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19 Chrome and Edge Extensions Found With Wallet-Stealing and Crypto

Socket found 19 malicious Chrome and Edge extensions, active since February 2024, stealing wallet seed phrases and credentials and draining crypto from about 80,000 users.

Socket researcher Karlo Zanki documented a cluster of 18 Chrome and one Edge extensions with wallet secret stealing and cryptocurrency draining capabilities, tracked as campaign Superior and possibly active since February 2024. The actor created 14 extensions and bought five legitimate ones, later pushing malicious updates; the largest, Enable Right Click & Copy, has roughly 80,000 installs across both browsers. The extensions maintain WebSocket C2 connections with endpoint rotation, strip CSP headers, and load 16 modules including multi-chain wallet drainers, hardware-wallet seed-phrase harvesters, credential grabbers, and ClickFix-style lures.

The Hacker News · 18d agoMalware in the wild

Edge infrastructure under siege: what two independent datasets reveal about who's exploiting your perimeter

Joint Tenable-SentinelOne analysis of 93 CVE-actor attribution pairs shows nation-state and criminal groups independently converge on the same edge infrastructure.

Tenable and SentinelOne jointly analyzed 93 CVE-actor attribution pairs covering exploitation of perimeter devices. The data shows state-sponsored and financially motivated actors independently target the same edge products from Ivanti, Fortinet, and Palo Alto Networks. The findings challenge the narrative that edge exploitation is exclusively a China-nexus nation-state problem, showing a broader shared attack surface.

Tenable Blog · 21d agoThreat actor in the wild

Five Eyes Guidance Improve Edge

Five Eyes intelligence agencies issued joint guidance aimed at improving security of edge network devices.

Based on the headline, Five Eyes cyber agencies released guidance recommending organizations improve the security posture of edge devices such as routers and remote-access appliances. No article text is available, so specific recommendations are unavailable.

Infosecurity Magazine · 28d agoAdvisory

Vulnerabilities fixed in libxml2-2.15.4

libxml2 2.15.4 fixes an out-of-bounds read in xmlregexp's NXT macro plus several integer overflow and parsing flaws.

libxml2 2.15.4 (released September 1, 2026) includes security fixes: an out-of-bounds read in the xmlregexp NXT macro, missing overflow checks in dict.c, uri.c, and valid.c, an integer overflow in xmlIO before the writecallback, and an overflow check in xmlXPtrEvalXPtrPart. The release also propagates parseFlags in xmlXIncludeProcess and xmlXIncludeProcessTree. No CVE identifiers, exploitation, or severity ratings are given in the announcement.

oss-security · 11d agoVulnerability

PEEP Turns Chrome and Edge Into Post-Compromise Backdoors for Host Command Execution

SOCRadar disclosed PEEP, a post-exploitation Chromium extension toolkit that turns Chrome and Edge into host-level backdoors via native messaging and C2 polling.

SOCRadar researchers detailed PEEP, a Chromium-based post-exploitation toolkit masquerading as a 'Smart Bookmarks' extension injected directly into Chrome and Edge profiles by forging Secure Preferences integrity values, bypassing Web Store checks. A native-messaging host binary (nm_host.exe) extends the browser agent to host-level command execution, file management, credential theft, and session hijacking, while the extension polls C2 endpoints at 206.237.30.232 or xfjcc.fun every 30 seconds over plaintext HTTP and exfiltrates browsing history, cookies, and tab metadata. PEEP is derived from the open-source RedExt red teaming framework, adds PowerShell persistence scripts, and includes a Linux-targeting Python script, suggesting cross-platform intent. The activity is unattributed but contains Chinese-language artifacts; a C2 /health endpoint showed 34 agent entries and 10 active sessions.

The Hacker News · 8d agoMalware in the wild

Secure Access Service Edge (SASE) Archives

Palo Alto Unit 42 archive page describing Secure Access Service Edge (SASE), a cloud architecture unifying SD-WAN with SWG, CASB, FWaaS and ZTNA services.

Category archive page defining SASE as a cloud-native architecture that converges SD-WAN with security functions such as SWG, CASB, FWaaS and ZTNA into one cloud service. It frames SASE as a shift from separate networking and security disciplines to unified, cloud-delivered security and connectivity. The page contains no news, incident, vulnerability or research findings.

Palo Alto Unit 42 · Aug 17, 2026Industry

Graph Machine: Towards Better Pretraining via Edges

Researchers propose Graph Machine, an O(n)-state sparse architecture that replaces 75% of Qwen3-0.6B dense layers with only slight loss change.

The paper introduces the Graph Machine (GM), an architecture that maintains an O(n)-sized state accessed through sparse, dynamic routing via pointer-like edges updated differentiably by a referral mechanism resembling pointer chasing. The authors replaced 75% of dense Transformer layers in Qwen3-0.6B with GM sparse layers and pretrained from scratch on 15.7B tokens. Retrieving 2 of 4,096 tokens per KV head in each sparse layer degrades loss only slightly, while retrieving 4 marginally improves loss over the dense baseline.

Hugging Face daily papers · 14d agoAI research

[local] Microsoft Edge 150.0.4078.48 - RCE

Exploit-DB publishes a local remote code execution exploit for Microsoft Edge 150.0.4078.48.

A public exploit demonstrates remote code execution in Microsoft Edge version 150.0.4078.48, listed under the local category on Exploit-DB. Successful exploitation could allow arbitrary code execution in the context of the browser. Users should update to the latest patched Edge release.

Exploit-DB · Aug 10, 2026Exploit / PoC

CoVeR: Coverage-Based Token Pruning for Multi-View 3D Reasoning in VLMs

CoVeR, a training-free coverage-based token pruner, preserves 93.5% of VLM 3D-reasoning performance using only about 8% of visual tokens.

Researchers introduce CoVeR, a deterministic, training-free selector that chooses visual tokens to cover every region of a multi-view 3D scene using only token coordinates. Unlike learned-importance and voxelization pruners, it enforces an exact per-scene token budget, avoids saturation plateaus, and prevents near-duplicate selections. Experiments across four vision-language models show it surpasses prior state of the art by 3.9 percentage points on average across three 3D reasoning benchmarks.

Hugging Face daily papers · 8d agoAI research

ENEAS: Embedding-guided Neural Ensemble for Adaptive Segmentation

ENEAS adds text prompting and semantic verification to video segmentation to keep tracking targets through occlusion and reject lookalike distractors.

ENEAS is a unified text-promptable method for instance tracking and open-concept semantic discovery in video, designed to fix temporal hallucinations, spatial fragmentation, and semantic misclassification seen in SAM 3-class foundation models. It extends the geometrically robust SeC architecture with a text-prompting adapter and temporal memory, and uses a verification layer combining fast visual embedding matching with conditional VLM refinement for ambiguous candidates. It targets 3D reconstruction pipelines where a single misclassified distractor corrupts the asset. Code and models are open-sourced.

Hugging Face daily papers · 13d agoAI research

What Breaks Under Pruning in Smart Homes, and When? Evaluating LLM Degradation Across Architectures and Task Complexity

Pruning study across four LLM architectures finds dense models degrade sharply on smart-home tool calling while MoE models tolerate far more.

Researchers systematically study pruning-induced degradation in smart-home tool calling across four LLMs spanning dense Transformer, dense hybrid, and mixture-of-experts architectures, combining depth, width, hybrid, and expert pruning methods, and evaluate over 19,500 instances from three datasets after post-pruning supervised fine-tuning. Dense models show narrow safe pruning regions followed by sharp degradation, while MoE models tolerate substantially more pruning. Pruning degrades grounded specificity (operation, device, argument, value) before schema-level intent, and aggressive dense pruning can induce systematic over-refusal.

arXiv cs.AI / cs.LG / cs.CL · 19h agoAI research

Technical Manual for a Toolkit for Measuring Contextual Individuation in Transformer Language Models

An open methodology toolkit measures whether transformer language models contextualize fixed word forms across domains using bridge forms and layer-wise silhouette analysis.

The manual documents an open toolkit built around 'bridge forms' - identical written words recurring across two or more subject domains with a different sense in each - to test whether transformer language models individuate word occurrences by context beyond the embedding layer. It covers declarative specification of bridge forms, Wikipedia corpus acquisition, occurrence localization, layer-wise representation extraction, domain-pairwise silhouette measurement, and visualization, justifying each choice against failure modes such as sense contamination and subword-tokenization misalignment. It is a methodological and implementation reference and reports no empirical results.

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

Augustinian BabyLM: What Ostensive Definition Can and Cannot Teach a Small Language Model

Study shows visually grounded token embeddings in a small masked LM persist through training and improve object-property knowledge, but escape standard BabyLM benchmarks.

The paper implements ostensive definition for a small DeBERTa masked language model trained on 10M words, seeding visually grounded tokens with embeddings derived from labeled image regions before training. Visual initialization leaves a persistent, seed-replicated advantage on object-property knowledge (COMPS) and a corpus-tailored Visual-Property Swap benchmark covering color, material, size, and shape, but has no effect on most BabyLM grammar benchmarks. Synthetic grounding of previously unseeded words causally transfers the advantage to exactly those words.

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

LimiX-2: A Contextual Mechanism Network Towards General Structured-Data Intelligence

LimiX-2 scales Contextual Mechanism Networks pretrained via context-conditional masked modeling, beating tabular foundation models on TabArena, TALENT, and BCCO benchmarks.

LimiX-2 is a new tabular model in the LimiX family, developed through model and data scaling guided by previously established scaling laws under the Contextual Mechanism Networks (CMNs) paradigm. It is pretrained with Context-Conditional Masked Modeling (CCMM) on synthetic datasets generated by structural causal models spanning diverse graph structures, functional mechanisms, and observation processes. It outperforms dataset-specific models and tabular foundation models on TabArena, TALENT, and BCCO, and its feature attention encodes direct causal relationships, enabling accurate causal skeleton recovery.

arXiv cs.AI / cs.LG / cs.CL · 19h agoAI research1

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 · 11d agoAI research

[webapps] Ray 2.56.0 - Directory Traversal & Local File Inclusion

Public exploit released for directory traversal and local file inclusion in Ray 2.56.0, the widely used distributed ML framework.

Exploit-DB entry 52635 publishes a web application exploit targeting Ray 2.56.0, the distributed computing framework from Anyscale commonly used for ML workloads. The PoC demonstrates a directory traversal and local file inclusion condition, allowing attackers to read files outside the intended path on an exposed Ray instance. Ray dashboard instances exposed to the internet could leak sensitive files such as credentials and configuration.

Exploit-DB · Aug 11, 2026Exploit / PoC

Xen Security Advisory 513 v3 (CVE-2026-79605,CVE-2026-79606) - Out-of-bounds accesses in Tapdisk

Xen published XSA-513 (CVE-2026-79605 and CVE-2026-79606): incorrect bounds checks in Tapdisk, the XAPI toolstack userspace xen-blkback, allow out-of-bounds accesses.

The Xen security team released XSA-513 version 3 as a public release, covering CVE-2026-79605 and CVE-2026-79606, out-of-bounds access flaws in Tapdisk. Tapdisk is the userspace xen-blkback implementation used by the XAPI toolstack. Several bounds checks were found to be incorrect, including a missing upper bounds check. The advisory was updated to version 3 for public release.

The extension you never installed: KREMLIN forges Chrome's own integrity checks to steal banking sessions

Elastic details KREMLIN, a Brazilian banking malware whose malicious Chrome/Edge extension forges Chromium integrity checks to steal sessions.

Elastic Security Labs tracked operation REF9334 and its KREMLIN toolkit, a Brazilian banking malware campaign impersonating twelve banks across seven campaigns since May 2025. The infection chain uses multi-stage obfuscated JavaScript loaders with sandbox checks (file and process counting), scheduled-task persistence, and an Ethereum smart contract acting as a dead-drop resolver for C2 and payload URLs, abusing Archive.org for hosting. The malicious browser extension bypasses Chromium integrity mechanisms by manipulating Secure Preferences and regenerating required HMACs and App-Bound encrypted hashes. Threat Command disrupted over 1,500 infections by registering the kill-switch canary domain.

Elastic Security Labs · 2d agoMalware in the wild

Decomposition Buys Integrity, Not Yield

Study of 600 production deep-research traces finds agent-tree decomposition loses findings at rate N^(1-δ); flat architectures maximize yield.

The paper models multi-agent decomposition as a tree where an agent holding b items retains each with probability r(b); with r(b)=1/b every tree delivers exactly one finding regardless of shape. Analysis of 600 production deep-research traces estimates delta=0.34 retention decay, and 1,012 annotated traces show one brief in sixteen goes off-target per tier, giving an alignment penalty of 0.536. Depth still cuts root context exposure from N to N^(1/k) and is cheaper at scale, with a hazard model over 743,819 production tool calls showing delegation is an opening move rather than a response to filling context.

arXiv cs.AI / cs.LG / cs.CL · 20h agoAI research

Generative Late-Interaction Embeddings For Visual Document Retrieval

GLIE compresses visual document retrieval embeddings to four vectors per page while retaining nearly 80% of uncompressed nDCG@5 accuracy.

Researchers analyzing late-interaction retrieval embeddings found they lie exactly on the unit sphere and concentrate near a manifold of intrinsic dimension five to six. GLIE learns a few k vectors per page that serve as a lightweight index and a basis to regenerate the full embedding set for exact rescoring of top candidates at query time. On ViDoRe v1 with four vectors per page, GLIE retains nearly 80% of uncompressed nDCG@5 versus 70% for the best prior post-hoc method, using a 415K-parameter network trained in under three GPU-minutes on 1,000 pages.

Hugging Face daily papers · 6d agoAI research

Perplexity Details Its GPU Embedding Stack: How Ivy, Tulip and ROSE Serve pplx-embed

Perplexity details its GPU embedding serving stack (Ivy, Tulip, ROSE), which reuses LLM prefill/decode kernels, CUDA graphs, and LazyTensors to cut launch overhead.

Perplexity engineers published a deep dive on the serving infrastructure behind pplx-embed, used across Perplexity Search and its API platform. The stack comprises Ivy (Rust HTTP gateway), Tulip (gRPC scheduling and batching), and ROSE (Runtime-Optimized Serving Engine), which reuses LLM prefill and decode kernels rather than running a separate embedding engine. Optimizations include whole-model CUDA graphs with lazy capture and a LazyTensor abstraction that overlaps CPU batch preparation with in-flight GPU work. Benchmarks are reported against vLLM v0.22.0 in BF16, with FlashAttention 4 generally fastest but FlashInfer 3 winning on Qwen-based models at very long sequence lengths.

MarkTechPost · 10d agoAI tools & infra1

12 Best Enterprise Browsers Compared (2026): Features & Pricing

2026 comparison of twelve enterprise browsers ranks Island and Palo Alto Talon as purpose-built leaders, with Chrome Enterprise and Edge free or bundled.

Guide compares twelve enterprise browser options across three models: purpose-built secure browsers (Island, Talon, Surf), layered controls on existing browsers (Chrome Enterprise, Edge for Business, LayerX, Seraphic), and streamed/isolated browsers (Kasm). Island and Palo Alto's Prisma Access Browser lead the purpose-built category for BYOD and contractor DLP. It also notes Mammoth Cyber has ceased operations.

GBHackers · 1d agoTools

Prisma SASE Archives

Palo Alto Unit 42 archive page describing Prisma SASE, which converges network security, SD-WAN and Autonomous Digital Experience Management in one service.

Vendor category page describing Prisma SASE as Palo Alto Networks' Secure Access Service Edge offering, combining network security, SD-WAN and Autonomous Digital Experience Management in a single service. The page contains no news, incident, vulnerability or research content.

Palo Alto Unit 42 · Aug 17, 2026Industry

Context Engineering Inside the Harness: 4 Mechanisms That Beat Context Overflow and Goal Loss on Long-Horizon Tasks

Survey of four harness mechanisms—context budgeting, compaction, todo-state, and memory—that keep long-horizon LLM agents on task across 200+ tool calls.

The article details how agent harnesses, not larger context windows, solve context overflow and goal loss on long-horizon tasks, citing Chroma's Context Rot report showing 18 LLMs (GPT-4.1, Claude 4, Gemini 2.5, Qwen3) degrade on long inputs. Concrete implementations include LangChain Deep Agents offloading tool responses over 20,000 tokens to the filesystem and truncating old tool calls at 85% window usage, and Claude Code capping auto memory at 25KB while re-reading the 5 most recently modified files after compaction. OpenAI's Responses API now offers server-side compaction via context_management with a standalone /responses/compact endpoint, which Codex uses for long-running coding tasks. Manus reports a roughly 100:1 input-to-output token ratio per ~50-tool-call task, motivating todo.md state recitation to prevent goal drift.

MarkTechPost · 3d agoAI research1

[dos] Nmap 7.99 - Extension Header Integer Underflow

A proof-of-concept denial-of-service exploit for Nmap 7.99 leverages an integer underflow in extension header parsing to crash the scanner.

Exploit-DB lists a denial-of-service proof of concept targeting Nmap version 7.99. The flaw is an integer underflow when handling extension headers, which can crash the scanner. No exploitation in the wild or patch details are mentioned in the listing.

Exploit-DB · Aug 17, 2026Exploit / PoC1

Everything in Moderation: Per-Domain Coverage Optima and Alignment-Resistant Domain Gaps in Multi-Domain Mid-Training

Controlled mid-training experiments on Qwen3-8B-Base find each domain has a 10-40% coverage optimum and domain gaps survive alignment SFT.

Using Qwen3-8B-Base (with a 4B replication) across five semantically rule-disjoint KOR-Bench domains, the authors train 30 data allocations spanning the five-domain simplex at five seeds each. All five domains show interior optima in the moderate 10-40% coverage band, and domain gaps persist after a fixed-budget compensatory SFT pass, which raises 116/120 cells yet bridges 0/240 pairs at a 5% threshold. Zero coverage collapses mid-training-only accuracy, though a FineWeb-Edu-only control shows the collapse is partly generic drift. The results argue mid-training data composition requires principled design rather than reliance on later alignment.

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

[webapps] Langflow 1.8.4 - Path Traversal to Remote Code Execution

A path traversal to remote code execution exploit for Langflow 1.8.4, a popular LLM application builder, was published on Exploit-DB.

Exploit-DB lists a proof-of-concept exploit chaining path traversal to remote code execution in Langflow 1.8.4, an open-source tool used to build LLM applications and agents. The chain allows an attacker to write arbitrary files outside the intended directory and achieve code execution on the host. The provided text does not include a CVE identifier or reports of exploitation in the wild, but RCE in a widely deployed AI tooling product is notable for defenders.

Exploit-DB · 16d agoExploit / PoC1

How to secure edge AI in customer-owned environments

Microsoft outlines security architecture guidance for edge AI, urging runtime attestation, artifact provenance, and deterministic mediation of model actions.

Microsoft details how edge AI shifts trust responsibilities to customers operating their own infrastructure, where prompt injection, model tampering, and malicious firmware updates can occur alongside model weights, credentials, and physical-system access. The guidance recommends verifying runtimes with attestation, verifying AI artifacts with provenance, and constraining model actions through a deterministic mediator outside the model. It also covers new exposure surfaces from MCP, multi-agent systems, and computer-use agents running in disconnected or hostile edge environments.

Microsoft Security Blog · 11d agoAI safety & security

PEEP: A Browser RAT Posing as a Chrome Extension

SOCRadar's STRU analyzed PEEP, an emerging Chromium-based RAT disguised as a Chrome extension enabling post-exploitation control of browsers.

SOCRadar's Threat Research Unit (STRU) identified and analyzed PEEP, a Chromium-based post-exploitation toolkit distributed as a browser extension. PEEP provides RAT-style capabilities while posing as a legitimate Chrome extension. It is assessed as an emerging threat worth monitoring by defenders.

SOCRadar · 12d agoMalware

Tables Decoded: DELTA for Structure, TARQA for Understanding

DELTA extracts tables into compact OTSL text and TARQA fine-tunes LLMs on it, beating VLM baselines on table QA.

DELTA separates physical structure recognition, logical structure recognition, and OCR to output tables in Optimised Table Structure Language (OTSL), a compact unified format encoding cell arrangements and content. It achieves TEDS-Structure scores comparable to state-of-the-art methods across FinTabNet, PubTabNet, and PubTables-1M, with robustness tested on a curated Hindi benchmark, TORQUE. TARQA, an LLM fine-tuned on OTSL sequences, gains 9.3 percentage points on WTQ TabQA and 9.2 points on FinTabNetQA TabVQA; code, models, and the benchmark are released on GitHub.

arXiv cs.AI / cs.LG / cs.CL · 20h agoAI research