Search: “spelevo”

Threat Brief: Maze Ransomware

Unit 42 issued a threat brief on Maze ransomware, noting an uptick across industries and exploitation of Pulse VPN and IE flaws for initial access.

Palo Alto Networks detected an uptick in Maze ransomware samples across finance, healthcare, government, and other sectors. Maze, a variant of ChaCha ransomware first seen in May 2019, is distributed via weaponized Word/Excel attachments and the Spelevo exploit kit leveraging CVE-2018-15982 and CVE-2018-4878, and has used CVE-2019-11510 (Pulse VPN) and CVE-2018-8174 (Internet Explorer). Operators establish a foothold, escalate privileges, move laterally, and exfiltrate files before encryption for extortion leverage.

Palo Alto Unit 42·Aug 17, 13:17 UTC · Aug 17, 2026Ransomware in the wildCVE-2018-15982CVE-2018-4878CVE-2019-11510+1 CVEs

Researchers Uncover RovoBlast Vulnerability in Atlassian AI Assistant

Atlassian fixed RovoBlast, a flaw letting a single crafted link make its Rovo AI assistant exfiltrate company data.

Researchers disclosed a vulnerability dubbed RovoBlast affecting Atlassian's Rovo AI assistant. A single crafted link could cause the assistant to exfiltrate company data accessible to it. Atlassian has since fixed the flaw; no widespread exploitation was reported in the disclosure.

Infosecurity Magazine·Aug 10, 15:30 UTC · Aug 10, 2026Vulnerability

Atlassian Rovo Can Be Tricked Into Sending Jira and Confluence Data to Attackers

The Hacker News·Aug 8, 08:54 UTC · Aug 8, 2026Exploit / PoC in the wild

Reward AI Releases OM-1: A Robot Policy Trained on Human Demonstrations Only, With No Teleoperation or On-Robot Data

Reward AI released OM-1, a general-purpose manipulation policy trained solely on human demonstrations from a sensorized glove, with no teleoperation or robot data.

Reward AI announced OM-1 (Omnibody Model 1), a general-purpose robot manipulation policy trained only on human demonstrations captured via Omnibody Hand, a 7-DoF wearable glove with tactile, proximity, and in-hand camera sensing. The system uses electromagnetic hand-pose tracking, cutting mean overshoot error to 9.5 mm versus 24.9 mm for visual-inertial at 67 cm/s (a 60% reduction), and reportedly learns brand-new tasks from under 30 minutes of human data. A separate RL-trained control layer runs on its own clock so policy inference latency never stalls motion, and the policy spans industrial arms, legged humanoids, and wheeled mobile manipulators. No weights, code, dataset, API, paper, or benchmark comparisons have been released, so claims are demonstration-backed only.

MarkTechPost·Sep 14, 21:08 UTC · 1d agoAI research

What Matters, When? Diagnosing and Improving Conditional Visual Grounding in Visuomotor Imitation Policies

Researchers diagnose conditional visual grounding failures in visuomotor imitation policies and show targeted interventions substantially improve distractor robustness.

The paper studies why ACT-based visuomotor imitation policies fail when visually similar distractor objects or receptacles are introduced, finding sensitivity depends on both distractor type and manipulation stage. Interventions including distractor augmentation, phase-dependent attention regularization, and appearance-based visual prompting improve target selection while preserving spatial control information, with gains in simulation and on a physical UR3e. The same failure pattern is confirmed in a pretrained vision-language-action policy on a state-conditioned medical instrument-handling task.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 17:27 UTC · 11d agoAI research

Attackers Exploit Critical Switchvox Flaw to Deploy Reverse Shells Without Credentials

Attackers exploit unauthenticated SQL injection CVE-2026-9586 in Sangoma Switchvox to run PostgreSQL commands and deploy reverse shells.

Threat actors are exploiting CVE-2026-9586 (CVSS 9.3), an unauthenticated SQL injection in Sangoma Switchvox SMB Edition 8.3 (104997), since August 30, 2026, running arbitrary SQL as the PostgreSQL superuser and achieving remote code execution. The /pa endpoint concatenates the user-controlled PhoneIP value into PostgreSQL queries; attackers can extract database contents, escalate to Switchvox web administrator, exfiltrate the cookie signing key to forge authentication, and invoke reverse shells. Sangoma patched the flaw in Switchvox 8.4.0.2 on July 14, 2026, roughly 4,000 instances are internet-exposed (mostly in the US), and honeypot activity from IP 176.65.148.184 deploys reverse shells followed by Base64-encoded process enumeration.

The Hacker News·Sep 2, 07:08 UTC · 14d agoExploit / PoC in the wildCVE-2026-9586

Pegasus and NoviSpy Used Against Serbian Protesters

Citizen Lab confirmed zero-click Pegasus infected a Serbian student activist's iPhone, part of the largest documented Serbian spyware wave targeting at least 14 people.

The Citizen Lab, with the SHARE Foundation, confirmed a Serbian student protest movement member's iPhone was infected with NSO Group's Pegasus via an iMessage zero-click exploit between December 2025 and January 2026; Apple patched the exploit in iOS 18.4.1. SHARE Foundation has documented at least 14 targeted individuals since early 2026, including student activists, civil society figures, an opposition MP and a local councilor, coinciding with the March 2026 local elections. SHARE and Amnesty Tech also found a new NoviSpy variant on a student activist's Android phone after Serbian authorities seized it during police questioning.

Security Affairs·Sep 3, 20:17 UTC · 12d agoThreat actor in the wild

Axis Robotics Releases AXIS: A Browser-Based Data Engine With 207 Robot Manipulation Tasks and 50,129 Trajectories

Axis Robotics and academic partners released AXIS, a browser-based teleoperation system yielding 207 manipulation tasks and 50,129 trajectories that lifts pi0.5 to 88.8 on LIBERO-Plus.

A team from Axis Robotics, UC Berkeley, Georgia Tech, and NTU introduced AXIS, a browser-based data engine where contributors teleoperate a simulated Franka Research 3 in a MuJoCo WebAssembly frontend while GPU backends handle task generation, training, and evaluation. The released snapshot holds 207 tasks, 50,129 episodes, and 60K+ task or scene variants from more than 70,000 community contributors. Continual pretraining of pi0.5 on AXIS data raises LIBERO-Plus performance from 83.9 to 88.8, versus 57.5 for a volume-matched RoboCasa365 control; the 2.36 TB dataset is gated for non-commercial academic use.

MarkTechPost·Sep 7, 18:38 UTC · 8d agoAI research

Pegasus Zero-Click Exploit Infects Serbian Student Activist's iPhone

Citizen Lab and SHARE Foundation confirm a Serbian student activist's iPhone was infected with NSO Group Pegasus via a zero-click iMessage exploit.

Forensic analysis found high-confidence infection indicators on the activist's iPhone during December 2025 and January 2026, using an iMessage zero-click exploit the Citizen Lab believes was patched as of iOS 18.4.1, released April 2025. The target was among at least 14 Apple Threat Notification recipients in Serbia's student movement, civil society, and opposition politics documented by the SHARE Foundation. Targeting occurred ahead of key 2026 election cycles; Amnesty Tech also confirmed a new NoviSpy version on another student movement member's device.

Infosecurity Magazine·Sep 3, 15:25 UTC · 12d agoThreat actor in the wild

GE-Act 2.0: Pretraining and Scaling a World-Action Model for Robotic Manipulation

GE-Act 2.0 is a from-scratch pretrained world-action model for robotic manipulation, with success rising from 17.1% to 44.1% as co-training data scales to 30,000 hours.

Genie Envisioner Act 2.0 (GE-Act 2.0) is a world-action model whose generative and action components are all initialized from scratch on manipulation data, combining a control-oriented autoencoder (CoAE), single-step visual planner (SVP), and inverse dynamics model (IDM) trained jointly via knowledge-aligned selective optimization (KASO). Scaling co-training data from 300 to 30,000 hours raises zero-shot success from 17.1% to 44.1% on G1-OP and 13.4% to 31.1% on G2-90D, despite the latter comprising under 2% of data, suggesting cross-embodiment transfer. Gains span 19/20 and 18/20 skill groups, and skill-specific coverage correlates with zero-shot OOD success (Pearson r=0.80).

Hugging Face daily papers·Sep 3, 20:00 UTC · 12d agoAI research

Tricky 'SynkLoader' Multitool May Herald Ransomware

Researchers detail SynkLoader, an advanced multilingual multitool that hijacks screens to steal passwords and may precede ransomware attacks.

Dark Reading reports analysis of SynkLoader, an advanced, multilingual malware family functioning as a multitool loader. The family revives an older technique — screen hijacking — to enable effective password theft, alongside several novel features. Analysts assess its activity may be a precursor to ransomware deployments, making early detection valuable for defenders.

Dark Reading·Aug 24, 15:02 UTC · 22d agoMalware

Off the Hook: Discovering and Observing Active Exploitation of Sangoma Switchvox CVE-2026-9586

Horizon3 disclosed CVE-2026-9586, an unauthenticated SQL injection in Sangoma Switchvox leading to RCE, now under active exploitation in the wild.

Horizon3.ai attack researchers discovered CVE-2026-9586, an unauthenticated SQL injection vulnerability in Sangoma's Switchvox VoIP appliance that can escalate to remote code execution. The researchers observed active exploitation of the flaw in the wild. A disclosure write-up was published alongside their findings, and defenders should treat internet-exposed Switchvox instances as at risk.

Horizon3.ai·Sep 1, 10:01 UTC · 15d agoExploit / PoC in the wildCVE-2026-9586

Hackers Target Claude, Cursor and Codex AI Agents to Steal Tokens and Prompt Histories

Gen Digital found infostealers like Amatera and Remus stealing AI coding agent tokens, prompt histories, and MCP configs from infected Windows and macOS machines.

Gen Digital analysts observed Amatera and Remus detections among tens of thousands of protected Windows users over three months, with Amatera targeting Cline and Continue data and Remus targeting Claude, Cursor, and OpenCode. CallbackBeaver added Cursor and Claude to its collection scope with more than 5,000 samples in 30 days, while macOS-focused Djinn Stealer has been associated with Claude, Codex, Gemini, Cline, OpenCode, and Kilo. The stealers harvest access and refresh tokens, prompt histories, and MCP configuration files that can expose source control, ticketing, databases, cloud resources, and sensitive project context for follow-on fraud. Many stealers add targets via remotely managed rules, meaning this is an adaptation of existing infostealers rather than a new vulnerability in the AI tools themselves.

Cyber Security News·Sep 9, 11:41 UTC · 7d agoMalware in the wild2

Pegasus Zero-Click Spyware Exploit Infects Serbian Student Movement Member's iPhone

Citizen Lab confirms Pegasus zero-click iMessage spyware infected a Serbian student activist's iPhone amid at least 14 spyware targets in Serbia during 2026.

The Citizen Lab, with the SHARE Foundation, confirmed an iMessage zero-click exploit infected a Serbian student protest movement member's iPhone with NSO Group's Pegasus spyware, with high-confidence indicators from December 2025 to January 2026. The exploit was addressed by Apple in iOS 18.4.1, released April 2025. At least 14 people in Serbia, including students, activists, an MP, and a councilor, were targeted with advanced spyware since the start of 2026, coinciding with March 29, 2026 local elections; a new Android spyware similar to NoviSpy was also found on a confiscated device.

The Hacker News·Sep 3, 08:43 UTC · 13d agoThreat actor in the wild

ThinkPrior: Zero-Rollout Difficulty Priors for Cold-Start Prompt Selection in RLVR

ThinkPrior builds zero-rollout difficulty priors via an offline verifier-anchored pass, halving silent groups in RLVR and cutting wasted rollouts on Qwen2.5-Math-7B.

In GRPO-based RLVR, groups where all rollouts are correct or all are wrong yield zero advantages and consume about 39% of a run's rollouts under uniform sampling. ThinkPrior initializes a Beta posterior from an external anchor pass's verifier-scored pass rate, selecting prompts by expected learnability before any target-policy rollout, without changing the loss or optimizer. On Qwen2.5-Math-7B across sixteen seeds it more than halves early silent groups and cuts wasted rollouts through step 30 by nearly a fifth, with no detected final-accuracy difference. The ThinkPrior+DAPO composition reduces generated rollouts by 10.6% at an equal 3,840-rollout update budget.

arXiv cs.AI / cs.LG / cs.CL·Sep 8, 17:30 UTC · 7d agoAI research1

The AI Kill Switch Act is repeating the Clipper Chip’s mistakes

Op-ed argues the AI Kill Switch Act repeats the Clipper Chip's mistake by mandating backdoors into frontier AI systems.

The op-ed criticizes the AI Kill Switch Act, sponsored by Reps. Ted Lieu and Nathaniel Moran, which would let CISA require frontier AI labs to build the ability to throttle, suspend, or shut down their systems. The author compares this to the 1993 Clipper Chip, whose Law Enforcement Access Field was found flawed in 1994, and argues mandated kill switches would create deliberate weaknesses in AI agents embedded in banking, power grids and other critical infrastructure. It also flags the bill's exemption of red-teaming incidents and CAISI's incomplete agent security standards, recommending mandatory red-teaming and liability frameworks instead.

CyberScoop·Aug 31, 10:00 UTC · 16d agoAI policy

DeepZero: Open-source hunting for vulnerable Windows drivers

DeepZero, a new open-source engine, automates discovery of exploitable Windows kernel drivers for BYOVD attacks using Ghidra, Semgrep, and an LLM.

DeepZero is a free, open-source Python pipeline orchestrator that automates hunting for exploitable Windows kernel drivers relevant to BYOVD (bring your own vulnerable driver) attacks. Its seven-stage YAML pipeline parses PE headers, filters for kernel-mode drivers with IOCTL surfaces, excludes drivers listed on loldrivers.io, then runs headless Ghidra decompilation, Semgrep scanning, and an LLM-based exploitability assessment. The maintainer reports multiple verified vulnerabilities in the Snappy Driver Installer corpus, some still in the disclosure process, and notes findings involving plug-and-play-created device objects may need physical hardware to confirm.

Help Net Security·05:30 UTC · 9h agoTools

C2Looper: A New Backdoor Likely Tied To Ransomware With GitHub C2

Zscaler ThreatLabz identified C2Looper, a new Rust-based backdoor likely tied to ransomware actors and delivered via ClickFix chains, using GitHub for C2.

In July 2026, Zscaler ThreatLabz identified C2Looper, a new Rust-based backdoor family. The malware supports arbitrary command execution, reconnaissance, and deployment of second-stage payloads, and uses GitHub as its command-and-control channel. ThreatLabz assesses with low-to-medium confidence that it is delivered through multi-stage ClickFix infection chains and is likely leveraged by a ransomware-related threat actor. The analysis covers multiple C2Looper variants, their network protocols, and capabilities.

Zscaler ThreatLabz·Aug 17, 14:06 UTC · Aug 17, 2026Malware in the wild1

Infostealers Target Claude, Cursor, Codex and Other AI Agents to Steal Credentials and Sensitive Data

Gen Digital researchers report infostealer families Amatera, Remus and CallbackBeaver now harvest Claude, Cursor and Codex agent data, including tokens and MCP configs.

Gen Digital researchers found commodity infostealers extending their collection rules to local AI coding agent data from Claude, Cursor, Codex, Cline, Continue and OpenCode on Windows and macOS. Amatera targets Cline and Continue, Remus targets Claude, Cursor and OpenCode, and CallbackBeaver added Claude and Cursor with more than 5,000 samples observed in 30 days; Djinn Stealer hits Claude, Codex, Gemini, Cline, OpenCode and Kilo on macOS. Stolen data includes access and refresh tokens, prompt histories, conversation databases and MCP configurations holding API keys, potentially exposing connected source-control, cloud and ticketing systems. Remus is assessed as a Lumma Stealer variant using EtherHiding C2 resolution via Ethereum smart contracts.

GBHackers·Sep 9, 07:05 UTC · 7d agoMalware in the wild1

TANGO: Humanoid Navigation in Cluttered Environments with a Whole-Body Vision-Language-Action Model

Researchers introduce TANGO, a whole-body vision-language-action model enabling zero-shot language-guided humanoid navigation on the Unitree G1 robot.

TANGO addresses humanoid navigation in cluttered indoor environments by predicting 29-DoF joint-space actions directly from natural-language instructions and egocentric RGB, rather than 2D path planning. It is trained entirely in simulation via a pipeline combining global path planning, kinematic whole-body motion generation, obstacle-aware motion editing, and RL-based tracking. In simulation it achieves state-of-the-art vision-language navigation performance and transfers zero-shot to a Unitree G1 humanoid without any real-world navigation data.

Hugging Face daily papers·Sep 7, 20:00 UTC · 8d agoAI research1

LLM Forensics: Where Do Backdoors Hide? Localizing and Controlling Trigger Mechanisms with Sparse Autoencoders

Researchers use sparse autoencoders to localize trigger-based backdoor mechanisms in 1B and 8B LLMs, finding detection features differ from causal control features.

In a controlled language-switching backdoor setting where fixed trigger sequences make 1B and 8B language models continue English prompts in French or German, the authors train sparse autoencoders (SAEs) across layers and transformer components. Attention and MLP features detect triggered prompts with near-perfect F1, but ablating them rarely suppresses the language switch, while residual-stream features can suppress triggered generation and some can induce target-language continuations without the trigger. The work decomposes token-trigger mechanisms into distinct SAE feature roles: trigger detection, residual-stream propagation, and language tracking, a decomposition the authors expect to transfer to other trigger-based backdoors.

arXiv cs.AI / cs.LG / cs.CL·Sep 7, 16:47 UTC · 8d agoAI safety & security1

Pro-Ukraine Hacking Cat group deploying new malware against Russian targets

Kaspersky links pro-Ukraine hacktivist group Hacking Cat to Gorilla RAT and Monkey Ransomware in destructive attacks on Russian targets.

Kaspersky reports that pro-Ukraine group Hacking Cat, active since February 2024, has shifted from defacements to destructive encryption attacks, using a previously undocumented Gorilla RAT remote-access tool and Monkey Ransomware, which appends the .monkey extension to files. Initial access in some attacks came from exploited Microsoft Exchange vulnerabilities, and rapid multi-language malware variants suggest possible generative AI assistance. Shared tools like Nemo Wiper across groups including Ukrainian Cyber Alliance complicate attribution, and targets include Rosatom contractor and heating provider Donbassteploenergo.

The Record·Sep 14, 16:15 UTC · 1d agoThreat actor in the wild

The Pelican comparison grid for Astra is pretty interesting

Simon Willison's pelican SVG comparison shows GPT-6 Astra producing markedly better images than GPT-5.6 Sol, Terra, and Luna across reasoning levels.

Willison generated pelicans-riding-bicycles SVGs with newly accessed GPT-6 Astra at low through max reasoning levels and rendered them in a comparison grid against GPT-5.6 Sol, Terra, and Luna. Astra's outputs were markedly more coherent, while even the best GPT-5.6-Sol images remained largely abstract shapes. Astra does not support a reasoning=none setting, so all comparisons involved reasoning-enabled runs.

Simon Willison·Sep 4, 23:59 UTC · 11d agoAI research

Sevii APS Module preempts attacks with autonomous cyber defens

Help Net Security·Aug 4, 00:00 UTC · Aug 4, 2026Exploit / PoC

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·Sep 15, 16:42 UTC · 21h agoAI research

CosmoH2G: A Hand-to-Gripper Transfer Dataset and Baseline Method for Object Manipulation with Complex Spatial Movements

Researchers release CosmoH2G, a 6,189-episode hand-to-gripper dataset with a two-stage method for complex spatial robot manipulation.

The paper introduces a scalable acquisition pipeline using a handheld gripper to collect paired hand-gripper demonstrations, producing 6,189 episodes across 1,254 unique objects with higher spatial complexity than existing benchmarks. A two-stage framework first predicts sparse gripper keyframes (initial and terminal), then generates the full continuous action sequence conditioned on them, while learning gripper orientation and post-optimizing translation via grasping heuristics and kinematic consistency. Simulation and real-robot experiments show stable, precise hand-to-gripper transfer of complex spatial manipulations, outperforming traditional baselines.

Hugging Face daily papers·Sep 6, 20:00 UTC · 9d agoAI research

Cortex XSIAM Archives

Palo Alto Networks positions Cortex XSIAM as a purpose-built platform to simplify security operations and speed incident remediation.

The Unit 42 blog page is a product category archive for Cortex XSIAM. The platform is marketed as purpose-built for SecOps transformation, simplifying security operations and accelerating incident remediation against current and future threats. No research findings, incidents, or vulnerabilities are discussed.

Palo Alto Unit 42·Sep 8, 14:27 UTC · 8d agoIndustry 6 sources

LLaDA-UI: Bringing Block-wise Diffusion to Vision-Language GUI Agents

LLaDA-UI, a 16.7B block-wise diffusion vision-language GUI agent, outperforms Qwen2.5-VL-7B and beats Qwen3-VL-8B on four of six GUI benchmarks.

LLaDA-UI is a 16.7B-parameter MoE-based, block-wise diffusion vision-language GUI agent built on the LLaDA2.0-mini-base diffusion language backbone with a native-resolution vision encoder. It uses a two-stage pipeline: general multimodal pre-training followed by GUI-agent supervised fine-tuning on mobile, desktop, web, and grounding data. It substantially outperforms Qwen2.5-VL-7B and surpasses Qwen3-VL-8B on four of six reported GUI benchmarks, establishing block-wise diffusion as a practical paradigm for latency-sensitive multimodal agents.

Hugging Face daily papers·Sep 8, 20:00 UTC · 7d agoAI research

Threat Actors Abuse Cursor Agent AI to Assist Ransomware Operations

Aurora ransomware operators are using SpaceX-owned Cursor's AI agent to perform reconnaissance and exploitation tasks during intrusions.

The Aurora ransomware group is abusing the Cursor Agent AI coding tool to automate reconnaissance and exploitation activities during its operations. This marks a notable case of criminals weaponizing an AI coding agent inside their attack workflow. Cursor was recently acquired by SpaceX, drawing extra attention to the tool's abuse.

Infosecurity Magazine·Aug 28, 08:00 UTC · 19d agoRansomware in the wild

TANGO: Humanoid Navigation in Cluttered Environments with a Whole-Body Vision-Language-Action Model

Researchers present TANGO, a whole-body vision-language-action model enabling humanoid robots to traverse cluttered spaces from language instructions.

TANGO predicts 29-DoF joint-space actions from egocentric RGB observations and natural-language instructions for whole-body humanoid navigation, going beyond 2D path planning. It is trained entirely in simulation using global path planning, kinematic whole-body motion generation, obstacle-aware motion editing, and RL-based tracking. The model reports state-of-the-art simulation performance and was deployed zero-shot on a Unitree G1 humanoid without any real-world navigation training data.

arXiv cs.AI / cs.LG / cs.CL·Sep 8, 17:59 UTC · 7d agoAI research1

Cortex Xsoar

Palo Alto Networks Unit 42 hosts content under its Cortex XSOAR category, covering the vendor's security orchestration, automation and response platform.

The item is a Unit 42 category page for Cortex XSOAR rather than a standalone article; no article text was available. Cortex XSOAR is Palo Alto Networks' security orchestration, automation and response (SOAR) platform used for incident management and playbooks. No incident, vulnerability, or research findings could be extracted from the available information.

Palo Alto Unit 42·Aug 17, 12:20 UTC · Aug 17, 2026Tools