Search: “AutoFocus”

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TrickBot Campaign Uses Fake Payroll Emails to Conduct Phishing Attacks

TrickBot phishing campaign used SendGrid, fake Google Docs, and Drive-hosted downloaders disguised as Word files to deliver a credential-stealing payload.

Unit 42 identified a TrickBot distribution campaign on November 7-8, 2019, using payroll and annual bonus-themed emails sent from likely compromised .edu addresses through the legitimate SendGrid email delivery service. Emails contained links to Google Docs documents linking to downloader executables hosted on Google Drive, further masked behind SendGrid click-tracking URLs. The downloaders, signed by PERISMOUNT LIMITED and displayed with Microsoft Word icons, show a decoy pop-up and retrieve TrickBot payloads from compromised legitimate domains such as savute[.]in and lindaspryinteriordesign[.]com. The newer TrickBot variant stores its files and configuration under %APPDATA%\cashcore.

Palo Alto Unit 42·Aug 17, 13:18 UTC · 29d agoPhishing & fraud

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DriveZero: End-to-End Driving Beyond Human Demonstrations

DriveZero pairs a frozen vision-foundation-model perception stack with a PPO-trained closed-loop RL teacher to beat replay experts on nuPlan.

DriveZero is an end-to-end camera-only autonomous-driving planner that separates perception and action. Its DriveVFM perception backbone consolidates frozen vision foundation models (DINOv3, SigLIP2, SAM, Depth Anything V2) from raw images without task annotations, while DriveRL trains a privileged PPO teacher policy through closed-loop rollouts in interactive worlds built from real driving logs. The planner distills this teacher, achieving a 93.57 mean nuPlan score across Val14, Test14-hard and Test14-random splits and beating the Log-Replay expert on all three. It also sets state of the art on NAVSIMv1, NAVSIMv2 and closed-loop HUGSIM without human trajectory supervision.

Hugging Face daily papers·Sep 4, 20:00 UTC · 11d agoAI research

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xHunt Campaign: New Watering Hole Identified for Credential Harvesting

Unit 42 tied the xHunt campaign to a watering hole on a Kuwait government website used to passively harvest visitors' NTLM credential hashes.

Palo Alto Unit 42 identified a Kuwait government organization's webpage injected with hidden HTML referencing image paths on domains (microsofte-update.com, learn-service.com) tied to xHunt/Hisoka C2 infrastructure. When visitors loaded the page, Windows would attempt SMB/NetBIOS authentication to the remote share, allowing the operators to capture NTLM hashes that could be cracked or relayed. Related DNS redirect activity on xHunt infrastructure in 2019 pointed to additional credential-harvesting interest against Kuwaiti government email servers.

Palo Alto Unit 42·Aug 17, 13:18 UTC · 29d agoThreat actor in the wild

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SlipSense: Multimodal Tactile Learning for Low-Latency and Generalized Slip Detection

SlipSense fuses a 32x32 piezoresistive array and MEMS accelerometer to detect robotic grip slips within 23.1 ms, generalizing zero-shot across platforms.

SlipSense is a multimodal tactile slip-detection framework built on TacV5, a sensor combining a 32x32 piezoresistive array at 240 Hz and a 3-axis MEMS accelerometer at 8 kHz. It performs modality-specific encoding, intra-sensor fusion, and cross-modal attention with causal temporal prediction at 240 Hz. On a 1.4-million-frame dataset spanning 37 objects it achieves 96.7% Macro F1 with a false-positive rate below 1.6%, detecting 76% of slip events within 23.1 ms. Trained solely on UMI data, it transfers zero-shot to a Tesollo dexterous hand across unseen objects, sensor units, and platforms.

arXiv cs.AI / cs.LG / cs.CL·Sep 14, 17:23 UTC · 1d agoAI research

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KRBanker Targets South Korea Through Adware and Exploit Kits

Unit 42 details KRBanker banking trojan targeting South Korean bank users via KaiXin exploit kit and NEWSPOT adware, using pharming and process hollowing.

KRBanker (aka Blackmoon) is a banking trojan targeting online banking users in the Republic of Korea, with roughly 2,000 unique samples and 200+ pharming servers observed by Unit 42 over six months. It is distributed through the KaiXin exploit kit exploiting Adobe Flash CVE-2014-0569 and CVE-2015-3133, and through the NEWSPOT adware update channel that also delivers the Venik trojan. The trojan uses process hollowing, retrieves pharming server IPs from Qzone profile nickname fields, and abuses Proxy Auto-Config with a local proxy to redirect banking traffic to forged sites.

Palo Alto Unit 42·Aug 17, 12:57 UTC · 29d agoMalware in the wildCVE-2014-0569CVE-2015-3133

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Recorded Future Launches AI Alert Filtering

Recorded Future launched AI Alert Filtering to automatically triage threat intelligence alerts by relevance, letting analysts prioritize faster while retaining control.

Recorded Future announced general availability of AI Alert Filtering, powered by Recorded Future AI. The feature automates the first pass of filtering alerts by relevance so analysts can prioritize faster while keeping human control. It applies LLM-based automation to threat intelligence alert triage workflows.

Recorded Future·Aug 26, 00:00 UTC · 21d agoTools

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New Mirai Variant Targeting Network Security Devices

New Mirai botnet variant exploits nine vulnerabilities in SonicWall, D-Link, Netgear, and other devices, with attacks ongoing at publication.

Unit 42 observed attacks exploiting VisualDoor (SonicWall SSL-VPN), CVE-2020-25506 (D-Link DNS-320), CVE-2020-26919 (Netgear ProSAFE Plus), and other flaws, with infrastructure rotating across at least three IP addresses between February 16 and March 13, 2021. Payloads were updated hours after CVE-2021-27561 and CVE-2021-27562 (Yealink Device Management, unauthenticated root RCE) and later added CVE-2021-22502 (Micro Focus Operation Bridge Reporter) and CVE-2019-19356 (Netis WF2419). Successful exploitation invokes wget to fetch shell scripts that download Mirai binaries compiled for multiple architectures and brute-forcers, and attacks were still ongoing when reported.

Palo Alto Unit 42·Aug 19, 12:04 UTC · 27d agoExploit / PoC in the wildCVE-2020-25506CVE-2020-26919CVE-2019-19356+3 CVEs

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Modality-Autoregressive World-Action Models

ModAR autoregressively denoises multiple future modalities (point tracks, DINO features, depth) before predicting actions, beating prior world-action models at all data scales.

ModAR is the first world-action model (WAM) to autoregressively denoise multiple future modalities before predicting actions, letting each prediction condition on previously generated modalities. Training from scratch shows WAMs benefit from predicting point tracks, DINO features, and depth maps, while future RGB adds no consistent benefit. ModAR's sequential generation outperforms existing WAM formulations with the highest average success rate at all evaluated data scales. It slightly beats video-model-initialized Flex-π (75% vs 72% success) using roughly 20x fewer training FLOPs and no pretraining, and wins on three real-world bimanual tasks.

Hugging Face daily papers·Sep 14, 20:00 UTC · 1d agoAI research

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Threat Assessment: Ryuk Ransomware

Unit 42 assesses Ryuk ransomware amid a CISA/FBI/HHS alert on threats to U.S. healthcare, including the UHS attack that disrupted hospital operations.

A joint CISA, FBI, and HHS alert on October 28, 2020 warned of an imminent threat to U.S. healthcare from operators deploying Trickbot and Ryuk ransomware. Universal Health Services reported a Ryuk attack that disrupted all U.S. UHS sites for weeks, with similar incidents at hospitals in Oregon and New York. Ryuk typically arrives after Trickbot or BazaLoader infections delivered via malicious email, and operators enumerate networks with PowerShell and WMI before encryption. The Trickbot Anchor_DNS module performs DNS tunneling for C2, using connectivity checks to benign domains like ipinfo.io and checkip.amazonaws.com.

Palo Alto Unit 42·Aug 17, 13:18 UTC · 29d agoRansomware in the wild

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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

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MILE TEA: Cyber Espionage Campaign Targets Asia Pacific Businesses and Government Agencies

Unit 42 names MILE TEA, a cyber-espionage campaign since 2011 targeting Japanese and Taiwanese businesses and government agencies with e-ticket phishing lures and Elirks-family malware.

Unit 42 tracks the MILE TEA espionage campaign, observed as early as 2011, targeting Japanese trading, petroleum, and mobile companies, a Beijing office of a Japanese public organization, and a Taiwanese government agency. The primary infection vector is spear-phishing emails with attachments, mostly custom executable installers posing as flight e-tickets, dropping Elirks, Micrass, or Logedrut as initial bridgehead malware. Elirks and Logedrut retrieve encrypted C2 addresses from attacker-posted blog articles, decoded with Base64 and TEA or DES ciphers. The campaign's focus shifted from Taiwan to Japan around 2013.

Palo Alto Unit 42·Aug 17, 12:56 UTC · 29d agoThreat actor in the wild1

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Studying Image Tokenizers as Visual Languages in Unified Multimodal Models

A controlled pure-autoregressive testbed shows task-specific validation losses rank image tokenizers differently, with I2T loss the most consistent signal.

Researchers built a controlled pure-autoregressive testbed and tracked task-specific validation losses during multimodal continual pretraining across text, image, text-to-image (T2I), and image-to-text (I2T) prediction. They find losses should be analyzed per task because they exhibit distinct scaling behavior and rank tokenizers differently, and that the loss-performance relationship depends on the predicted token space. I2T loss, computed over a shared text vocabulary, correlates consistently with both generation and visual understanding performance after supervised finetuning. Case studies revisit the discriminator, semantic supervision, and vocabulary size as tokenizer design axes.

arXiv cs.AI / cs.LG / cs.CL·Sep 8, 17:57 UTC · 7d agoAI research1

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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 · 29d agoRansomware in the wildCVE-2018-15982CVE-2018-4878CVE-2019-11510+1 CVEs

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Researchers built a $7 gadget for anyone paranoid about hidden cameras in hotel rooms

KAIST-led researchers built SweepLED, a sub-$7 smartphone LED clip using AI to detect hidden cameras with 93.9-95.1% accuracy.

SweepLED, built by KAIST with the National University of Singapore and Singapore Management University, clips 15 LEDs to a smartphone camera and sweeps multi-angle light while the phone films reflections. A spatio-temporal AI model compares LED-on and LED-off frames to distinguish lens reflections from glossy surfaces across three viewpoints. Testing on 30 objects, 12 with hidden cameras, achieved 93.9% accuracy handheld and 95.1% static. Core components cost under $7, targeting privacy checks in hotels and short-term rentals.

Help Net Security·Sep 3, 00:00 UTC · 13d agoResearch1

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UBoatRAT Navigates East Asia

Unit 42 discovers UBoatRAT, a new custom RAT targeting South Korean and video-game industry personnel, delivered via Google Drive with GitHub-based C2 and BITS persistence.

Unit 42 identified UBoatRAT, a new custom remote access trojan first found in May 2017, whose initial version used a public Hong Kong blog service and a compromised Japanese web server for command and control. The latest variants target personnel or organizations related to South Korea or the video games industry, are delivered through Google Drive, and masquerade as Microsoft Word, Excel, or folder icons. The RAT checks for virtualization software and domain join, retrieves its C2 address from a Base64-encoded string in a GitHub-hosted file, uses a custom XOR-encrypted C2 protocol, and maintains persistence via Windows Background Intelligent Transfer Service (BITS) jobs that survive reboots.

Palo Alto Unit 42·Aug 17, 12:55 UTC · 29d agoMalware in the wild1

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Injected and Leaked: Actively Inducing Side-Channel Leakage Using Electromagnetic Injection and Hardware Nonlinearity

Researchers introduce InjectEave, using electromagnetic injection and hardware nonlinearity to induce side-channel leakage and eavesdrop on headphone audio from 30 meters.

An arXiv paper shows electromagnetic injection can actively amplify side-channel leakage: nonlinear hardware such as amplifiers, ADCs, and power converters modulates secret electrical signals onto an injected EM carrier, upconverting low-frequency secrets into measurable EM emissions. By tuning injection frequency and amplitude, an adversary can shape the effective spectrum and entropy of the resulting leakage. The InjectEave attack demonstrated eavesdropping on wired and wireless headphone audio from up to 30 meters and in through-wall scenarios using accessible RF equipment, plus leakage of smart home device power consumption and analog sensor inputs. Case studies show closed-loop eavesdropping and manipulation of landline phone conversations, and the paper discusses mitigations.

arXiv cs.CR·Sep 4, 06:22 UTC · 12d agoResearch

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Tracking Elirks Variants in Japan: Similarities to Previous Attacks

Unit 42 links new Elirks backdoor variants attacking Japanese organizations to 2012 Taiwan attacks, delivered via spear-phishing PDFs exploiting Adobe Flash CVE-2011-0611.

Unit 42 analyzed new Elirks backdoor variants found in an attack on a Japanese business, noting strong similarities to 2012 attacks on Taiwanese ministries. The backdoor retrieves its C2 address from attacker-created accounts on Japanese blog and SNS services. Recent deliveries used an airline e-ticket lure named "E-TKT" with a PDF exploiting Adobe Flash CVE-2011-0611. Shared infrastructure and tactics with the Scarlet Mimic campaign suggest possible ongoing cyber espionage across East Asia.

Palo Alto Unit 42·Aug 17, 12:56 UTC · 29d agoThreat actor in the wildCVE-2011-0611

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AlayaVista: Streaming World Modeling from Panoramic States to Perspective Video

AlayaVista is a camera-controllable streaming video world model that decouples panoramic scene evolution from perspective synthesis, trained on a 1,318-hour 4K dataset.

AlayaVista builds a 360-degree scene prior from a single perspective image, evolves it as a camera-conditioned panoramic latent state, and maps it to perspective video via a latent viewport renderer plus a perspective refiner. Chunk-autoregressive generation and few-step distillation enable efficient streaming. The authors introduce MUGEN, a real-world panoramic video dataset with 1,318 hours of at-least-4K video and rich semantic and geometric annotations.

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

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Upatre Continued to Evolve with new Anti

Unit 42 analyzes an undocumented Upatre downloader variant with VM detection via process hashing, packed code, disabled Windows defenses and Namecoin .bit C2 domains.

Unit 42 analyzed an Upatre downloader variant compiled in December 2016 that went largely undetected by automated systems, featuring heavy code flow obscuration, on-demand decryption of network communications, and novel virtual machine detection. The sample enumerates running processes, computes CRC32 hashes XORed with a hard-coded key, and sleeps if analysis-related processes such as vmtoolsd.exe or python.exe are found. It masquerades with Google Chrome icons, disables Windows Defender, Firewall and other security services, injects code into msiexec.exe, and resolves .bit Namecoin domains like bookreader[.]bit via hardcoded OpenNIC DNS servers over TCP.

Palo Alto Unit 42·Aug 17, 13:23 UTC · 29d agoMalware1

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Quantifying the Engagement Trap: Impact of Short-form Video Recommender Systems on Users with ADHD

A 302-participant study finds engagement-optimized short-form video recommenders cause disproportionate time blindness and distress for users with ADHD.

Researchers ran a stratified Prolific study with 302 participants comparing short-form video recommendation experiences with and without ADHD. Participants with ADHD reported significantly higher time blindness, post-usage regret, and emotional distress despite perceiving recommendations as similarly relevant. The paper proposes neurodiversity-aware, human-centered design interventions to mitigate these algorithmic harms.

arXiv cs.AI / cs.LG / cs.CL·Sep 7, 17:38 UTC · 8d agoAI research

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Cardinal RAT Sins Again, Targets Israeli Fin

Unit 42 documents updated Cardinal RAT attacks against Israeli FinTech firms, using BMP steganography, MD5-hash obfuscation, and process injection to hinder analysis and detection.

Unit 42 tracked a series of attacks using an updated Cardinal RAT (version 1.7.2) targeting the Israeli financial technology sector. The .NET loader hides a second-stage DLL inside an embedded BMP image decrypted with a single-byte XOR key, and the payload renames functions, methods, and variables to MD5 hashes for obfuscation. The malware installs a startup-folder LNK file and injects its final payload into RegSvcs.exe or RegAsm.exe, communicating with affiliatecollective[.]club over port 443. A possible relationship with the EVILNUM JavaScript malware used against similar organizations was also noted.

Palo Alto Unit 42·Aug 17, 12:21 UTC · 29d agoMalware1

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Mask Forcing: Improving Autoregressive Video Diffusion Distillation via Dual-Noise Masking Rollout

Researchers propose Mask Forcing, a dual-noise masking rollout that mitigates mode collapse in autoregressive video diffusion distillation.

The paper targets over-saturation and over-smoothing in autoregressive video diffusion models distilled via Distribution Matching Distillation, attributed to reverse-KL mode-seeking behavior. Mask Forcing perturbs the student self-rollout with random masks along spatial and temporal axes, injecting cleaner tokens that act as denoising guidance for noisier tokens. Experiments show improved visual quality across multiple distillation methods without using real video data or extra post-training stages.

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

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Campaign Evolution: pseudo

Unit 42 traces the pseudo-Darkleech campaign's 2016 shift from Angler to Neutrino to Rig exploit kits and rotating ransomware payloads.

Unit 42 documents how the pseudo-Darkleech exploit kit campaign evolved through 2016, switching from Angler EK to Neutrino EK in June and to Rig EK in September after Neutrino ceased operations. Payloads rotated from TeslaCrypt to CryptXXX, CrypMIC, and finally Cerber ransomware by October 2016. Injected script on compromised websites changed from 12,000-18,000 character obfuscated blocks to short, unobfuscated hidden iframes starting July 1, 2016.

Palo Alto Unit 42·Aug 17, 09:54 UTC · Aug 17, 2026Threat actor in the wild

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Studying Image Tokenizers as Visual Languages in Unified Multimodal Models

A controlled autoregressive testbed shows validation losses must be analyzed per task, and image tokenizer choice affects joint multimodal text modeling.

Researchers built a pure-autoregressive testbed to study image tokenizers as the 'visual language' of unified multimodal models, tracking task-specific validation losses during multimodal continual pretraining across text, image, text-to-image (T2I), and image-to-text (I2T) prediction. They found that losses exhibit distinct scaling behavior per task and rank tokenizers differently, and that I2T loss over a shared text vocabulary gives a more consistent loss–performance signal than T2I loss. Better reconstruction does not necessarily yield lower task-specific losses or stronger downstream performance, and tokenizer choice can affect text modeling under joint optimization. Case studies examine the discriminator, semantic supervision, and vocabulary size design axes.

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

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Malspam Targeting Brazil Continues to Evolve

Brazilian malspam campaigns continue evolving, abusing Google URL shortener and Dropbox and using Squiblydoo plus DLL side-loading to deploy likely infostealing botnet malware.

A June 2017 Brazilian malspam campaign spoofed IPTU tax notification emails, using the recipient's address as the sender, and abused Google's URL shortener and Dropbox to deliver a zip containing a malicious Windows shortcut (.lnk) file. The LNK used the Squiblydoo technique (regsvr32.exe) to download and execute a scriptlet with elevated privileges, retrieving a signed G-Buster Browser Defense executable alongside a malicious fltLib.dll loaded via side-loading, likely an information-stealing botnet. Post-infection HTTP traffic exposed over 400 infected Windows hosts, mostly in Brazil, with 2,132 Banload-tagged samples observed in the first half of 2017.

Palo Alto Unit 42·Aug 17, 09:31 UTC · Aug 17, 2026Malware in the wild

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It's Not RoPE that Creates Sinks: The Role of Self-Concentration and Value-Non-Mixing in Attention

Study shows attention sinks and massive activations stem from causal-mask self-concentration and value-non-mixing rather than RoPE, informing quantization work.

The paper analyzes why attention sinks and massive activations emerge at initial sequence positions regardless of which token occupies them. Experiments attribute both phenomena to self-concentration of attention induced by the causal mask and the subsequent value-non-mixing in attention outputs. The findings provide empirical evidence on LLM internal dynamics and may inform low-bit quantization strategies, which massive activations currently complicate.

arXiv cs.AI / cs.LG / cs.CL·Sep 8, 17:32 UTC · 7d agoAI research

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Tracking OceanLotus’ new Downloader, KerrDown

Unit 42 identifies KerrDown, a new OceanLotus (APT32) downloader active since 2018 targeting Vietnamese speakers via malicious macros and DLL side-loading.

Unit 42 tracks KerrDown, a previously undocumented downloader family used by OceanLotus (APT32) since at least early 2018, primarily targeting Vietnam or Vietnamese-speaking individuals. Delivery uses macro-laced Microsoft Office documents embedding base64-encoded 32-bit and 64-bit DLLs, and RAR archives containing a legitimate program abused for DLL side-loading. KerrDown is dropped as main_background.png, downloads a DES-encrypted payload from a URL, and executes it directly in memory. Researchers used Jaccard-index similarity analysis to identify the new family, connect campaign samples, and infer patterns in the group's working hours and days.

Palo Alto Unit 42·Aug 17, 12:53 UTC · 29d agoMalware in the wild1

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Researchers found a way to hijack devices through Zoom screen sharing

Researchers used a public AI tool to find a Zoom flaw enabling device hijacking via screen sharing in under 20 prompts.

Security researchers discovered a serious vulnerability in Zoom that can be used to hijack devices through the screen-sharing feature. The flaw was reportedly found by a publicly available AI tool in fewer than 20 prompts, highlighting the role of agentic AI in vulnerability discovery. The article does not report active exploitation or assign a CVE in the provided text.

Ars Technica · Security·Aug 12, 13:37 UTC · Aug 12, 2026Vulnerability

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Bisonal Malware Used in Attacks Against Russia and South Korea

Unit 42 details a Bisonal malware variant, active since 2014, targeting Russian and South Korean defense organizations via PDF-disguised spearphishing emails.

In early May, Unit 42 discovered a campaign delivering a Bisonal malware variant against at least one Russian communications security and cryptography company and one unidentified organization in South Korea. The variant, in the wild since at least 2014, introduces a new C2 cipher and rewritten networking and persistence code, with only 14 samples collected to date. Attackers spoofed Russian state corporation Rostec in spearphishing emails carrying an executable disguised with a PDF icon; the dropper decrypts an RC4-encrypted DLL and establishes persistence via a registry Run key. Bisonal has been used since 2013 against government, military, and defense targets in South Korea, Russia, Japan, and India, alongside successors Bioazih and Dexbia.

Palo Alto Unit 42·Aug 17, 12:55 UTC · 29d agoMalware in the wild

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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

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Afraidgate: Major Exploit Kit Campaign Switches from CryptXXX Ransomware Back to Locky

The Afraidgate exploit kit campaign stopped distributing CryptXXX and now delivers the .zepto Locky variant exclusively through Neutrino EK since July 2016.

By mid-July 2016, the Afraidgate campaign switched from CryptXXX ransomware to consistently delivering the .zepto (Zepto) variant of Locky, using the Neutrino exploit kit after Angler EK disappeared in early June 2016. The campaign starts from compromised websites with injected scripts that redirect to Afraidgate domains and then Neutrino EK landing pages on .top domains. Zepto emerged after the Necurs botnet returned from a three-week outage, bringing new anti-sandboxing and evasion techniques.

Palo Alto Unit 42·Aug 17, 09:47 UTC · Aug 17, 2026Ransomware in the wild

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DeCAL: Towards Physically-Grounded Dexterous Vision-Language-Action Models via Contact-Aware Latent Co-Imagination

DeCAL, a contact-aware dexterous vision-language-action model with visuo-tactile fusion, reports 71% average task success.

DeCAL is a physically-grounded dexterous vision-language-action (VLA) model built on a Mixture-of-Transformers architecture with specialized experts for understanding, imagination, and action generation. It introduces Adaptive Visuo-Tactile Fusion with contact-aware gating and Visuo-Tactile Latent Co-Imagination to jointly model visual and tactile dynamics. It reports state-of-the-art results with a 71% average success rate and 83.4% progress success rate, plus generalization to unseen scenarios.

arXiv cs.AI / cs.LG / cs.CL·Sep 8, 17:47 UTC · 7d agoAI research1

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xHunt Campaign: Attacks on Kuwait Shipping and Transportation Organizations

xHunt deployed custom backdoors Hisoka, Killua, Gon, and EYE against Kuwait shipping and transportation organizations, using DNS tunneling and email-draft C2 channels.

Unit 42 observed the xHunt campaign targeting Kuwait transportation and shipping organizations between May and June 2019, installing backdoors named after characters from the anime Hunter x Hunter, including Hisoka, Killua, Sakabota, and Netero. The tools use HTTP and DNS tunneling for C2, and Hisoka v0.9 added an unusual email-based C2 channel that abuses Exchange Web Services with stolen credentials to exchange email drafts. The Gon tool provides port scanning, file transfer, screenshots, remote command execution, and RDP session creation, while EYE acts as a cleanup failsafe if a legitimate user logs in. Related activity targeting Kuwait between July and December 2018 was reported by IBM X-Force IRIS, suggesting the campaigns are likely related.

Palo Alto Unit 42·Aug 17, 13:21 UTC · 29d agoThreat actor1

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Attention-DP3: Spatially Object-aware 3D Diffusion Policy via Geometry-aligned Attentional Conditioning

Attention-DP3 adds spatially object-aware attentional conditioning to 3D diffusion policies, improving robotic manipulation by up to 31% under heavy clutter.

Attention-DP3 injects object-level geometric cues into the unchanged DP3 diffusion policy via Tri-field Attentional Conditioning, using targetness, intra-target saliency, and backgroundness fields. Open-vocabulary 2D segmentation masks are lifted to 3D with calibrated camera geometry to build object-centric priors. Experiments on Adroit, DexArt, MetaWorld, and a real-world SO101 platform show state-of-the-art results, outperforming DP3 by up to 31% under heavy distractor clutter; the code is publicly available on GitHub.

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

15

Analysis of Smoke Loader in New Tsunami Campaign

Fake Japanese Meteorological Agency tsunami warning emails delivered Smoke Loader and AzoRult malware to steal credentials from targets in Japan.

A fake tsunami warning email impersonating Japan's Meteorological Agency asked recipients to click a link on a registered fake agency domain, delivering the commodity loader Smoke Loader to targets in Japan. Smoke Loader, active since 2011, is modular, and its payloads have included banking trojans, ransomware, cryptominers, password stealers, and PoS malware; the campaign later also deployed AzoRult. New samples add junk-jump obfuscation, encrypted network traffic and payload files, a unique machine ID used for tracking and encryption, and PROPagate injection into explorer.exe, with persistence via a Startup folder shortcut and RC4-encrypted C2 communication.

Palo Alto Unit 42·Aug 17, 12:54 UTC · 29d agoMalware in the wild

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TransNormal-2: Geometry-Grounded Rectified Flow with Edge-Aware Decoding for Precise Normal Estimation

TransNormal-2 improves monocular surface-normal estimation by fixing VAE edge degradation with geometry-aware losses and refinement, matching MoGe-2 with 1.4% of annotations.

TransNormal-2 is a FLUX.2-based rectified-flow framework for monocular surface-normal estimation with single-step deterministic inference. The authors quantify that VAE 8x spatial compression introduces 1.3-8.5 degrees of mean angular error even on ground-truth normals, with edge error up to 2.8x the global error. The method adds geometry-aware pixel-space losses and an RGB-guided Geometric Refinement Module to correct boundary-localized decoding errors. It matches or exceeds MoGe-2 on all eight reported metrics using only 1.4% as many task-specific annotations, and cuts transparent-object MAE by 4.2 degrees on ClearGrasp and 3.1 degrees on ClearPose.

Hugging Face daily papers·Sep 5, 20:00 UTC · 10d agoAI research

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The Fractured Block Campaign: CARROTBAT Used to Deliver Malware Targeting Southeast Asia

Unit 42 uncovers the Fractured Block campaign using the CARROTBAT dropper to deliver SYSCON and OceanSalt malware in cryptocurrency-themed attacks across Southeast Asia.

Unit 42 identified 29 CARROTBAT dropper samples used in the Fractured Block campaign, delivering decoy documents on cryptocurrencies, exchanges, and Korean political topics. Early samples delivered the SYSCON RAT, which uses FTP for command and control, while later ones dropped the previously reported OceanSalt malware. CARROTBAT supports 11 decoy file formats and uses certutil to download and execute payloads. Initial discovery stemmed from a December 2017 spear phishing attack on a British government agency, with infrastructure overlap tying the campaign to KONNI activity.

Palo Alto Unit 42·Aug 17, 12:22 UTC · 29d agoMalware

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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·Sep 3, 20:00 UTC · 12d agoAI research

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RANCOR: Targeted Attacks in South East Asia Using PLAINTEE and DDKONG Malware Families

Unit 42 names RANCOR, a previously unidentified espionage group targeting Southeast Asian political entities with newly discovered PLAINTEE and DDKONG malware families.

Unit 42 tracks a previously unidentified group it dubs RANCOR conducting highly targeted espionage attacks in Singapore and Cambodia using two custom malware families, DDKONG and PLAINTEE. Attacks appear to have begun with spear phishing, with decoy political news documents hosted on legitimate sites including a Cambodian government website and Facebook. Infrastructure links to IP 89.46.222[.]97 and KHRAT-associated domains such as facebook-apps[.]com, and the activity is grouped into two clusters tied together by PLAINTEE usage and similar targeting.

Palo Alto Unit 42·Aug 17, 13:24 UTC · 29d agoThreat actor1

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The Attention Triangle in Audio-Video Models

Researchers analyze the 'attention triangle' in audio-video diffusion models, showing bias-driven cross-attention routing causes semantic leakage and proposing inference-time interventions that improve grounding.

A study probes the three cross-attention edges linking text, audio, and video streams in audio-video diffusion models. It finds the audio-video edge is bidirectional and shaped by parameter-encoded biases, so prompts in tension with learned priors can be overridden, producing visually canonical but incorrect outputs. Attention-derived signals are used as diagnostics and to guide inference-time interventions that improve cross-modal semantic grounding while preserving generation quality.

Hugging Face daily papers·Sep 2, 20:00 UTC · 13d agoAI research

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