates, showing both stop at the platform or key and never establish a person. It then covers harms (one-person-one-share abuse, no one to answer for an agent, distorted public counts, collapsing confidence, scaled deception, broken ad economics) and lists the properties a privacy-preserving proof-of-personhood credential needs: strong, private, portable, delegable, accessible.

Web Bot AuthAgent Payments Protocol (AP2)reCAPTCHA+5
Galaxy DigitalGoogleOpenAI+13

agents, ai-policy· Added 16 Oct 2026

galaxy.comarticle🛡️ Security

Inside the $91M Ledger Reseller Wallet Theft

Galaxy Research newsletter piece on the roughly $91M theft from buyers of Ledger hardware wallets sold by the reseller CryptoBilis. A hidden component reads the 24-word recovery phrase off the screen during setup and sends it over LTE via an eSIM. The Secure Element and Genuine Check are untouched, so the check passes on tampered units. It traces the drain across 474 victim addresses on Bitcoin, Ethereum and TRON, including 88% of the value moving in one hour on Oct. 9, and the laundering and freezes (Tornado Cash, Tether). It also places the incident among the quarter's other custody and infrastructure failures (Coldcard weak seeds, Liquid, Bitget) and gives buying and operational guidance.

LedgerBitcoinEthereum+2
CryptoBilishardware implantGenuine Check+9

Blockchain, Hardware & RF, Supply Chain· Added 16 Oct 2026

arxiv.orgpaper🧠 AI

Acceptance Is Not Speed: Length Inflation in Training-Free Lossy Speculative Decoding

This paper shows that training-free relaxed (lossy) verification in speculative decoding causes length inflation: completions get longer, mostly through extended reasoning traces, which offsets gains in accepted tokens per round. Across twelve target-drafter pairs, relaxed rules accept 1.34x as many tokens per round but produce 1.54x longer completions. Rules that cut verifier rounds usually lose substantial accuracy, so the authors argue completion length and verifier rounds must be reported.

LLM
arXiv

research, inference, evals· Added 20 Oct 2026, published 16 Oct 2026

a16zcrypto.comarticle🛡️ Security

Fast post-quantum signature aggregation with lattice SNARKs

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.

FalconEthereumSolana+1
AerieAkitaLattice Jolt+17

other· Published and added 16 Oct 2026

a16zfrontier.comarticle🛡️ Security

Fast post-quantum signature aggregation with lattice SNARKs

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.

AerieFalconEthereum+2
AlpenglowleanVMXMSS+11

other· Added 22 Oct 2026, published 16 Oct 2026

microsoft.comarticle🛡️ Security

Managing open-weight model risk in enterprise deployments

Microsoft blog post introducing "Risk Management for Open-Weight Models in Enterprise", a joint Microsoft–NVIDIA paper. It proposes a shared risk taxonomy (Cybersecurity, Data Protection, Content, Human-AI Interaction, Bias) grounded in ISO standards and the NIST AI RMF. The paper maps evaluations to risks as evidence and argues that risk depends on the model, use case, deployment and safeguards, not on weight openness alone. It also covers how responsibility for controls shifts when enterprises self-host models, and points to a joint repository of evaluations. The first paper focuses on the model layer; runtime, harness and application layers are planned for later.

Microsoft FoundryNVIDIA
NIST AI RMFISO

GRC, AI Security· Published and added 16 Oct 2026

microsoft.comarticle🧠 AI

Managing open-weight model risk in enterprise deployments

Microsoft's announcement of "Risk Management for Open-Weight Models in Enterprise", the first paper in a planned joint series with NVIDIA. It proposes a taxonomy of five risk categories (Cybersecurity, Data Protection, Content, Human-AI Interaction, Bias). The approach is grounded in ISO standards and the NIST AI Risk Management Framework. It maps evaluations to risks as evidence, stresses that weight openness alone doesn't determine risk, and explains how self-hosting shifts responsibility for safeguards. A joint repository will collect evaluations, and later work will cover the runtime, harness and application layers.

Microsoft Foundry
MicrosoftNVIDIANIST+7

ai-policy, evals· Published and added 16 Oct 2026

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