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From Specs to Apps: Verifying and Monitoring Models of Signal and WhatsApp

Researchers use the SpecMon runtime monitor to verify WhatsApp Web and Signal Desktop against formal Signal protocol models, finding undocumented libsignal fork differences.

The paper applies SpecMon, a runtime monitoring tool, to check whether executions of WhatsApp Web and Signal Desktop conform to formal models of the Signal protocol. The authors instrument both applications and build Tamarin-compatible multiset-rewrite models, including the first model of WhatsApp Web's implementation and the most detailed model to date of Signal's original protocol. They verify authentication and secrecy properties for core Signal protocol components, show monitoring detects deliberately injected faults with low overhead, and identify previously undocumented behavioral differences between the original libsignal library and WhatsApp's fork.

arXiv cs.CR · 5d agoResearch

Do AI Coding Assistants Check Before They Install? A Pre-Registered Demand-Side Audit of Trust Signals in the Research Software Supply Chain

Pre-registered audit finds AI coding assistants verified provenance signals in only 9 of 1,920 trials before installing research software packages.

The study tested whether AI coding assistants check machine-readable trust signals such as SBOMs, signed releases, and provenance attestations before installing six open-source research software projects spanning HPC and quantum computing. Three models under two operating modes produced 1,920 registered trials scored from container logs. Provenance signals were opened in only 9 of 1,920 trials (0.5%) and zero of 384 control trials, with no trial running a verification command. The authors conclude publishing signals is insufficient and verification must be built into the program running the assistant.

arXiv cs.AI / cs.LG / cs.CL · 8d agoAI safety & security

A Deep Generative Model for Synthesizing Labeled Wireless Signals

Researchers propose IIns-GAN, a GAN that synthesizes realistic labeled ultra-wideband wireless signals, cutting dataset costs for wireless sensing training.

The paper introduces Inter-Instance Generative Adversarial Networks (IIns-GAN), a deep generative method that synthesizes realistic wireless signals with position-related labels to avoid costly real-world measurement and labeling. Unlike environment-model-based synthesis, the generated signals adapt to different environment scenarios and support training tasks such as distance estimation and environment identification. Experiments on public Ultra-Wideband (UWB) datasets show the synthetic signals closely mirror real measurements and improve model training performance.

arXiv cs.AI / cs.LG / cs.CL · 11d agoAI research

Top 10 Best Patch Management Software in 2026

Roundup ranks 2026 patch management software, favoring Automox, Action1's free tier and Tanium, and warns buyers to vet patching platform security.

This buyer's guide ranks ten patch management tools for 2026, placing Automox first for cloud-native patching, Action1 for a genuinely free small-estate tier and Tanium for patching hundreds of thousands of endpoints. It contextualizes the category with the 2021 Kaseya VSA ransomware supply-chain incident and the 2020 SolarWinds Orion compromise, arguing the security of the patching platform itself must be part of evaluation. It also notes Ivanti products have repeatedly appeared in CISA's Known Exploited Vulnerabilities catalog.

Cyber Security News · 7d agoIndustry

Imagine the SOC Without a Queue: From Alert Backlog to AI Hypothesis Engine

Corelight argues agentic AI should replace SOC alert queues with hypothesis-driven, machine-run investigations, reserving humans for judgment.

A Corelight opinion piece argues traditional SOC alert queues guarantee most alerts go unreviewed because human analysts are the investigative bottleneck. It proposes agentic AI that investigates signals within seconds, tests hypotheses against network telemetry asynchronously, and escalates only evidence-backed cases to humans. The vendor claims this inversion lowers cost per investigation, expands coverage, and converts security telemetry into actionable evidence.

The Hacker News · 21d agoIndustry

Train Smarter, Not Harder: Switching Signal-Guided Training in Active Learning

HybridAL is an active-learning training schedule that switches from retraining to fine-tuning on stabilization signals, saving up to 49% time.

Researchers find that choosing between retraining from scratch and fine-tuning is an exploitable decision variable in active learning: retraining helps in early rounds while fine-tuning is safer once the model trajectory stabilizes. HybridAL monitors an online stabilization signal using spectral exponent change and accuracy change, switching from retraining to fine-tuning after sustained stabilization. Across three encoder backbones and six text-classification tasks with five seeds each, HybridAL keeps endpoint macro-F1 non-inferior within a 0.010 margin, saves up to 49% of retraining time, and improves the time-calibration trade-off measured by negative log-likelihood.

Hugging Face daily papers · 10d agoAI research

ImpossibleRubrics: Stress-Testing Generated Rubrics as Reward Signals

ImpossibleRubrics benchmark shows LLM-generated rubric reward signals are exploited 8-26% of the time by adversarial answers on impossible tasks.

ImpossibleRubrics is a benchmark of 169 impossible tasks across six impossibility categories, each paired with a verifiable oracle certificate, plus 48 answerable controls, for stress-testing LLM-generated rubrics used as reward signals. Eleven rubric generators were exploited 8-26% of the time on an unbiased 150-task cut and up to 36% on a stress cut, while a certificate-faithful rubric scored 0%. A single generic 'be decisive, penalize hedging' rubric was exploited 64% of the time, suggesting tailored criteria can reveal which claims attackers should fabricate.

Hugging Face daily papers · 1d agoAI research

Banks look for fraud signals in customer behavior

ThreatMark's 2026 benchmark finds 55% of banks see social engineering in most fraud, pushing behavioral intelligence and earlier detection during customer sessions.

ThreatMark's Fraud Readiness Benchmark 2026 reports social engineering is involved in most fraud at 55% of surveyed banks, with criminals impersonating trusted people to make customers authorize payments using legitimate credentials. The report highlights behavioral intelligence as underused (18% adoption, 83% rating it effective), expects authorized push payment reimbursement regulation in North America within two years, and notes 91% agreement that AI can shorten fraud investigations. It also finds 81% of fraud professionals now carry cybersecurity responsibilities.

Help Net Security · 28d agoPhishing & fraud

First Galileo SAS Authenticated Time Solution

Researchers demonstrate the first timing solution computed from Galileo's new Signal Authentication Service, protecting receivers against GNSS spoofing.

Galileo's new Signal Authentication Service (SAS) on the E6-C signal directly authenticates ranging measurements, closing a gap left by OSNMA, which only protects navigation data. Researchers built a snapshot software receiver implementing a simplified SAS protocol and computed an authenticated receiver clock bias from recordings of both SAS-capable satellites, collected with a Septentrio SDR prototype. The results demonstrate feasible authenticated timing ahead of full SAS operational deployment.

arXiv cs.CR · 1d agoResearch

Cognition hits $48B valuation, signaling investors believe AI coding is far from a winner-take-all market

Cognition, maker of Devin, raised $2 billion at a $48 billion valuation led by a16z, Accel, and Founders Fund, with revenue at $900M annualized.

Cognition raised $2 billion at a $48 billion valuation, four months after a $26 billion round, led by Andreessen Horowitz, Accel, Founders Fund, General Catalyst, and Avenir. Its annualized run-rate revenue grew from $492 million to $900 million since May, with projected $4-5 billion by end of 2026, while compute costs could push 2026 burn to $800 million. The startup, founded by Scott Wu, counts Mercedes-Benz, NASA, Goldman Sachs, and Citi as customers and is training its own model to cut reliance on OpenAI and Anthropic.

TechCrunch · AI · 7d agoAI industry

Can your coding style predict whether your code is vulnerable?

University of Massachusetts Dartmouth researchers present VulStyle, a stylometry-based vulnerability detector that also exposes benchmark reliability problems.

VulStyle combines stylometric features with syntax-tree structure and source tokens, pre-trained on about 4.9 million functions across seven programming languages and fine-tuned on five vulnerability detection datasets. It beat token-only detectors on some benchmarks but its F1 drops sharply on DiverseVul, which the authors link to noisy labels inflating reported performance across popular datasets. The authors argue style-aware detection should be harder to evade but did not test this empirically, and they note that uniform LLM-generated code may strip away the individual developer style the model depends on.

Help Net Security · 23d agoResearch1

AI Infra Summit: NVIDIA Vera Rubin and DSX Platform Advancements Showcase Energy Efficiencies of Optimizing Tokens Per Watt for AI Factories

At AI Infra Summit, NVIDIA showcased Vera Rubin and DSX gains up to 1.4x tokens per megawatt, plus Annapurna, d-Matrix, and Pinterest partnerships.

Ian Buck's AI Infra Summit keynote before 8,000+ attendees emphasized validated agentic tokens per megawatt as the emerging AI infrastructure metric. Announcements include Amazon's Annapurna Labs collaborating on NVHBM custom high-bandwidth memory, d-Matrix integrating NVLink Fusion with Raptor XPUs, and Pinterest using Blackwell plus Dynamo inference software for conversational visual discovery. Lambda reported 23% better performance per watt with DSX MaxLPS on Blackwell servers, running 19 nodes on a 16-node power budget. NVIDIA says DSX MaxLPS combined with Groq 3 LPX on Vera Rubin NVL72 targets up to 35X token throughput per megawatt versus GB200 NVL72 for 2-trillion-plus-parameter models.

NVIDIA Blog · 21h agoAI industry

What is Proactive Threat Intelligence? | Recorded Future

Recorded Future publishes a vendor explainer on proactive threat intelligence, arguing external adversary context helps teams act before alerts fire.

Recorded Future published a conceptual blog on proactive threat intelligence, describing how external context on adversaries, infrastructure, stolen credentials, and vulnerability exploitation helps security teams act before intrusions surface internally. The piece outlines a four-step program: defining intelligence requirements, collecting external sources including OSINT and dark web, analyzing relevance to the organization, and driving security actions. Use cases include prioritizing CVEs by real-world exploitation activity and identifying external exposure before it becomes an internal incident.

Recorded Future · 2d agoIndustry

Cross-Model Agreement as a Deployment-Time Reliability Signal for Automatic Polyp Segmentation

Referee-Based Quality Estimation flags unreliable polyp segmentations at inference without ground truth, reaching ROC-AUC 0.960 with SegFormer-B0 referees.

RBQE measures agreement between a primary segmentation model and an independently trained referee on a 1,223-image external benchmark drawn from four public datasets. A cross-architecture SegFormer-B0 referee achieves the strongest signal (ROC-AUC 0.960), beating a Test-Time Augmentation baseline by 0.055 ROC-AUC under an identical protocol. Excluding trivially separable empty-mask cases, ROC-AUC falls to 0.876 (SegFormer-B0) and 0.783 (same-architecture control), but RBQE's margin over baselines widens. Progressive rejection of low-agreement predictions increases mean Dice of retained outputs, supporting selective prediction at the cost of one extra forward pass.

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

Introducing the CyberAgents Exchange AI Inspector: Rigorous review for community-built AI

Tenable and OpenAI launch the CyberAgents Exchange AI Inspector to security-review community-submitted AI agents, MCP servers, and skills using GPT Cyber models.

Tenable and OpenAI announced the CyberAgents Exchange AI Inspector, unveiled at OpenAI's "Intelligence at Work: Cyber Summit," to vet community-submitted AI agents, skills, MCP servers, and multi-agent playbooks in the CyberAgents Exchange registry. The process combines Tenable One AI Exposure scanning, OpenAI GPT Cyber model assessment, and human review, with reviews anchored to specific Git commits. The registry launched in August and hosts over 100 AI listings; the Inspector is expected to be available in September and has already detected prompt injection implemented via invisible Unicode tag characters in a SKILL.md file.

Tenable Blog · 7d agoTools

Proofpoint SOC Analyst Agent Uses OpenAI Cyber Models

Proofpoint launched its SOC Analyst Agent in private preview, using OpenAI Daybreak models to automate security investigations with human-controlled remediation, GA expected end of Q3 2026.

The SOC Analyst Agent uses OpenAI Daybreak cyber models to enable natural-language investigations across Proofpoint alerts, logs, DLP events and user risk signals, and to automate recurring threat hunts, data security investigations and escalation reporting. It is currently in private preview with general availability expected by the end of Q3 2026, and it does not independently make account changes or take remediation actions. Proofpoint joined the OpenAI Daybreak Defense Network in June 2026 and is exploring additional uses for the models in threat research, data security and AI security workflows.

Proofpoint Threat Insight · 7d agoTools

Why 2026 is the Year to Upgrade to an Agentic AI SOC

Elastic Security Labs argues 2026 is the production inflection point for agentic AI in security operations centers.

Elastic Security Labs argues 2026 is the practical inflection point for agentic AI SOCs, noting nearly two-thirds of organizations are experimenting with AI agents while fewer than one in four have production deployments. The piece outlines operational challenges and recommendations: treat agents as non-human identities with least-privilege tool access, version-control system prompts as code, deploy unified agents with on-demand task packages, and enforce per-agent budgets and rate limits. It stresses explainability via RAG and transparent reasoning traces so analysts can verify and override autonomous decisions.

Elastic Security Labs · 7d agoIndustry

Pre-Whitening and BCJR Posterior Distillation for Bi-LSTM Detection in Faster-than-Nyquist Signaling

Study shows nested-window Bi-LSTM architectures do not improve faster-than-Nyquist detection; pre-whitening plus BCJR distillation cuts bit error rates.

Across roughly 260 controlled trainings, processing nested intersymbol-interference windows in separate recurrent branches never significantly beat a plain Bi-LSTM at matched parameter budgets. The authors attribute the limitation to the observation model rather than architecture, and instead pre-whiten inputs and distill BCJR soft posteriors into the network. With 3.4% more parameters, the method reaches 1.05x the BCJR bit error rate at compression factor 0.8 and 1.89x at 0.7, improving to 1.47x with a wider whitened window.

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

Proofpoint Brings OpenAI GPT Cyber Models into Security Operations to Help Defenders Investigate Threats Faster

Proofpoint launched its SOC Analyst Agent, an agentic investigation tool powered by OpenAI Daybreak models, now in private preview with Q3 GA planned.

Proofpoint introduced the SOC Analyst Agent, the first capability to emerge from its membership in the OpenAI Daybreak Defense Network, which it joined in June 2026. The agent converts natural-language questions into structured, traceable investigation findings across Proofpoint alerts, logs, DLP events and user risk signals, while leaving remediation decisions to human analysts. It is in private preview with select beta customers, and general availability is expected by the end of Q3 2026. Proofpoint cites its 2025 report finding that 54% of organizations already use AI-enhanced capabilities to triage and investigate alerts.

Proofpoint Threat Insight · 13d agoAI industry

The Money Mule Solution: What Every Scam Has in Common

CYBERA's money mule intelligence, now in Recorded Future's Payment Fraud Intelligence, targets the shared exit point of $450B-$1T annual scam losses.

Scams, especially authorized push payment fraud, do not require a breach; Global Anti-Scam Alliance estimated ~$450B in 2025 losses while CYBERA co-founder Claudio Staub puts the real figure near $1 trillion when underreporting is counted. Every scam needs a mule account to receive funds, so CYBERA uses agentic personas to engage active scammers and extract verified mule account details before payments occur, now available as an add-on to Recorded Future's Payment Fraud Intelligence. CYBERA collected over 16,000 confirmed mule accounts across 72 countries in H2 2025, finding 28% remained active 30 days or more after identification, including one account in 25 engagements. In Europe 51% of mule accounts sat at neobanks and fintechs, while outside Europe 69% were at major banks; regulatory pressure like the UK's APP reimbursement mandate is raising the stakes for institutions.

Recorded Future · 17d agoPhishing & fraud

From Megawatts to Tokens: How NVIDIA Maximizes AI Factory Production

NVIDIA detailed DSX power-management results: Lambda gained 24% token throughput at fixed power, and an AI factory auto-shed 1MW via Emerald AI's grid program.

NVIDIA says Lambda's first validation of DSX MaxLPS on HGX B200 servers ran 19 nodes within a 16-node power budget, lifting cluster token throughput 24% (roughly 4M to 5M tokens/second) and improving performance per watt by 23%. NVIDIA projects DSX MaxLPS can enable up to 40% more GPU capacity for Vera Rubin NVL72 factories within the same megawatt budget. Emerald AI's Conductor platform, running at NVIDIA's Eos factory with Silicon Valley Power, responded to over 200 utility demand signals, automatically dropping power from 4MW to 3MW without interrupting priority workloads. The first dedicated DSX Flex commercial deployment is planned at a 96-megawatt Manassas, Virginia facility.

NVIDIA Blog · 21h agoAI industry

The Price of Sparsity: Sufficient Conditions for Sparse Recovery using Sparse and Sparsified Measurements

Researchers derive sufficient sample-size conditions for recovering sparse binary signals from sparse Gaussian measurements, quantifying an information-theoretic threshold of order slog(p/s)/log(ds/p).

The paper studies support recovery of sparse binary signals from noisy linear measurements. For sparse Gaussian designs, the authors identify sufficient minimal sample sizes for maximum-likelihood recovery in the high-SNR regime d*s/p -> infinity, yielding an information-theoretic threshold of order slog(p/s)/log(ds/p) that makes the price of measurement sparsity explicit. They also show a regime where the sample-complexity loss from sparsity is only logarithmic while computational gains are nearly linear, and prove that for independently sparsified dense Gaussian designs a sample size of order p/ψ² suffices for support recovery at any fixed error level.

Hugging Face daily papers · 8d agoAI research

ASCII smuggling crosses over from AI prompt injection to phishing evasion

Microsoft details high-volume phishing campaign using ASCII smuggling (Unicode tag chars) for filter evasion, peaking at 2.3M messages.

Microsoft researchers observed a high-volume finance-themed phishing campaign using invisible Unicode tag characters (U+E0000–U+E007F), a technique known from AI prompt injection research as ASCII smuggling, to split lure words like 'funding' and evade email filters. Telemetry from Microsoft Defender for Office 365 showed signature hits jump from roughly 21,000 messages on February 8, 2026 to more than 1.3 million on February 9, peaking above 2.3 million on February 11, with elevated weekday activity lasting approximately three months. The discovery emerged from prompt injection protection research, showing AI-era evasion techniques crossing into traditional phishing. Most messages were flagged by layered Defender protections rather than a single Unicode-specific signal.

Microsoft Security Blog · 12d agoPhishing & fraud in the wild

Exclusive: NSA to host a hacker reunion in bid to rebuild secretive unit

NSA will host a reunion of former Tailored Access Operations hackers as it moves to rebuild and rebrand the elite unit.

The invitation-only event at Fort Meade, spearheaded by Deputy Director Tim Kosiba, a former TAO technical director, will tour the new TAO building and pitch alumni to return. TAO, credited with contributions to Stuxnet and once grown to over 2,000 personnel, was renamed Computer Network Operations about a decade ago, and the recent reshuffle undid some of those changes after NSA lost roughly 2,100 staff (8% of its workforce) last year.

The Record · 20d agoIndustry

ThreatsDay: GhostJacking AI Attacks, EtherHiding ClickFix, Cursor CLI Flaw + 17 More Stories

A weekly bulletin aggregating short security updates, including the City-Forum data-theft campaign, a ShipMonk breach, a Cursor CLI flaw, and GhostJacking AI attacks.

The Hacker News ThreatsDay Bulletin bundles roughly 20 short updates across cloud services, AI tools, malware, breaches, and scams. Highlights include the City-Forum campaign pulling data from unauthenticated guest access in Salesforce Experience Cloud and ServiceNow Service Portals since March 2025, and a ShipMonk breach exposing Trezor customer order data for orders in seven countries between May 10 and August 8, 2026. Other items cover a patched Cursor CLI flaw that let cloned repositories run commands before the workspace-trust prompt, Okta's analysis of the Work Panel vishing console used by actors like UNC6671, and GhostJacking AI agent hijacking via a patched Claude Desktop sandbox escape. Meta also launched an on-device WhatsApp Scam Alert machine learning model that keeps message content on the device.

The Hacker News · 28d agoIndustry

New Report: AI threats are here. Why Q2 2026 signals the end of traditional patch cycles

Rapid7 Labs' Q2 2026 threat report finds vulnerability disclosures surging while AI-assisted attackers compress the time from disclosure to exploitation.

Rapid7 Labs' Quarterly Threat Landscape Report for Q2 2026 reports continued growth in vulnerability disclosures alongside attacker use of automation and AI-assisted tooling. The report argues the window between disclosure and exploitation is shrinking, eroding the value of traditional patch cycles. It recommends prioritizing exposures attackers can actually reach rather than attempting to patch everything.

Rapid7 Blog · 29d agoResearch

Threat Intelligence Alone Won't Close the Exploitation Gap

Pentera argues threat intelligence alone leaves a validation gap, promoting threat-led penetration testing that auto-tests leaked credentials against real attack surfaces.

A contributed Pentera piece argues that threat intelligence signals such as leaked credentials and vulnerability advisories often sit unactioned in queues because teams lack the offensive capacity to validate them against live environments. It promotes threat-led penetration testing (TLPT) and highlights Pentera's integration with Recorded Future, which triggers automated validation of leaked credentials against an organization's external attack surface. Wyndham Hotels & Resorts cybersecurity VP Joseph Gothelf is quoted supporting the convergence of threat intelligence and security validation.

The Hacker News · 2h agoIndustry

Australia is replacing the Essential Eight with a new cyber framework. Here’s how exposure management can help you get ahead of it.

Australia's ASD is replacing the Essential Eight with an outcomes-based Essentials series covering IT, cloud, OT and likely agentic AI, with deprecation from mid-2027.

The Australian Signals Directorate announced in June 2026 that the Essential Eight will be replaced by an outcomes-focused Essentials series structured as chapters covering enterprise IT (including identity and SaaS), cloud, OT, and likely agentic AI. Deprecation begins around mid-2027 with full retirement around mid-2028, though timelines are targets; the Essential Eight is mandatory for roughly 98 non-corporate Commonwealth entities but voluntary for private firms. Tenable argues the shift demands continuous security posture evidence via exposure management rather than point-in-time checklist assessments.

Tenable Blog · 1d agoPolicy & legal1

PhysStream: Streaming Physics-Grounded Video Generation with Structured Scene Memory and Fine-Grained Motion Control

PhysStream enables mid-generation interactive control of physics-grounded video via structured scene memory and velocity-increment signals, reducing motion distribution distance 33%.

PhysStream is an autoregressive physics-grounded image-to-video model that maintains structured scene memory—positional maps and object tracking maps derived online from previously generated frames—and accepts fine-grained motion control via sparse velocity-increment signals encoding physical quantities. Training runs in two stages: a bidirectional model finetuned with motion-control conditioning, then a causal autoregressive model with structured scene memory. It supports interactive mid-generation control over multi-object tabletop rigid-body scenes, reducing motion distribution distance (FVMD) by 33% and trajectory error by 12% over the strongest baselines. Human evaluators preferred it in over 85% of in-the-wild comparisons.

Hugging Face daily papersupdated · 20h agofirst · 1d agoAI research 2 sources

Evaluating Time-Series Foundation Models and Multimodal Dietary Context for CGM Forecasting

Study finds zero-shot time-series foundation models underperform on CGM forecasting; fine-tuned Chronos-Bolt cuts RMSE up to 18.4% and dietary context adds signal.

The paper evaluates time-series foundation models for continuous glucose monitoring forecasting across eight public datasets covering Type 1 diabetes, Type 2 diabetes, and non-diabetes populations. Under a unified protocol, zero-shot foundation models did not consistently outperform baselines like Elastic Net and PatchTST, but lightweight fine-tuning did, with fine-tuned Chronos-Bolt reducing RMSE by 6.5%-18.4% in the T1D cohort and 8.6%-18.2% in the non-diabetes/T2D cohort. A residual-based fusion framework adding dietary context from CGMacros reduced overall RMSE by about 3% and postprandial RMSE by about 15% versus CGM-only baselines.

arXiv cs.AI / cs.LG / cs.CL · 5d agoAI research

AutoTrans: AI-Assisted Automatic Translation of Security Assertions for RISC-V Processors

AutoTrans uses LLMs with regex extraction and formal verification to automatically translate security assertions across RISC-V processors, achieving 78% unattended acceptance.

AutoTrans is an automated framework for translating verified security assertions between RISC-V processor targets, where manual translation takes hours per assertion. It combines a regex-based SystemVerilog signal extractor to prevent LLM signal hallucination, a pinned prompt template yielding byte-identical prompts resilient to model updates, and JasperGold FPV formal verification of generated assertions. Applied with DeepSeek V4 to translate assertions between RISC-V targets such as IBEX and NS31A, it achieves a 78% automatic translation acceptance rate without human intervention and 100% after human refinement.

arXiv cs.CR · 7d agoResearch

What breach and attack simulation needs to become in the AI era

Picus argues calendar-driven BAS is obsolete as AI compresses exploit timelines, citing 338 million simulations showing 69% prevention and a flat 14% alert score.

In a vendor opinion piece, Picus Security contends that with over 130 CVEs disclosed daily, fewer than 0.5% patched upstream, and disclosure-to-weaponized-exploit timelines near 10 hours, scheduled breach and attack simulation no longer keeps pace. The Picus Blue Report 2026, aggregating 338 million production simulations, found average prevention effectiveness of 69%, 58% of attack actions captured in the SIEM, an unchanged 14% alert score, and detection rule failures driven by performance issues (49%) and silent log collection gaps (41%). Picus proposes agentic BAS as a closed loop—simulate, validate, fix, verify—with AI-built threats and humans at decision gates.

Help Net Security · 7d agoIndustry

Claude Mythos 5 is coming to Tenable One, powering the new “Adversary View”

Tenable will integrate Anthropic's Claude Mythos 5 into Tenable One, launching Adversary View to surface exploitable vulnerability chains from scan data.

Tenable announced it is bringing Anthropic's Claude Mythos 5 into the Tenable One Exposure Management Platform, extending its Project Glasswing research work with Anthropic. The first capability, Tenable One Adversary View, will use the model's adversarial reasoning over raw scanner evidence, plugin output, live connections and low-confidence signals to identify viable vulnerability chains and ranked defensive actions. Customers will act on results through Tenable Hexa AI. Availability details for Adversary View are expected in the coming weeks; no customer deployment exists yet.

Tenable Blog · 7d agoTools1

WearableQA: A Benchmark for Health Reasoning over Real-World Wearable Data

WearableQA benchmark tests LLM health reasoning over longitudinal wearable data; the best of 14 evaluated LLMs reaches 72.9% accuracy.

WearableQA comprises 4,084 ten-option multiple-choice questions built from wearable time series, blood biomarkers, and demographics of 200 real users with up to 500 days of daily measurements. It defines 16 question types along two axes: data versus health reasoning, and single- versus cross-signal reasoning. Evaluation of 14 proprietary and open-source LLMs shows performance from 19.6% to 72.9% against a 10% chance baseline, with most models below 60%.

arXiv cs.AI / cs.LG / cs.CL · 11d agoAI research

Instagram’s AI detection is a mess (again)

Instagram is mislabeling ordinary edited photos as AI Content while some AI imagery goes unlabeled, repeating a 2024 detection failure.

The Verge documents weeks of erroneous AI Content labels on Instagram, including images edited only with Canva's Background Remover or an iPhone Photos app, while some generative images escape tagging. Canva said some of its assistive AI tools were being tagged as generative and claims the issue is fixed, though users still report tagging. Meta scans IPTC and C2PA metadata and uses signals like Google's SynthID, but remains vague about detection criteria; one tester found only Meta AI-created or edited images reliably triggered labels, and an image-poisoned photo was tagged. A similar mislabeling wave hit Instagram in 2024.

The Verge · AI · 12d agoAI industry

WearableQA: A Benchmark for Health Reasoning over Real-World Wearable Data

WearableQA benchmark introduces 4,084 questions over real longitudinal wearable data, showing 14 LLMs score 19.6-72.9% on health reasoning, far from solved.

WearableQA is a benchmark of 4,084 10-option multiple-choice questions built from wearable time series, blood biomarkers, and demographics of 200 real users with up to 500 days of daily measurements. It defines 16 question types along two axes: data versus health reasoning, and single- versus cross-signal reasoning, using a dual-grounding framework combining literature and population-validated patterns. Evaluations of 14 proprietary and open-source LLMs show accuracy ranging from 19.6% to 72.9% against a 10% chance baseline, with most models below 60%.

Hugging Face daily papers · 12d agoAI research

The Coding-Agent Trap: When a "Free" LLM Endpoint Is the Adversary, (Mon, Aug 31st)

A SANS honeypot caught a real coding-agent session routed to a rogue "free" LLM endpoint, exposing a Windows user's transcript and tool outputs.

A SANS analyst describes how an internet-exposed inference honeypot was discovered, relabeled with sought-after model names like DeepSeek, and enrolled in infrastructure serving "free" LLM backends. On 2026-08-30 an opencode terminal coding agent sent an 88-message, 224 KB transcript 210 times in 91 seconds via a China Unicom relay, exposing directory listings, tool outputs and read file portions. The analyst frames tool-enabled agents treating model endpoints as trusted control planes as a novel risk — a "rogue model endpoint" that could request tool executions on the user's machine.

SANS Internet Storm Center · 15d agoAI safety & security1

Fideo Lens reveals connections across identities, accounts and devices

Fideo Intelligence launched Fideo Lens, an investigative platform mapping relationships across identities, accounts, devices and behaviors for fraud and AML teams.

Fideo Intelligence introduced Fideo Lens, an investigative intelligence platform that helps fraud, financial crime, and AML teams discover hidden relationships among identities, accounts, devices, and behaviors. The tool draws on the company's Identity Fraud Intelligence Network (iFIN) and offers interactive relationship mapping, entity resolution, explainable reason codes, and continuously refreshed data. It is designed to complement existing fraud, AML, and case management systems rather than replace them.

Help Net Security · 22d agoTools

Mapping out your unknown: A threat hunter’s guide to GitHub

Datadog Security Labs publishes a threat-hunting guide with audit-log queries to detect GitHub token theft, device code phishing, and source code exfiltration.

Datadog's threat-hunting guide covers GitHub audit log queries for detecting compromised accounts, stolen personal access tokens, and malicious OAuth app authorizations. Attackers typically obtain credentials through phishing, credential stuffing, leaked secrets, or device code phishing, then map private repositories, exfiltrate source code, and pivot into connected cloud and CI/CD environments. The guide maps detections to MITRE techniques like T1078 and T1528 and documents GitHub logging quirks affecting attribution, token metadata, and visibility fields.

Datadog Security Labs · 14h agoResearch in the wild

Phishing Attacks Abuse Trusted Email Infrastructure and URL Cloaking to Evade Security Filters

VBSpam Q3 2026 test shows phishers abusing DKIM-aligned domains, Amazon SES, and multi-stage URL cloaking to defeat email filters.

Virus Bulletin's Q3 2026 VBSpam test (AMTSO-LS1-TP207) found phishing campaigns moving payloads past the email itself via browser-fingerprinting gates, redirect chains, and hidden POST requests. Examples include a Dutch McAfee/TotalAV scareware renewal scam, a German overdue-payment Web3 fraud delivered via Amazon SES from DKIM-aligned moolaah.com, and Romanian BCR PSD2 credential phishing embedding IPv6-mapped URLs resolving to 103.193.179.223. Net at Work NoSpamProxy ranked first with a 99.995 score while open-source Rspamd caught only 62.55% of phishing mail.

GBHackers · 1d agoPhishing & fraud in the wild 2 sources