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CategoryAll Industry 162 Vulnerability 138 Malware 128 Ransomware 79 Policy & legal 69 AI industry 61 AI tools & infra 48 Data breach 41 Exploit / PoC 37 Threat actor 31 Tools 23 Phishing & fraud 17 AI research 10 Research 9

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Linux Detection Engineering - Local Privilege Escalation

Elastic details a layered detection framework for Linux local privilege escalation, covering 2026's copy-on-write bug wave and LLM-assisted discovery.

Elastic Security Labs describes how most Linux local privilege escalations share a common host flow — an unprivileged process launched from a writable path becoming root — and proposes layered detections combining general outcome-based rules with per-technique rules in Elastic Defend and Auditd. It tracks 13 recent LPE disclosures, seven of which share a copy-on-write/zero-copy bug class, including Copy Fail, DirtyFrag, Fragnesia, DirtyDecrypt, DirtyClone, pedit COW, and RefluXFS. Qualys attributes RefluXFS to an LLM-assisted research effort with Anthropic using Claude Mythos Preview, and another bug is credited to an LLM-assisted workflow. Detection and endpoint rules are published in Elastic's detection-rules and protections-artifacts repositories.

Elastic Security LabsSep 11, 00:00 UTC · 5d agoResearch

From 88 lines to 1: Detecting DLL hijacking with Elastic Defend

Elastic condenses 88 lines of detection logic into one Elastic Defend 9.5.0 rule catching the DLL hijacking used by a ClickFix campaign.

The ClickFix campaign side-loads a malicious mscoree.dll next to a signed Microsoft binary and also ships a driver to kill Elastic Endpoint. Elastic rebuilt the DLL as a NativeAOT library, dropped it beside the signed binary, and confirmed that Elastic Defend 9.5.0 flags the load. The post replaces 88 lines of detection logic with a single rule for DLL search-order hijacking.

Elastic Security LabsAug 28, 00:00 UTC · 19d agoTools in the wild

Inside Elastic's agentic SOC: How we took AI alert triage from 60% to 92% accuracy

Elastic's InfoSec team raised AI alert-triage accuracy from 60% to 92% using three self-correcting agents integrated into Slack triage.

Elastic's InfoSec team deployed three AI agents that read detection-rule investigation guides and closure reasons from 30 days of historical cases to triage alerts. The agentic pipeline lifted triage accuracy from 60% to 92%. Analysts now clear most alerts with a single click in Slack.

Elastic Security LabsAug 25, 00:00 UTC · 22d agoTools

How a team of entity maintainers monitors, connects and scores entities in Elastic Security

Elastic Security explains how background 'maintainer' jobs build user, host and service entities from raw logs and drive identity resolution and risk scoring.

Elastic Security Labs describes the internal background jobs, called maintainers, that each own one piece of every user, host and service record in Elastic Security. The maintainers construct entities from raw logs, resolve identities across sources and compute risk scores, and the write-up explains how the team keeps this entity machinery consistent.

Elastic Security LabsAug 24, 00:00 UTC · 23d agoTools

Elastic Defend now covers 800+ vulnerable drivers, with automated troubleshooting and ARM support

Help Net SecurityAug 3, 00:00 UTC · Aug 3, 2026Ransomware

13 million tool calls: auditing every AI coding agent action with Elastic Agent

Elastic Security Labs shows how Cursor hooks plus Elastic Agent turn AI coding agent activity into 13 million huntable security events.

Elastic Security Labs demonstrates auditing AI coding agent behavior by pairing Cursor hooks with Elastic Agent, capturing every tool call, shell command, file read, and MCP request as structured events. The dataset of 13 million captured events can be hunted with ES|QL, giving defenders visibility into agent actions.

Elastic Security LabsAug 11, 00:00 UTC · Aug 11, 2026AI safety & security1

Linux Detection Engineering - Fileless Execution

Elastic Security Labs reproduces five Linux fileless execution patterns, including memfd_create staging and in-memory kernel module loads, and maps each to Elastic Defend rules.

Elastic Security Labs reproduced five Linux fileless execution patterns using its FENIX tooling: memfd_create staging, interpreter one-liners, deleted binaries, and in-memory kernel module loads. Each pattern is mapped to the Elastic Defend detection rules that catch it. The post is part of the team's ongoing Linux detection engineering series.

Elastic Security LabsSep 1, 14:26 UTC · 14d agoResearch

Data access: the hidden cost of security vendor lock-in

Elastic compares SIEM data egress cost, latency, and fidelity across CrowdStrike, Microsoft, Google, and Splunk, arguing vendors engineer lock-in.

Elastic Security Labs published an opinion piece comparing how major SIEM and security vendors handle data egress, based on each vendor's public documentation as of September 2026. It rates CrowdStrike Falcon Data Replicator and Palo Alto Networks XSIAM Event Forwarding as restricted (paid add-ons with batch delays), Microsoft as partially open, Splunk as open, and Elastic as open with no export license. The piece argues frictionless ingestion paired with licensed or delayed egress is an intentional lock-in business model, and cites CrowdStrike's 2026 Global Threat Report eCrime breakout time of 29 minutes to argue real-time telemetry access is now essential.

Elastic Security LabsSep 4, 00:00 UTC · 12d agoIndustry

Four REVSTEALER-Linked Modules Disable Windows Update and Defender to Run a Crypto Miner

Elastic documents four persistent REVSTEALER-linked tools (ProManager, WinUpdate, SoftManager, LockAppHost); LockAppHost disables Windows Update and Defender to run a crypto miner.

Elastic Security Labs identified four previously unreported executables tied to REVSTEALER, a commercial Windows infostealer sold since at least February 2026: ProManager, WinUpdate, SoftManager, and LockAppHost. LockAppHost abuses CMSTP for elevation, adds Microsoft Defender exclusions, disables five Windows Update services and 13 scheduled tasks, then hides a miner in legitimate Windows processes; other modules steal wallets, clipboard-swap crypto addresses, and turn victims into reverse proxies. The components share REVSTEALER tradecraft including packer, runtime function resolution, and Polygon smart-contract backup configuration (EtherHiding). Elastic's detection rule matched about 4,700 VirusTotal samples over the past year; distribution uses hijacked YouTube channels promoting game cheats and a fake 'Claude Opus 5 Free Desktop' app.

The Hacker NewsSep 6, 08:34 UTC · 10d agoMalware in the wild

How to correlate Kubernetes audit logs with container runtime data

Elastic Security Labs shows how to join Kubernetes audit logs with Defend for Containers runtime data to investigate service account abuse and container escapes.

Elastic Security Labs demonstrates correlating Kubernetes audit logs with Defend for Containers (D4C) runtime telemetry in Elastic. In an Amazon EKS lab, a compromised workload service account performed discovery, read secrets, minted a token, created a privileged pod, and execed into it to attempt a container escape via nsenter and chroot. The escape wrappers appeared only in the decoded Kubernetes audit requestURI, not in runtime process events. The post covers join fields, prebuilt EQL sequence rules, and continues the control-plane correlation thread from the TeamPCP container attack scenario and the Hugging Face intrusion write-up.

Elastic Security LabsSep 3, 15:19 UTC · 12d agoResearch1

REVSTEALER ramps up: analysis of up-and-coming infostealer

Elastic Security Labs analyzes REVSTEALER, an emerging infostealer harvesting browser credentials, cryptocurrency wallets, and gaming accounts.

Elastic Security Labs published a deep-dive analysis of REVSTEALER, described as an up-and-coming infostealer. The malware targets browser data, cryptocurrency wallets, and gaming accounts, with credential harvesting as its core function. The report tracks the family's capabilities as it ramps up activity in the wild.

Elastic Security LabsSep 2, 00:00 UTC · 14d agoMalware in the wild

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

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

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

Elastic Security LabsSep 8, 21:00 UTC · 7d agoIndustry

Update modules/auxiliary/scanner/http/elasticsearch_tika_xfa_xxe.rb

Rapid7 updated a Metasploit auxiliary scanner module that detects XML external entity injection in Elasticsearch via Apache Tika.

A commit in the Metasploit Framework updated modules/auxiliary/scanner/http/elasticsearch_tika_xfa_xxe.rb, an auxiliary scanner module. The module targets XML external entity (XXE) injection in Elasticsearch through Apache Tika, and was co-authored by jheysel-r7. The terse commit message contains no additional details, CVE references, or exploitation notes.

Metasploit Framework commitsSep 8, 19:22 UTC · 7d agoTools

You Can't Prefer Emotions You Don't Sample: Intensity Undershoot in DPO-Tuned LLMs

Study quantifies DPO-tuned LLMs undershooting requested emotional intensity, tracing the gap to candidate-pool extremity rather than conditioning format.

Conditioning an instruction-tuned LLM on continuous valence-arousal targets yields gain of only 0.26 for valence and 0.13 for arousal on Llama-3.1-8B, far below faithful control of 1.0. The authors attribute undershoot to neutral-heavy preference corpora like EmoBank and candidate pools lacking extreme affect, leaving DPO without extreme exemplars. Uniform target coverage with a hotter candidate pool raises valence gain to 0.40 on Llama-3.1-8B and 0.44 on Qwen3-8B, with modest in-distribution cost; arousal gains remain unstable across seeds.

arXiv cs.AI / cs.LG / cs.CLSep 7, 17:47 UTC · 8d agoAI research

KREMLIN Banking Malware Bypasses Chrome Security to Steal Banking Sessions

Elastic Security Labs details KREMLIN, a Brazilian banking malware that implants malicious Chrome and Edge extensions by forging Chromium integrity values to steal banking sessions.

Elastic Security Labs tracks the KREMLIN banking malware operation as REF9334, active since at least May 2025 across seven campaigns primarily targeting 12 Brazilian banks. The malware is installed by a victim-run JavaScript loader, achieves scheduled-task persistence, and side-loads a malicious DLL via SentinelOne's SentinelMemoryScanner.exe. It modifies Chrome and Edge Secure Preferences files, enables developer mode, and regenerates Chromium MAC values to silently install extensions, while extracting browser encryption material including the newer App-Bound OSCrypt key. An Ethereum smart contract serves as a dead-drop resolver for C2 config; Elastic disrupted over 1,500 infections via a canary domain.

GBHackers05:33 UTC · 5h agoMalware in the wild 2 sources

Molecular Déjà Vu: Digit-Level Retrieval of Published Values in Frontier Language Models

Audit of 22 frontier models finds widespread verbatim retrieval of published molecular property values, with higher reasoning increasing recall of memorized numbers.

An arXiv audit tests 22 frontier LLMs across 12 molecular regression benchmarks for verbatim retrieval of published values. More than 50% of the LLMs show verbatim retrieval on five datasets, and identical experiments are flagged 89% more often at a high reasoning level than at the lowest one. Suppressing retrieval moves model prediction errors closer together in relative terms, suggesting predictive capability is not determined solely by memorized values.

arXiv cs.AI / cs.LG / cs.CLSep 4, 17:32 UTC · 11d agoAI research1

Cadence: Error-Bounded Lossy Compression of Demand Time Series with a Time-Series Foundation Model

Cadence pairs Google's 330M-parameter TimesFM-3 foundation model with adaptive arithmetic coding, gaining 13-28% on 2026 demand series over classical predictors.

Cadence is an error-bounded lossy compressor for numeric time series combining the 330M-parameter Google TimesFM-3 foundation model with an adaptive arithmetic coder, guaranteeing a per-sample error bound. On 49 EIA-930 balancing-authority demand series from 2026 it gains 13.3% over the best of six classical predictors and 28.3% on 50 MTA ridership series, winning all 297 series-tolerance pairs with a 21.4% median gain. The paper also reports negative results, including that foundation models add negligible value for lossless coding and that PyTorch predictions are not bit-identical across batch sizes.

Hugging Face daily papersSep 4, 20:00 UTC · 11d agoAI research1

Cybersecurity jobs available right now: August 18, 2026

Help Net Security lists current cybersecurity job openings at ADI Global Distribution, Schneider Electric, L'Oreal, GovCIO, Elastic, and others across multiple countries.

A recurring job roundup featuring roles such as CISO at ADI Global Distribution, Cybersecurity Analyst at Schneider Electric in India, Cybersecurity Architect at L'Oreal in France, and security engineering positions at GovCIO, Neros Technologies, Elastic, and Chamelio. Most listed positions are no longer accepting applications; several emphasize AI-enabled security environments and identity threat detection and response. No vulnerability, incident, or research content is included.

Help Net Securityupdated Sep 14, 22:15 UTC · 1d agofirst Sep 9, 12:47 UTC · 6d agoIndustry 6 sources

Fortunate Recall: Ontology-Driven Memory Lifecycle Management for Persistent Coherence in LLMs

Fortunate Recall introduces ontology-based lifecycle policies for LLM memory, cutting confabulation roughly in half (e.g., 45.1% to 22.4%) versus Mem0.

Fortunate Recall (FR) is a composable policy layer that classifies personal facts into a 10+1 behavioral ontology and applies category-specific lifecycle rules including differential temporal decay, slot-key supersession, event-time validity, and retrieval routing. FR-Bank scores 76.9% on the new 516-question LifecycleBench, ahead of Mem0, A-MEM, Memory-R1, and MemoryOS (61%-70.5%), and 75.2% on LongMemEval-S. End-to-end, confabulation drops from Mem0's 45.1% to 22.4% over answered queries, with the ranking replicating on open-weight Kimi K2.5 and transferring to the independent BEAM benchmark (46.8% vs 32.9%).

arXiv cs.AI / cs.LG / cs.CLSep 9, 16:31 UTC · 6d agoAI research

Risky Bulletin: Ukraine's top prosecutor resigns amid scam call center scandal

Ukraine's top prosecutor Ruslan Kravchenko resigned after NABU arrested a deputy for taking bribes protecting scam call centers running fake investment platforms.

Ukraine's anti-corruption bureau NABU arrested Serhiy Kropyva, Deputy Head of International Cooperation at the Prosecutor General's Office, alleging officials took monthly protection fees from a network of 100-500 scam call centers luring victims into fake investment platforms, with bribes reportedly growing from $700,000 to $3.5 million per month. Prosecutor General Ruslan Kravchenko resigned on Monday, calling it a political decision, while Kropyva was fired with bail set at 120 million hryvnias ($2.7 million) and over 100 call centers shut down in the past month. The newsletter also briefly covers a cyberattack crippling more than 80 Luxembourg medical practices via payment vendor BMS Engineering, ShinyHunters' claimed theft of 200,000 Florida DMV driver records, a cyberattack on the American Meteor Society, and school closures in Springfield, Massachusetts.

Risky Business NewsSep 9, 06:06 UTC · 7d agoPhishing & fraud

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 LabsSep 14, 00:00 UTC · 2d agoMalware in the wild

SNAP3D: Physically Grounded 3D Parts for Assembly from a Single Image

SNAP3D uses physics simulation feedback to make single-image 3D part generation produce valid, stable assemblies, validated through 3D printing.

The framework improves part-aware 3D generation by resolving inter-part penetration, recovering contact graphs between neighboring parts, and placing parameterized connectors at contact surfaces. Physical simulation feedback refines connector placement, orientation, and dimensions to improve assembly stability while preserving geometry. A physics-based evaluation protocol tests assembly validity and stability under gravity, and results are validated through 3D printing and real-world assembly.

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

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

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

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

Hugging Face daily papersupdated Sep 15, 17:55 UTC · 17h agofirst Sep 14, 20:00 UTC · 1d agoAI research 2 sources

SMOKE#SCREEN Campaign Abuses ScreenConnect to Give Attackers Remote Control Access

Security AffairsAug 9, 11:05 UTC · Aug 9, 2026Threat actor1

⚡ Weekly Recap: Chrome 0-Day, Router Hijacks, Coder Supply Chain Attack and More

Weekly recap: actively exploited Chrome V8 zero-day, MikroTik RouterOS zero-day chain, Magento StyleSmuggler backdoor, and critical N-able N-central flaws.

Google patched an actively exploited Chrome V8 type confusion zero-day, CVE-2026-85046 (CVSS 8.8), the sixth exploited Chrome zero-day of 2026. CERT Polska warned of the MikroTrick exploit chain (CVE-2026-67276 and CVE-2026-86060, CVSS 9.2) giving unauthenticated full control of MikroTik RouterOS devices via SSH, observed since September 2. Sansec disclosed the StyleSmuggler Magento/Adobe Commerce zero-day used since September 4 to inject a Rust backdoor into online stores, while N-able patched three critical N-central flaws (CVE-2026-86206, CVE-2026-86207, and CVE-2026-86218, CVSS 10.0) with Huntress observing likely exploitation. Elastic and Morphisec also detailed RevStealer, an information stealer spread via game cheats and a fake Claude Desktop app.

The Hacker NewsSep 7, 14:36 UTC · 8d agoExploit / PoC in the wildCVE-2026-85046 CVE-2026-86206 CVE-2026-86207+7 CVEs

[webapps] PodcastGenerator 3.2.9 - Stored XSS

A stored cross-site scripting flaw in PodcastGenerator 3.2.9 is documented with a public proof-of-concept exploit on Exploit-DB.

Exploit-DB published exploit ID 52677 targeting PodcastGenerator 3.2.9, a web application affected by stored cross-site scripting. The listing provides a proof-of-concept for the flaw but includes no CVE identifier or reports of active exploitation.

Exploit-DBSep 2, 00:00 UTC · 14d agoExploit / PoC1

Risky Bulletin: BEC campaign steals €35 million from French notaries

Hackers stole over €35 million from 500+ French notary offices in a four-year BEC campaign; ANSSI spent two years helping evict the attackers.

A business email compromise campaign breached more than 500 French notary offices — about 7% of all French notaries per the Conseil Supérieur du Notariat — over four years, stealing more than €35 million by phishing initial access and silently modifying wire transfer details. France's cybersecurity agency ANSSI worked for two years behind the scenes to help notaries remove the persistent attackers, who had deep access; officials also feared hackers could issue fake notarized acts such as marriage certificates or forged real estate deals. No forged documents have been found so far, but notaries have added two-factor authentication and in-person requirements for banking details, and banks added extra checks in 2024. The newsletter also notes other incidents, including a $320 million Bitcoin extraction from Blockstream's Liquid Network and a JetBrains Cadence breach via TeamCity servers.

Risky Business NewsSep 7, 03:42 UTC · 9d agoPhishing & fraud in the wild1

datasette-publish-fly 1.4

Datasette-publish-fly 1.4 sets force_https in fly.toml, fixes a volume detection bug, and adds support for app-scoped Fly deploy tokens.

Version 1.4 of the datasette-publish-fly plugin for deploying Datasette to Fly.io has been released. It sets force_https=true in fly.toml, fixes a 'Volume could not be found' bug, and adds compatibility with app-scoped deploy tokens. No security vulnerabilities are mentioned in the release notes.

Simon WillisonSep 11, 02:58 UTC · 5d agoTools1

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

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

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

arXiv cs.AI / cs.LG / cs.CLSep 10, 17:43 UTC · 5d agoAI research

LACE: Layer-Wise Compression for Dynamic Frame Rate Codecs

LACE introduces layer-wise compression for dynamic frame rate audio codecs, cutting sequence lengths and speeding TTS inference while preserving quality.

LACE (Layer-Adaptive Codec Encoding) applies an independent compression step at each quantization layer of a neural audio codec, enabling layer-specific segmentation boundaries instead of shared ones. Union alignment and boundary anchor mechanisms keep durations consistent for downstream text-to-speech. On LibriTTS, LACE achieves a better rate-quality tradeoff than prior dynamic frame rate codecs and improves TTS inference efficiency at competitive synthesis quality. Code is released in the ESPnet3 codec recipe.

arXiv cs.AI / cs.LG / cs.CLSep 15, 17:46 UTC · 17h agoAI research

Domain-Incremental Learning for Multi-Channel Replay Speech Detection

First continual learning benchmark for multi-channel replay speech detection shows task-specific beamforming cuts catastrophic forgetting across 24 acoustic environments.

Researchers frame replay-attack detection for voice-controlled systems as domain-incremental learning over acoustic environments, evaluating a beamformer-based detector across all 24 environment orderings of the ReMASC corpus with five seeds. Naive sequential fine-tuning raises error rates on previously learned environments by 18.8 points, while elastic weight consolidation halves forgetting but loses plasticity and gradient projection memory is statistically indistinguishable from naive fine-tuning. A task-specific beamformer keeping one spatial front-end per environment significantly improves final and incremental accuracy, and the last environment in a sequence dominates final performance.

arXiv cs.CRSep 10, 08:03 UTC · 6d agoResearch1

How Hugging Face Inference Endpoints, Jobs, and Buckets Power Search on Papers with Code

Hugging Face explains how Inference Endpoints, Jobs, and Buckets power semantic search on Papers with Code.

Hugging Face describes the infrastructure behind search on Papers with Code, built on its Inference Endpoints, Jobs, and Buckets services. The post is a product-focused engineering walkthrough with no security impact.

Hugging Face BlogAug 21, 00:00 UTC · 26d agoAI tools & infra

Week in review: Cisco fixes IMC bug, Patch Tuesday forecast, Black Hat USA 2026

Help Net SecurityAug 9, 00:00 UTC · Aug 9, 2026Vulnerability CVE-2026-66066 CVE-2026-185771

Type Diversity Enables Transformers to Generalise Compositionally

Researchers show lexical-versus-structural compositional generalization gaps in Transformers stem from type diversity imbalance in datasets, not architectural limits.

The paper argues that Transformers' difficulty with structural compositional generalization is an artifact of low structural type diversity in prior benchmark datasets rather than an architectural limitation. Using Grammatical Framework, the authors create linguistically diverse variants of COGS and SLOG. They find type diversity correlates with compositional generalization equally in lexical and structural test cases, contradicting previous claims that compound divergence explains task difficulty.

arXiv cs.AI / cs.LG / cs.CLSep 11, 17:59 UTC · 4d agoAI research

Wordfence Argus Finds Unauthenticated Arbitrary File Upload Vulnerability in Gravity Forms

Wordfence finds an unauthenticated arbitrary file upload flaw in Gravity Forms (1M+ installs) that can lead to remote code execution.

On August 9, 2026, Wordfence's Argus scanner discovered an unauthenticated arbitrary file upload vulnerability in the WordPress plugin Gravity Forms, estimated at over one million active installations. Attackers can write files with attacker-selected extensions to a public temporary upload directory, potentially enabling remote code execution. The post does not mention a CVE identifier or observed exploitation.

WordfenceSep 1, 17:47 UTC · 14d agoVulnerability

Massive Redis Cryptojacking Campaign Hijacks Thousands of Linux Servers

RedisRaider cryptojacking campaign compromises thousands of exposed, unauthenticated Linux Redis servers using cron persistence to deploy XMRig Monero miners.

Hunt.io researchers track a large-scale cryptojacking operation named RedisRaider that scans IPv4 ranges for Redis services exposed on TCP port 6379 and targets instances accepting unauthenticated connections. From a master list of 12,966 candidate hosts, 2,342 were confirmed to accept commands without authentication. Attackers abuse Redis commands (CONFIG SET dir/dbfilename, SET, BGSAVE) to write malicious cron entries into /etc/cron.d or /var/spool/cron, launching XMRig-based Monero miners, with branches including SSH authorized-key injection, Lua probing, and WordPress spraying. The article also references CVE-2026-81934, a Redis TLS use-after-free allowing unauthenticated command execution, fixed in releases including 8.2.9, 8.4.6, 8.6.6, 8.8.2, and 8.10.1.

GBHackersSep 9, 05:28 UTC · 7d agoExploit / PoC in the wildCVE-2026-81934

Multi-Vector (Late Interaction) Embedding Models with Sentence Transformers

Hugging Face details building and using multi-vector late-interaction embedding models with Sentence Transformers for retrieval workloads.

Hugging Face published a guide on multi-vector, late-interaction embedding models (ColBERT-style) supported through Sentence Transformers. The post covers how practitioners can build and use these models for retrieval and RAG pipelines. It is a developer tooling and technique write-up, not a security advisory.

Hugging Face BlogAug 18, 00:00 UTC · 29d agoAI tools & infra1

HarvestBench: Measuring Whether LLM Agents Will Pay to Avoid Killing Animals

HarvestBench, a reproducible farm-simulation benchmark, shows LLM agents pay fuel costs to avoid killing animals, with kill rates spanning 0.4% to 98.8% across nine models.

HarvestBench is a reinforcement-learning gridworld farm simulation where LLM agents choose between driving over animals at no cost or paying a posted fuel price to swerve during a cooperative corn harvest. Across nine models and 7,201 priced decisions, kill rates ranged from 0.4% to 98.8%, unordered by capability, with Terra and Sol the most merciful and GPT-4o-mini the most cruel. Morality briefings cut kill rates below 6% in five of six reasoning models, while removing them pushed rates above 84% in all six. The scorer counts events in the game log without an LLM grader, making results fully reproducible.

Hugging Face daily papersSep 2, 20:00 UTC · 13d agoAI safety & security