ZeroHour
DashboardNewsCVEsExploitsIncidentsAIBriefAnalyticsEntitiesWatchlistIOCsAsk the feedSourcesFeeds & APIKiosk mode

Search: “diagnostics”

75 stories

Searchkeywordsmart Sortlatesthotimportancerelevance
DomainAllCyberAIWindow24h3d7d30dAllIn the wildImportant onlyShow duplicates
CategoryAllVulnerability 174Ransomware 132Industry 101Exploit / PoC 90Malware 89Policy & legal 60Data breach 57AI research 36Threat actor 32Phishing & fraud 22Research 11Advisory 10AI tools & infra 9Tools 8
SeverityAllcritical 363high 194medium 90low 126info 76

Before You Poll with LLMs: A Deliberative Diagnostic Framework

Deliberative diagnostic shows all five tested frontier LLMs misrepresent human belief shifts after arguments, with GPT-5.1 reversing on outgroup questions.

The Deliberative Polling Diagnostic Framework compares human and LLM persona belief shifts after identical informational interventions, using data from America in One Room (526 personas, 72 questions). All five frontier models tested failed uniquely: GPT-5.1 exhibited partisan reversal (80% on outgroup vs 26% on policy questions), Gemini 2.0 Flash, Claude Sonnet 4.5 and Llama 3.3 70B overshot at 5-7x human magnitude, and DeepSeek V3 showed near-zero change (rigidity). The authors term the underlying signature 'self-sycophancy', conformity to the model's internal persona stereotype rather than reasoning from provided information.

arXiv cs.AI / cs.LG / cs.CL · 2d agoAI research

Performance of Clinical AI System and Physicians and Frontier Language Models in primary care diagnostics

Clinical AI system Doctorina achieved 82.0% primary-care diagnostic concordance versus 57.0% for physicians across 150 synthetic consultations.

The study compared Doctorina, eight physicians, and four standalone frontier language models on 150 synthetic Polish-language primary-care consultations. Doctorina achieved 82.0% Top-1 diagnostic concordance versus 57.0% for physicians (25.0-point difference, 95% CI 17.7-32.7) and 97.3% versus 85.0% primary-or-reference-differential concordance. Normalized workup and treatment scores were 89.4 versus 66.9 and 83.7 versus 61.2. Kimi K3 ranked next on diagnosis, while Claude Opus 5 led the closely spaced management estimates among Opus, Doctorina and Kimi.

arXiv cs.AI / cs.LG / cs.CL · 8d agoAI research

The hidden work of modernizing Malwarebytes

Malwarebytes details its migration of Windows product managed components to .NET 10, citing security, supportability, diagnostics, and performance benefits.

Malwarebytes says it migrated the managed portions of Malwarebytes for Windows to .NET 10 while leaving native drivers and the detection engine untouched. The vendor cites a supported runtime, safer defaults, stronger cryptography, better diagnostics, and JIT/GC performance improvements as benefits. The migration also deprecated Windows 7 support, and the company applies staged rollouts and automated validation because its code runs with elevated privileges on millions of endpoints. No vulnerabilities or incidents are described.

Malwarebytes Labs · 12d agoIndustry1

Perturbation Probing: A New Diagnostic for the Fragility of LLM Safety

Unit 42 research shows LLM safety refusals concentrate in a thin neural layer, motivating external, multi-layered AI security controls.

Palo Alto Networks Unit 42 introduces Perturbation Probing, a diagnostic technique for measuring the fragility of LLM safety mechanisms. The research finds that safety refusal behavior is localized within a thin neural layer, implying small perturbations can undermine built-in refusals. The authors argue this motivates external, multi-layered security defenses on top of model-internal safety training.

Palo Alto Unit 42 · 18d agoAI safety & security

LexFlip: A Dissociation Diagnostic for Legal Meaning Preservation Metrics

LexFlip releases 373 minimal perturbations of Quebec statutory French that reverse legal force while preserving tokens, exposing weaknesses in embedding-based meaning preservation metrics.

LexFlip provides 373 minimal perturbations of Quebec statutory French that reverse legal force while preserving 0.93 of tokens, creating dissociation items that break monotone token-overlap metric validation. The seven embedding and BERTScore metrics tested register only 0.022-0.039 of their identical-to-unrelated range on these edits, versus 0.670 for bidirectional NLI. Against FrJudge, with a measured human ceiling of r=0.597, a bare length feature outscores every semantic metric tested.

arXiv cs.AI / cs.LG / cs.CL · 12d agoAI research

Right Tool, Right Job: Native-Language Evaluation, Tokenizer Sensitivity, and Methodological Findings from a French-Only BabyLM

French BabyLM entry METRON-FR (125M GPT-2, 92.47M words) shows tokenizer artifacts dominate child-scale zero-shot evaluation; proposes standard diagnostics.

METRON-FR is a 125M-parameter GPT-2 pretrained on 92.47M French words, submitted to the BabyLM 2026 Strict track, scoring 85.97% on the native Quebec-French QFrBLiMP benchmark and 62.80% on the BabyLM-weighted leaderboard. A cross-lingual GLUE protocol combining French task-data translation with rank-16 LoRA shows relational tasks gain while world-knowledge tasks regress. Bilingual Lexicon Induction reaches p@1 of 68.84%, 18x above chance, and ablations show single-token zero-shot scoring is dominated by tokenizer and template artifacts at child scale.

arXiv cs.AI / cs.LG / cs.CL · 1d agoAI research

Top 10 Best Mobile Device Management (MDM) Solutions in 2026

A 2026 MDM buyer guide ranks ten solutions, recommending Microsoft Intune for Microsoft 365 estates and Jamf for Apple-only environments.

A 2026 buyer guide evaluates ten mobile device management solutions, leading with Microsoft Intune as the default for Microsoft 365 organizations and Jamf for Apple estates. It recommends choosing the enrolment model before selecting a vendor and clarifying BYOD visibility to prevent privacy disputes. Kandji, Mosyle, Omnissa Workspace ONE, ManageEngine, Scalefusion, and Hexnode are covered as alternatives. Guidance ties MDM to Zero Trust data access policies via Apple User Enrolment and Android work profiles.

Cyber Security News · 7d agoIndustry

What’s next for CISA’s CDM program that gives cybersecurity tools to federal agencies

CISA officials outline future plans for the CDM program, emphasizing speed, automation, unified data, and data-driven federal risk management.

Speaking at an Elastic Federal Cyber Defense Breakfast, CISA officials described next steps for the Continuous Diagnostics and Mitigation (CDM) program that supplies cybersecurity tools to federal agencies. Acting deputy program manager Richard Grabowski named velocity, unification, and data-driven risk management as core goals, including a three-year roadmap to expand SIEM-as-a-Service. Federal CISO Mike Duffy urged aggregating demand across agencies, buying outcomes rather than products, and designing acquisition for continuous improvement. CISA's Matt House tied the program's evolution to post-SolarWinds needs for a government-wide common operating picture.

CyberScoop · 21h agoPolicy & legal

Understanding the Usability of Cryptographic Verification Tools

Survey of Tamarin and ProVerif users reveals usability barriers: debugging non-termination, model validation, and opaque proof failures hinder cryptographic protocol verification.

The paper presents an exploratory human-centered survey of researchers, graduate students, and practitioners with hands-on experience using Tamarin, ProVerif, and related cryptographic protocol verification tools. Findings reveal usability barriers across the verification workflow, including difficulties debugging non-termination and performance issues plus the lack of systematic methods for validating formal models against real protocols. When proofs fail without concrete attacks, users commonly simplify models, add helper lemmas, and revisit modeling abstractions. Participants called for actionable diagnostics, clearer explanations of results, visualization, and automation for recurring proof tasks.

arXiv cs.CR · 1d agoResearch

Root-Cause Attribution Is a Search Problem: Continual Search for Long-Horizon Agent Failures

Continual Search framework iteratively prompts LLM judges to keep searching agent execution logs, boosting long-horizon failure root-cause attribution accuracy.

The paper frames automated root-cause attribution (RCA) for long-horizon AI agent failures as a search problem, since relevant evidence is sparse and distributed across massive execution traces. The authors propose Continual Search, an iterative framework that nudges an LLM judge across successive turns to keep hunting unresolved diagnostic evidence instead of settling on an early plausible diagnosis. They introduce MegaRCA-Mix, a benchmark of 50 human-annotated failure trials on long-horizon, execution-heavy tasks. On MegaRCA-Mix, Continual Search improves GPT-5.5's F1 from 0.349 to 0.498 (over 40% gain), and lower-tier models can surpass higher-tier counterparts when search is effective.

Hugging Face daily papers · 5d agoAI research1

Threat Matrix: Mapping threats across cloud web applications

Microsoft released a Cloud Web Applications Threat Matrix, a MITRE ATT&CK-aligned framework mapping threats to cloud-hosted web apps and serverless platforms.

Microsoft introduced the cloud web applications threat matrix, which organizes attack techniques for cloud-hosted web apps and serverless platforms using MITRE ATT&CK tactics, from resource development through impact. The framework covers attack paths spanning application code, managed runtimes, workload identities, and deployment pipelines, cataloging techniques such as subdomain takeover, code injection in connected repositories, compromised registry images, exposed admin interfaces, and serverless trigger injection. It builds on Microsoft's earlier Kubernetes and storage services matrices to help defenders identify visibility gaps, prioritize hardening, and plan investigations in cloud-native environments.

Microsoft Security Blog · 6d agoTools

ActReview: Rebuttal-Guided Training Data and Rubric Rewards for Actionable Peer Review Generation

ActReview post-trains Qwen3-8B-Base on 40K rebuttal-derived instances with rubric rewards to generate actionable, grounded peer-review feedback, plus a 1,000-instance benchmark.

The framework builds ActReview-40K from real OpenReview review-rebuttal threads, aligning reviewer weaknesses with author responses and grounding feedback in localized paper evidence. Qwen3-8B-Base is post-trained with multi-task supervised fine-tuning followed by GRPO using candidate-aware, weakness-specific rubric rewards. Experiments show improved actionability and grounding over prior specialized review-generation models, supported by ActReview-Bench, a human-curated 1,000-instance evaluation set. Human evaluation confirms better revision usefulness while noting a remaining gap in technical accuracy.

arXiv cs.AI / cs.LG / cs.CL · 8d agoAI research

ActReview: Rebuttal-Guided Training Data and Rubric Rewards for Actionable Peer Review Generation

ActReview post-trains Qwen3-8B-Base on OpenReview rebuttals to generate actionable peer-review feedback with grounded revision suggestions, benchmarked on 1,000 curated instances.

The paper defines Actionable Peer-review Generation as diagnostic claim generation plus revision suggestion generation and introduces ActReview, a rebuttal-guided post-training framework. From OpenReview review-rebuttal threads the authors build ActReview-40K, aligning reviewer weaknesses with author responses grounded in localized paper evidence, and post-train Qwen3-8B-Base with multi-task SFT followed by GRPO using weakness-specific rubric rewards. They also release ActReview-Bench, a human-curated 1,000-instance benchmark, on which ActReview outperforms prior specialized review-generation models on actionability and grounding while remaining competitive with strong prompt-based LLMs. Human evaluation confirms improved revision usefulness but identifies a remaining gap in technical accuracy.

Hugging Face daily papers · 8d agoAI research

RoboSPA: Can VLA Models Go Beyond Simple Scenes and Short-Horizon Tasks?

RoboSPA introduces a 527K-trajectory robotic benchmark with 280 task variants exposing VLA model weaknesses in spatial reasoning and long-horizon planning.

RoboSPA is a large-scale robotic manipulation dataset and benchmark for diagnosing embodied reasoning in vision-language-action models, spanning fine-grained spatial reasoning and long-horizon procedural planning. It covers 10 task categories and 56 base tasks instantiated across five difficulty levels for 280 variants, with 527K trajectories collected across multiple embodiments. Experiments on representative VLA models show current systems struggle with complex spatial relations, precise low-level execution, and memory-intensive planning.

arXiv cs.AI / cs.LG / cs.CL · 12d agoAI research

RoboSPA: Can VLA Models Go Beyond Simple Scenes and Short-Horizon Tasks?

RoboSPA introduces a 527K-trajectory benchmark with 280 task variants showing current VLA models struggle with spatial reasoning and long-horizon planning.

RoboSPA is a large-scale robotic manipulation dataset and benchmark for diagnosing embodied reasoning in vision-language-action models, covering fine-grained spatial reasoning and long-horizon procedural planning. It spans 10 task categories and 56 base tasks instantiated across five difficulty levels for 280 variants, with 527K trajectories collected across multiple embodiments and diverse scenes. Diagnostic metrics go beyond binary success rates, and experiments show current VLA models struggle with complex spatial relations, precise low-level execution, and memory-intensive planning.

Hugging Face daily papers · 12d agoAI research

EU Chief Warns of AI-Powered Hacking, Moves to Rein In Social Media

EU Commission President von der Leyen warned AI will enable unprecedented hacking and announced Kids Act and Digital Fairness Act proposals regulating social media.

In her State of the European Union 2026 speech, Ursula von der Leyen warned that upcoming AI models 'will allow hacking on a level we never thought possible' and cited dangers of self-improving models, referencing a Hugging Face incident. She reaffirmed the AI Act as the core guardrail framework and pledged cooperation with Canada, the UK, and other partners. She also proposed a Kids Act banning social media under age 13 and personal accounts under 15, plus a Digital Fairness Act to be proposed in autumn.

SecurityWeek · 3h agoAI policy

Self-improving AI should slow down, von der Leyen tells EU lawmakers

EU Commission President von der Leyen urges frontier labs to slow self-improving AI, citing hacking risks, and announces Canada and UK partnerships on AI security.

European Commission President Ursula von der Leyen used her State of the Union address to call for slowing self-recursive frontier AI, warning that models in development will enable hacking at previously unimagined levels. She announced joint work with Canada and the UK on model evaluation, verification, early warning, and AI security, and proposed widening the CETA trade agreement into an alliance covering AI, quantum technology, and cyber and economic security. She defended the EU AI Act as central to guardrails, promised initiatives for health, transport, agrifood, manufacturing, and defense in November, and backed an EU Kids Act barring social media for children under 13.

Help Net Security · 6h agoAI policy

12 Best CASB Solutions Compared (2026): Features & Pricing

GBHackers' 2026 buyer's guide compares 12 CASB-capable vendors, arguing standalone CASB pricing has dissolved into per-user SSE subscriptions.

The article evaluates twelve CASB-capable platforms including Microsoft Defender for Cloud Apps, Palo Alto Networks' Prisma Access CASB, Netskope, iboss, Forcepoint ONE (Bitglass), Trend Micro Cloud App Security, and Skyhigh Security. It frames purchasing around SSE bundle economics, noting Defender for Cloud Apps ships inside Microsoft 365 E5 while Netskope, Zscaler, and Skyhigh price CASB into per-user SSE tiers. It also flags Saviynt, common on legacy roundups, as an IGA vendor rather than a true CASB.

GBHackersupdated · 7h agofirst · 10h agoIndustry 14 sources

ECHO: A Matched-Contrast Benchmark for Context-Sensitive Turn-Taking in Full-Duplex Dialogue

ECHO benchmark pairs identical-overlap Chinese dialogue examples with contrasting contexts, revealing most full-duplex systems bias toward yielding the floor.

ECHO is a paired diagnostic benchmark for Chinese full-duplex turn-taking that matches examples with identical overlap transcripts but contrasting preceding multi-turn contexts, one requiring Yield and the other Keep. It also includes off-talk examples for diagnosing unnecessary yielding and introduces pair accuracy, which grants no credit to constant-action policies. Experiments across multiple full-duplex systems show most exhibit a pronounced Yield bias, performing substantially better on interruptions than backchannels. The benchmark and metadata will be publicly released.

arXiv cs.AI / cs.LG / cs.CL · 1d agoAI research

After warning AI is too dangerous, Bill Gates bets a billion on its upside

Gates Foundation pledges at least $1 billion over two years to widen AI access in health, education and agriculture, warning of a rich-poor divide.

The Gates Foundation's 2026 Goalkeepers report outlines spending of at least $1 billion over two years on AI access in health, education and farming. Gates notes over 90% of early LLM training data was English, with speech recognition error rates below 6% in English but above 60% in Yoruba. Cited projects include Penda Health clinics in Kenya (16-point diagnostic accuracy gain), Gemini Guided Learning in Sierra Leone (1.7 years of learning gains in eight weeks), and India's MahaVISTAAR reaching 740,000+ farmers at under 18 cents per person.

The Decoder · 1d agoAI industry1

Homebrew 7.0.0 Adds Built-In Vulnerability Scanner and Stronger Package Sandboxing

Homebrew 7.0.0 ships a native brew vulns scanner, OSV-backed advisory database, stronger sandboxing, and fixes a sandbox-escape issue.

Homebrew 7.0.0 introduces a built-in 'brew vulns' command that scans installed formulae, dependencies, and Brewfiles against a new Homebrew-specific advisory database and OSV.dev data, distinguishing backported fixes from outdated versions. The release hardens sandboxing by blocking home-directory reads during builds, disabling network access at install time, and replacing Bubblewrap with Landlock on Linux. It also fixes moderate-severity GHSA-5263-whxq-77hp, where a malicious cask could execute code outside the macOS sandbox via LaunchServices, and drops macOS Catalina while moving Intel Macs to Tier 3.

Cyber Security News · 1d agoTools

New insights from Google’s AI & Economy ATLAS

Google launches an interactive AI & Economy ATLAS experience; new research shows nearly half of surveyed scientists use AI daily.

Google introduced new interactive, open-access data visualizations for its AI & Economy ATLAS project tracking global AI adoption patterns. Research from Google, Google DeepMind, and MIT FutureTech analyzed 2,600 specialized AI models and surveyed over 600 U.S. and U.K. scientists, finding nearly half use AI daily and report saving almost seven hours per week. The study also found validation bottlenecks and a growing backlog of untested hypotheses limiting research productivity gains.

Google · AI · 1d agoAI industry

Anatomical Grounding and Leakage-Aware Multimodal Contrastive Learning for Alzheimer's Disease Classification from Structural MRI

Study of label leakage and anatomical grounding in multimodal MRI models for Alzheimer's staging shows cognitive-score fusion accuracy of 87.3% is leakage-driven.

The authors train a ResNet18 slice-based encoder with a one-layer Transformer on 1,075 ADNI-1 T1 MRI scans, using FastSurfer segmentations and YOLOv8 localization (mAP_50 above 0.96) as anatomical reference. Grad-CAM shows the image-only classifier often attends to skull and background rather than disease-relevant structures. A CLIP-style image-tabular contrastive framework organized along a label-leakage spectrum yields 87.3% three-way accuracy with cognitive scores versus 73.0% with regional volumes, and cropping to the medial temporal lobe raises image-only accuracy from 58.7% to 65.1%. Results come from single runs on a small balanced test set with reported confidence intervals.

arXiv cs.AI / cs.LG / cs.CL · 2d agoAI research1

When the World Lies: Backdoor Attacks on Latent World Models for Downstream Control

A poisoned world-model checkpoint hijacks downstream controllers without an explicit trigger rule, passing clean-data evaluation while steering 100% of triggered actions.

Researchers show that a released pretrained world-model checkpoint acts as a supply-chain backdoor for downstream control. The poisoned model routes trigger-bearing observations into a chosen latent region and reshapes dynamics so the victim's own Dreamer-style actor training or MPC/CEM planning re-discovers attacker-targeted actions. The attack hijacks 100% of triggered steps in the strongest settings while retaining roughly 75% clean-task success and passing standard clean-data diagnostics. Moderate clean fine-tuning fails to remove the backdoor without substantially degrading clean control.

arXiv cs.CR · 2d agoAI safety & security

Approval Integrity and Recovery in LLM Answer Publication

Study measures approval integrity in Lightcap LLM answer publication, finding the 14B response-act checker accepts 291 of 302 unsupported answers.

The study evaluates exact-content binding, authorization freshness, and checkpoint recovery in Lightcap's publication enforcement using 3,600 assessments over 900 human-annotated RAGTruth responses from three Ministral models. The production 14B response-act checker accepts 291 of 302 unsupported answers versus 41 for a direct-grounding baseline, with supported-answer retention of 95.2% versus 66.9%. A stateful recheck-recovery policy increases exact-match error by 9.23 percentage points relative to initial checkpoints, and controlled evidence-fingerprint changes expose asymmetric freshness enforcement between publication and recovery. A separate BIPIA prompt-injection experiment records zero target insertions among 266 valid editor outputs.

arXiv cs.CR · 2d agoAI safety & security

Hierarchical NeRF with JAX3D for Volumetric Rendering, Novel-View Synthesis, and 3D Reconstruction

MarkTechPost tutorial implements a hierarchical NeRF in JAX using jax3d volume-rendering primitives for novel-view synthesis and 3D reconstruction.

The tutorial builds an end-to-end hierarchical Neural Radiance Field using JAX, Flax, Optax, and jax3d's volume-rendering functions (sample_along_rays, volume_rendering, sample_piecewise_constant_pdf). It implements positional encoding, skip connections, separate coarse and fine networks, and view-direction conditioning with hierarchical importance sampling. Training uses JAX JIT compilation, Adam optimization, exponential learning-rate decay, and gradient clipping. Evaluation covers PSNR, depth and opacity visualization, 360-degree rendering, and marching-cubes geometry extraction.

MarkTechPost · 2d agoAI research

ZGCM-1: A Fully Open and Extremely Efficient Foundation Model for Math and Agentic Search

ZGCM-1 is a fully open 7B foundation model with 256K context that stays competitive with frontier models on math reasoning and agentic search.

ZGCM-1 is a fully open 7B dense foundation model trained from scratch using an efficiency-focused recipe: interleaved gated sliding-window and full attention, a stable FP8 Muon optimizer, and MDP-based mid-training with context scaling across 16K, 64K, and 256K. On mathematical reasoning and agentic search suites it remains competitive with much larger frontier models such as Qwen3-235B-A22B and GLM-5.1. The recipe yields a ~4.2x improvement in 16K pre-training time-to-loss, and all weights, checkpoints, training code, data recipes, and W&B logs are open-sourced.

Hugging Face daily papers · 5d agoModel release

From Parameters to Answers: How LLMs Retrieve and Use Their Internal Knowledge

Interpretability study traces how Qwen, Llama, and Gemma route query information and internal knowledge across layers when answering questions.

Researchers used layerwise interventions on hidden states to separate query-routing signals from target knowledge in language models, testing Qwen, Llama, and Gemma on country-continent questions with varied answer types. A pair-conditioned request direction strengthens before interventions alter downstream knowledge, opening a causal window while answer-supporting content is still forming. Trajectories differ by model: Gemma shows a partially overlapping mid-layer routing profile, while Llama has no sustained routing-effect window under the same gates.

arXiv cs.AI / cs.LG / cs.CL · 6d agoAI research1

Model-Aware Schedules Improve Generation via Fiberwise Optimal Transport

Researchers introduce model-aware diffusion schedules via fiberwise optimal transport, cutting flow-matching FID on CIFAR-10 by 38.6% at 16 function evaluations.

The paper proposes constructing diffusion and flow-matching sampling schedules from a fiberwise prediction risk defined via optimal transport, combined with coefficient-path kinetic action, yielding a closed-form time allocation. Across DDPM and flow-matching experiments spanning targets, datasets, and architectures, the schedules beat model-agnostic baselines, including a 38.6% relative FID reduction for flow matching on CIFAR-10 at 16 function evaluations. Normalized fiberwise-risk profiles from independently trained models align closely, suggesting empirical universality, and a frozen analytic allocation template retains most of the gains.

arXiv cs.AI / cs.LG / cs.CL · 6d agoAI research

Target leakage, not model class, explains reported accuracy in survey-based cardiovascular screening: a leakage-tiered audit of glass-box and tabular foundation models

Audits of 10 classifiers on BRFSS show target leakage, not model class, drives the reported 0.89 AUROC in survey-based cardiovascular screening.

The study benchmarks ten model classes, including glass-box and tabular foundation models, for prevalent myocardial infarction on 442,067 respondents of the 2022 BRFSS across five feature tiers of decreasing leakage risk. Removing two post-diagnostic features costs every model 0.049-0.051 AUROC and collapses performance into a 0.0045-wide band, and the explainable boosting machine matches all alternatives within 0.005 while scoring roughly 104x faster than the strongest foundation model. Frozen models transport within 0.002 AUROC to 2023 data; the authors conclude evaluation practice and feature sets, not model capacity, are the binding constraint.

arXiv cs.AI / cs.LG / cs.CL · 6d agoAI research1

The Top 4 Threats We Found by Investigating Every Alert for a Quarter

Prophet Security's quarterly threat report finds identity attacks made up roughly half of confirmed malicious activity, with stolen authenticated sessions bypassing conditional access controls.

Between May 1 and July 31, 2026, Prophet Security investigated every alert in customer environments immediately on arrival; about 7% of completed investigations were confirmed malicious. Direct account/session attacks made up roughly 18% of confirmed activity, with replayed authenticated sessions bypassing conditional access since no re-authentication occurs. Infostealer activity affected about a quarter of investigated organizations, mostly delivered via browsers through compromised websites, malicious ads, sponsored search results and ClickFix fake CAPTCHA gates, with payloads including Lumma Stealer, Vidar, HijackLoader and AsyncRAT. Credential phishing was the largest category at about 28%, with adversary-in-the-middle relays revealed by seconds-long MFA approvals from distant countries and MFA fatigue attacks exploiting automatic unlock policies.

BleepingComputer · 6d agoThreat actor in the wild

The 12 Best Mobile Device Management (MDM) Solutions, Compared and Priced

A comparison of 12 MDM platforms ranks Microsoft Intune as best value for Microsoft 365 estates and Jamf, Kandji, and Mosyle for Apple fleets.

The buyer's guide compares 12 mobile device management (MDM) products, naming Microsoft Intune best value since it is included in Microsoft 365 E3/E5, and Jamf, Kandji, and Mosyle as Apple specialists with day-one OS support and automated compliance remediation. Eight of the twelve publish rates; per-device pricing punishes multi-device users, while Microsoft, Omnissa, and IBM offer per-user options. Free tiers from Mosyle, Miradore, and ManageEngine support genuine small deployments.

GBHackersupdated · 6d agofirst · 6d agoIndustry 4 sources

OmniMed-FL: A Robust Multimodal Federated Learning Framework for Clinical Diagnosis

OmniMed-FL benchmarks multimodal federated learning for chest radiograph diagnosis across 3-20 clients, with FedProx leading under severe non-IID skew.

OmniMed-FL studies multimodal federated learning combining chest radiographs and clinical notes for five-class condition classification under HIPAA/GDDR-compliant decentralized training. It benchmarks eight fusion strategies, imputation rules, and federated baselines under Dirichlet non-IID partitioning across 3-20 hospital clients. With 5 clients and severe skew (alpha=0.1), FedProx scored 0.737 macro-F1 versus 0.662 for FedAvg and 0.297 for local-only training. Multimodal fusion beat unimodal inputs (0.956 vs 0.934 text, 0.664 images) on the synthetic corpus.

arXiv cs.AI / cs.LG / cs.CL · 7d agoAI research1

Top 10 Best Unified Endpoint Management (UEM) Solutions in 2026

A 2026 buyer's guide ranks UEM platforms, recommending Intune for Microsoft 365 shops, Jamf for Apple estates, and SOTI for rugged devices.

The guide ranks ten unified endpoint management platforms for 2026, recommending Microsoft Intune for Microsoft 365 organizations, Jamf for Apple-heavy estates, and SOTI for rugged, kiosk, and industrial devices. It notes VMware Workspace ONE now operates as Omnissa after Broadcom divested the End-User Computing division, and that BlackBerry sold Cylance to Arctic Wolf in February 2025 while retaining BlackBerry UEM. The article provides a coverage checklist spanning Windows, macOS, iOS, Android, Linux, kiosks, legacy on-prem Windows, and wearables/IoT.

Cyber Security News · 7d agoIndustry

August updates trigger 0xc0000409 errors on Windows Server 2016

Microsoft says the August 2026 security update causes recurring CompatTelRunner.exe 0xc0000409 crashes on Windows Server 2016 with Compatibility Appraiser enabled; no functional impact.

Microsoft confirmed a known issue in which the August 2026 Windows security update generates recurring Application Error events (Event ID 1000, exception code 0xc0000409) in CompatTelRunner.exe on Windows Server 2016. The issue affects physical and virtual machines, including VMware and Azure environments, and per Microsoft does not affect device functionality. A permanent fix is planned for a future update, and the event log entries can be dismissed temporarily.

BleepingComputer · 8d agoAdvisory

ResidualAuth: What Authorization State Must Language Agents Preserve under Revocable Delegation?

Formalizes residual authorization state language agents must preserve under revocable delegation; token-budget summaries mostly fail while hard gates stop unauthorized effects.

The paper shows two authorization histories with identical current permissions can require opposite decisions after the same direct-edge revocation, formalizing the needed information as residual authorization state. Exponentially many future-distinct states can share one transitive closure, with exact or tight asymptotic bounds on the state an exact monitor requires. Across four open-weight models, fixed 256-token summaries solved at most 2 of 16 paired episodes while authenticated current-query reads solved 15-16 of 16. A hard effect gate reduced eight observed unauthorized effects to zero without changing preceding attempts.

arXiv cs.CR · 8d agoResearch