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19 stories in the last 24h

KREMLIN Banking Malware Infects Over 1,500 Systems With Malicious Chrome Extension

Elastic tracks KREMLIN banking malware that used fake Brazilian bank JavaScript lures to deploy malicious Chrome and Edge extensions on 1,515 systems.

Elastic researchers tracked the KREMLIN banking malware operation across seven campaigns over 15 months, infecting 1,515 systems, 98.75% of them in Brazil. Portuguese-language lures posing as bank records and invoices deploy a hostile 'AVSync' extension into Chrome and Edge profiles that harvests passwords, session cookies, keystrokes and screenshots. Loaders check for sandboxes, create scheduled tasks and fetch fresh infrastructure from an Ethereum smart contract; a network canary takeover temporarily disrupted infections.

Cyber Security News · 1h agoMalware in the wild

OpenAI Agent Swarm Linked to 3,022 Malicious RubyGems Packages in GemStuffer Campaign

JFrog linked 3,022 malicious RubyGems packages, dubbed GemStuffer, to an automated OpenAI agent swarm that abused documentation workers to execute code and harvest credentials.

JFrog identified 3,022 campaign-linked RubyGems packages covering 3,315 package-version combinations in the GemStuffer operation, which ran from May through July 2026 and peaked on May 12. Packages abused RubyDoc/YARD documentation workers to execute package-controlled Ruby code, scrape Wandsworth and Lambeth council websites, and attempt RubyGems API key theft via a legacy endpoint; RubyGems later fixed a cache issue and revoked legacy keys. Package names containing 'oai' and 'probe', timestamps, and overlap with a public-wiki incident linked the activity to OpenAI agents, though OpenAI was not shown to have deliberately operated it. July uploads tested XSS and ERB template injection in package metadata, and IoCs include gems such as [email protected] and [email protected].

Cyber Security News · 2h agoMalware in the wild 2 sources

1Password's AI patching benchmark is misleading

Trail of Bits reanalysis says 1Password's 26% AI clean-fix rate is misleading; 86% of eligible patches blocked exploits.

Trail of Bits critiques 1Password's FLAWED AI patching benchmark, arguing its 26% clean-fix headline mixes trials where agents were instructed to apply wrong fixes (22% of data) with trials that prohibited compiling or testing (36%). Restricting to reasonable conditions, 2,634 of 3,067 patches (86%) blocked the supplied exploit. Trail of Bits also reports 12.5% of 2,265 developer first fixes failed in its own 2024-2026 assessments, and released post-patch-validation and review-walkthrough agent skills.

Lobsters · security · 13h agoResearch

“We Think the Security Control Is Working” Is No Longer Good Enough

Opinion piece argues CISOs must replace point-in-time, sampling-based audits with continuous control monitoring to prove controls work in real time.

The article contends that annual, sampling-based compliance assessments no longer satisfy boards, customers, and regulators who demand live proof that security controls are working. It cites a 2025 Dell study where 69 percent of IT professionals said leadership overestimates cyber readiness, and notes NIST's 2024 CSF update added a Govern function emphasizing continuous, measurable outcomes. The author advocates continuous control monitoring of identity, cloud configuration drift, vulnerability remediation clocks, and vendor posture, feeding automated evidence into existing GRC systems.

SecurityWeek · 14h agoIndustry

Re: Retrospective by 'gpg.fail' authors

GnuPG's Werner Koch says gpg.fail samples only crash GnuPG via DER-as-printf format string in --debug x509; RCE claim remains unproven.

Werner Koch replied to the gpg.fail retrospective, noting that GnuPG versions above 2.2 produce garbled stderr or crash when the project's certificates are used with --debug x509 because DER data is passed as a printf format string. Testing the certificates from the researchers' Git repo yielded only a segfault, not demonstrated code execution. Koch states how remote code execution would be achieved is unclear and asks for a real reproducer.

oss-securityupdated · 4h agofirst · 18h agoVulnerability 6 sources

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 · 20h agoPhishing & fraud in the wild 2 sources

Hackers demand 10,000 Bitcoin from Revolut following data breach

Revolut breach via spoofed government-agency email requests; attackers posted stolen data samples on Telegram and demand 10,000 Bitcoin.

Revolut disclosed that an unauthorized third party obtained sensitive customer information by sending fraudulent requests from the email domain of a legitimate government agency. People claiming responsibility have posted samples of the allegedly stolen data across several Telegram groups. The perpetrators are demanding 10,000 Bitcoin from Revolut.

DataBreaches.net · 22h agoData breach

Jev: New frontier model 40-400x cheaper and 20-200x faster

TypeSafe AI launches Jev, an early-access 'System One' model delivering calibrated structured outputs claimed 40-400x faster and cheaper than LLMs.

TypeSafe AI, founded by former OpenAI researcher Diogo Almeida, released its first 'System One Model' called Jev in early access. Jev forgoes string generation and is trained with Reinforcement Learning for Calibrated Decisions (RLCD) to produce type-safe structured values with calibrated probabilities. The company claims 70-500ms response times (40-200x faster), input pricing of $0.042 per million tokens, and free output tokens via a parallel sampling architecture. Target use cases include AI-powered workflows, real-time applications, and verification/guardrail tasks.

Iranian Hackers Use Fake MRI Results to Infect Victims With CHOSEN BRICK Spyware

Iranian state-linked hackers deliver CHOSEN BRICK Windows spyware via fake MRI results to surveil dissidents, activists, and journalists in the UK, US, and Netherlands.

A joint advisory from the UK NCSC, FBI, and the Netherlands' AIVD links Iranian state-linked actors to CHOSEN BRICK, a Windows spyware family used for long-term surveillance since at least 2025. Targets are approached on WhatsApp or Telegram with tailored lures such as fake MRI scan results or application files, and operators often redirect victims to personal devices to bypass corporate controls. The malware persists via Run registry keys, adds antivirus exclusions, uses a per-victim Telegram bot for command and control, and exfiltrates data through cloud storage and proxy services. Capabilities include screenshots, audio recording, email and messaging theft, command execution, file deletion, data wiping, and some victims' details have appeared on pro-Iranian leak sites for harassment.

Cyber Security Newsupdated · 53m agofirst · 1h agoThreat actor in the wild 4 sources

Nums AI Releases Causilo: A Tabular Foundation Model That Tops TabArena Among Single Models

Nums AI released Causilo, an Apache-2.0 tabular foundation model achieving the highest single-model Elo (1794) on TabArena for classification and regression.

Nums AI released Causilo 1.0.1, a pretrained in-context learning tabular foundation model for classification (up to 10 classes) and regression, with Apache-2.0 code and research-only weights on Hugging Face. It achieved the highest single-model TabArena Elo of 1792.9 overall, beating TabFM (1764.4) and EXAONE Tabular (1758.8), and a maintainer re-run placed it 3rd of 88 including system entries. It also ranked first by CRPS, R² and RMSE on ScoringBench across 101 datasets, and was fastest on fit and predict versus TabICLv2 and TabPFN-3 on an H100 GPU at 8.15 GiB memory. The model was pretrained only on synthetic data, uses cross-attention to keep cost linear in feature count, and version 1.0.1 adds quantile outputs via 999 native quantiles.

MarkTechPost · 5h agoModel release

Building a Linux GPU Driver for the M4 Mac Mini in One Month

Two developers built a fully OpenGL ES 3.0 compliant Linux GPU driver for the M4 Mac Mini in one month via clean-room reverse engineering.

Niklas and the author reverse engineered Apple's AGX GPU firmware ABI and user-space components in about a month, a process that normally takes years, producing an OpenGL ES 3.0 conformant driver fast enough to run Minecraft at 200fps on an M4 Mac Mini. The work was done transparently using hypervisor traces without examining Apple binaries, following clean-room practices, and included a custom shader compiler, command stream builder, and a full Linux kernel driver for the firmware ABI. The A18 Pro firmware ABI proved significantly more complex than the M1's, with 1.5x as many structs and twice as many pointers. All experiments and provenance evidence were published in public agx-re repositories.

Google launches Gemini 3.8 Live to take on OpenAI's GPT-Live-1 at a fraction of the cost

Google DeepMind launches Gemini 3.8 Live speech-to-speech models, topping Artificial Analysis leaderboard at 82.6% with much cheaper pricing than OpenAI.

Google DeepMind released Gemini 3.8 Live and 3.8 Live Extended Thinking, audio models for voice agents available through the Gemini API and Google AI Studio, supporting over 97 languages plus background API calls and visual input. The Extended Thinking variant ranks first on the Artificial Analysis Speech-to-Speech Leaderboard with 82.6%, ahead of OpenAI's GPT-Live-1 models. Google charges $0.005 per minute for audio input and $0.018 for output, versus OpenAI's $0.05 per minute, though OpenAI retains full-duplex conversation quality advantages.

The Decoder · 15h agoModel release1

Reduced-Space Multi-Fidelity Bayesian Optimization of Process Simulation Models

RS-MFBO couples global sensitivity analysis with fidelity-augmented Gaussian processes to slash costly high-fidelity simulation runs in industrial flowsheet optimization.

The paper presents RS-MFBO, a reduced-space multi-fidelity Bayesian optimization framework for high-dimensional, expensive black-box functions. It integrates Global Sensitivity Analysis for dimensionality reduction with a fidelity-augmented Gaussian process and a cost-aware acquisition strategy featuring cooldown and promotion mechanisms. Validation on a plasmid DNA bioprocess (SuperPro Designer) and a green fuel synthesis plant (Aspen HYSYS) shows substantial reductions in high-fidelity evaluations while remaining competitive with single-fidelity baselines.

arXiv cs.AI / cs.LG / cs.CL · 17h agoAI research

Learning-Guided Planning in Large Dynamic Action Spaces: Budgeted Tree Search for One-to-Many Mobile Charging

LP-BTS uses graph proposal policies, learned critics, and budgeted PUCT search to plan mobile charging across dynamic action spaces up to 2,813 stops.

LP-BTS is a learning-guided planning architecture for one-to-many mobile charging, where N=250 sensors induce roughly 1,125 initial candidate charging stops. A graph proposal policy concentrates candidate support, a learned value critic evaluates leaves, and edge-budgeted PUCT compares simulated futures, letting a single frozen checkpoint cover action universes from 736 to 2,813 stops. On a sealed 30-scenario confirmatory bank it attains the highest observed survival (0.4545) and alive-AUC (0.8031), though its +0.0066 survival edge over the strongest engineered comparator is statistically unresolved.

arXiv cs.AI / cs.LG / cs.CL · 17h agoAI research

OPEN-1B: A Fully Auditable Training Run

Open-1B releases a 1B-parameter model with bitwise-reproducible training, letting independent auditors verify every step of the run on commodity hardware.

The paper introduces a 'fully auditable' tier of model transparency: every training operation is reproducible with bitwise certainty on heterogeneous commodity hardware by imposing definite ordering on GPU kernel reductions, data batch ordering, and collective communication. Because replaying a full run on one machine is infeasible, a collective verification scheme lets many independent auditors certify individual steps covering the whole run. The authors release Open-1B with its full pretraining dataset, every intermediate checkpoint, the training codebase, and an audit harness. This rules out undisclosed data, injected biases, or backdoors that proof-of-learning or proof-of-training-data techniques cannot exclude.

arXiv cs.AI / cs.LG / cs.CL · 17h agoAI research

BambooToken malware controls Windows and Linux systems via MQTT

Lumen Black Lotus Labs exposes BambooToken, a China-aligned malware framework using MQTT C2 to backdoor Windows and Linux systems at roughly a dozen enterprises.

Lumen's Black Lotus Labs documented BambooToken, a previously unknown malware framework active since at least 2023 that adopted MQTT for command-and-control in 2024-2025 variants targeting Windows and Linux. Infection occurs via DLL side-loading through digitally signed Tendyron OnKey USB-token software or an impersonated Kingsoft Office installer; dead code suggests keylogging, clipboard theft, audio/webcam capture, and screenshot modules. Telemetry identified roughly a dozen compromised entities, mostly in Asia and South America, including a Hong Kong GitLab server and possibly users of the SpeedCN VPN service. Targeting patterns are consistent with China-aligned operations, though no attribution to a known cluster was made.

BleepingComputerupdated · 18h agofirst · 19h agoMalware in the wild 2 sources1

Observational Indistinguishability and Integrity Blind Regions in Hybrid Quantum-Classical Workflows

Framework formalizes integrity blind regions in hybrid quantum-classical workflows, validated across 3,600 label interventions with conformal detection rules.

The paper presents a claim-relative evidence and reference framework for integrity of hybrid quantum-classical workflows, distinguishing structural blind regions caused by observational indistinguishability from finite-batch statistical misses. Experiments over 3,600 label interventions show exact label-path invariance for feature and prediction views. The geometry-aligned construction detects 343 of 2,700 conclusion-changing interventions using the conformal rule and 1,183 of 2,700 with the uncorrected union, with executed conformal clean false-action rates of 0.048-0.059.

arXiv cs.CR · 20h agoResearch

Iranian cyber targeting of dissidents, activists and journalists

UK NCSC, FBI, and Dutch AIVD expose CHOSEN BRICK spyware used by Iranian state actors against dissidents, activists, and journalists worldwide.

A joint advisory from the UK NCSC, FBI, and Dutch AIVD details CHOSEN BRICK, a Windows spyware family used by Iranian state cyber actors since at least 2025 against dissidents, activists, and journalists in the UK, US, and Netherlands. Actors build rapport on WhatsApp and Telegram impersonating known contacts or platform support, then deliver disguised payloads resembling apps such as Telegram, Norton, RunwayML, or fake MRI results. The malware persists via HKCU Run registry keys, adds Microsoft Defender exclusions, and uses a unique Telegram bot C2 per victim. Capabilities include screen capture, microphone recording, process enumeration, email and messaging data theft, file deletion, and system wiping; victim data has appeared on pro-Iranian leak sites.

NCSC UK · 22h agoThreat actor in the wild2

TasmScan: Continuation-Aware Taint Analysis for TVM Bytecode with Savelist Abstraction

TasmScan introduces source-free taint analysis for TON smart-contract bytecode, detecting 95.3% of defects with 96.8% precision and 17x speedup.

TasmScan is the first bytecode-level static analysis framework for the TON Virtual Machine, enabling cross-continuation data flow reasoning without source code by modeling savelist semantics through forward register analysis with formal over-approximation guarantees. It lifts bytecode into a typed intermediate representation (TASIR) and performs path-sensitive taint analysis. On a 208-contract benchmark with human-confirmed ground truth it detects 95.3% of defects across five classes at 96.8% precision, and resolves 294,546 dynamic continuation targets with 100% precision across 2,921 registry contracts. It achieves a 17x median speedup over symbolic-execution baselines.

arXiv cs.CR · 22h agoResearch