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DomainAll Cyber AIWindow24h 3d 7d 30d AllIn the wild Important only Show duplicates

CategoryAll Malware 44 Vulnerability 10 Exploit / PoC 7 Ransomware 2 Data breach 1 Industry 1 Threat actor 1

SeverityAll critical 29 high 14 medium 21 low 2 info 0

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Xen Security Advisory 511 v3 (CVE-2026-79603) - Unconditionally do TLB flushing ahead of page scrubbing

Xen Project released XSA-511 (CVE-2026-79603) fixing missing TLB flushes before page scrubbing that can leak x86 PV guest data.

Xen Security Advisory 511 v3 publicly discloses CVE-2026-79603, a TLB handling flaw in the Xen hypervisor on x86. x86 PV guests can free memory pages while a stale TLB entry still points to them, and Xen only flushes the TLB when the page is reused, potentially exposing stale data ahead of scrubbing. The advisory changes Xen to unconditionally flush the TLB ahead of page scrubbing. The issue was published in version 3 of the advisory.

oss-securitySep 8, 15:39 UTC · 7d agoVulnerability 4 sources CVE-2026-79603

ShieldCrash PoC: Microsoft Defender Fix Bypass

A ShieldCrash proof-of-concept bypasses Microsoft's patch for CVE-2026-69414, a high-severity elevation-of-privilege flaw in the Microsoft Malware Protection Engine.

Microsoft previously fixed CVE-2026-69414 (ShieldBreak), a high-severity elevation-of-privilege vulnerability in the Microsoft Malware Protection Engine used by Microsoft Defender. SOCRadar now reports a new proof-of-concept dubbed ShieldCrash demonstrating that the published fix can be bypassed. The available source text does not detail affected versions or whether the bypass has been used in real attacks.

SOCRadarSep 10, 12:18 UTC · 5d agoExploit / PoC 4 sources CVE-2026-69414

Kimwolf v7 Hides DDoS Traffic Behind Chrome Fingerprints and Ethereum

Unit 42 details Kimwolf v7, an Android TV botnet upgrade using HTTP/2 Chrome-fingerprint DDoS floods and Ethereum ENS-based C2 across 1.8M+ infected devices.

Palo Alto Networks Unit 42 identified Kimwolf v7 on February 3, 2026, an upgrade to an Android TV botnet active since August 2025 and linked to the AISURU botnet, which has infected over 1.8 million devices. The new version adds an HTTP/2-based DDoS flood that mimics full Chrome browser fingerprints, consolidates 43 attack commands into 15 methods covering layers 3-7, and resolves C2 addresses via Ethereum Name Service using five hard-coded public blockchain RPC endpoints, backed by a Tor hidden service and a local proxy on 127.0.0.1:23075. It spreads through residential proxies to Android TV boxes with ADB enabled on port 5555 and masquerades as netd_service. The botnet is associated with the record 31.4 Tbps DDoS attack in November 2025.

Security AffairsAug 12, 08:27 UTC · Aug 12, 2026Malware in the wild

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-securitySep 4, 21:23 UTC · 11d agoVulnerability

Approval Integrity and Recovery in LLM Answer Publication

Study measures approval integrity in Lightcap LLM answer publication, finding the 14B response-act checker accepts 291 of 302 unsupported answers.

The study evaluates exact-content binding, authorization freshness, and checkpoint recovery in Lightcap's publication enforcement using 3,600 assessments over 900 human-annotated RAGTruth responses from three Ministral models. The production 14B response-act checker accepts 291 of 302 unsupported answers versus 41 for a direct-grounding baseline, with supported-answer retention of 95.2% versus 66.9%. A stateful recheck-recovery policy increases exact-match error by 9.23 percentage points relative to initial checkpoints, and controlled evidence-fingerprint changes expose asymmetric freshness enforcement between publication and recovery. A separate BIPIA prompt-injection experiment records zero target insertions among 266 valid editor outputs.

arXiv cs.CRSep 14, 13:48 UTC · 1d agoAI safety & security

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

[webapps] CubeCart 6.7.4 - Stored XSS

A proof-of-concept stored cross-site scripting exploit targeting CubeCart 6.7.4 was published on Exploit-DB.

Exploit-DB lists a proof-of-concept exploit for a stored cross-site scripting (XSS) vulnerability in CubeCart 6.7.4, a PHP-based e-commerce web application. The listing demonstrates injection of attacker-controlled script that persists in the application, but no exploitation in the wild or CVE assignment is reported in the provided text.

Exploit-DBAug 31, 00:00 UTC · 16d agoExploit / PoC1

Edge0/Edge0-35B-A3B-preview — new model trending #30 on Hugging Face

Edge0 released a 35B sparse MoE model running in under 3 GiB of memory at 15 tok/s via SSD expert offload and int4 quantization.

Edge0-35b-a3b-preview is a 35B-parameter MoE (256 experts, 4 active per token) built on Qwen3.5-MoE 35B-A3B, shipped as a 4-bit checkpoint with LoRA and prerouter adapters under Apache 2.0. The edge0 framework streams expert weights from SSD on demand, bounding peak active memory at 2.9 GiB and achieving 14.9-17.7 tok/s decode on a Mac mini M4 Pro (MLX backend). Recover-LoRA distillation keeps the int4 model within 3.9 points of its fp16 base (79.2 vs 83.2 average on OpenCompass benchmarks including AIME 2026, HumanEval, GPQA-Diamond, MMLU-Pro, and IFBench).

Hugging Face trending modelsSep 8, 13:56 UTC · 7d agoModel release

Re: Vulnerabilities fixed in libxml2-2.15.4

libxml2 2.15.4 patches two flaws including a heap buffer overflow in xmlDictAddQString tracked as CVE-2026-86137 and CVE-2026-86138.

libxml2 releases before 2.15.4 are affected by an integer overflow in xmlDictAddQString in dict.c that leads to a heap-based buffer overflow, tracked as CVE-2026-86137 and CVE-2026-86138. The oss-security post from Debian's Salvatore Bonaccorso flags the fixed release for downstream tracking. No exploitation is mentioned in the disclosure.

oss-securitySep 5, 12:16 UTC · 10d agoVulnerability CVE-2026-86137 CVE-2026-86138

XHToken/Spark-X2.5-4B-GGUF — new model trending #30 on Hugging Face

XHToken released GGUF weights of Spark-X2.5-4B, a compact model with 1M-token context and 200+ language support, under Apache 2.0.

The Hugging Face repository provides BF16 GGUF conversions of Spark-X2.5-4B, a compact general-purpose language model for conversation, writing, translation, reasoning, coding, tool use, and agentic workflows. The model uses a hybrid attention architecture, supports a native context length up to 1M tokens, and covers more than 200 languages. Local inference is supported through Ollama and LM Studio via an XHToken llama.cpp fork, with a --think=false flag to disable thinking mode for faster responses. Released under Apache License 2.0; it was trending #30 on Hugging Face at publication.

Hugging Face trending modelsAug 28, 11:26 UTC · 19d agoModel release

JustFit: 200K-Token LLM Serving on a 24 GiB Laptop with Just-in-Time State Management

JustFit MLX runtime serves 200K-token contexts for Qwen3.8-27B on a 24 GiB MacBook via just-in-time state management.

JustFit is an MLX-based inference runtime combining KVExec for compressed KV execution, PhaseSwap for component residency, and StateTrans for state-preserving serving transitions, independent of weight quantization. On a 24 GiB M4 Pro MacBook running Qwen3.8-27B MXFP4, it completed 196,608 input and 16,384 output tokens, raising single-request context from the mlx-vlm baseline's 30,720 positions to 212,992 (6.93x). Performance tests show 19.11 tokens/s on a 32K-input probe with a 16,374 MiB median peak footprint, and the runtime answered 29 of 30 AIME 2026 problems correctly.

arXiv cs.AI / cs.LG / cs.CLSep 15, 17:15 UTC · 18h agoAI research

ukisai/Swift-Qwen3.8-27b — new model trending #30 on Hugging Face

UkisAI releases Swift-Qwen3.8-27B, a Qwen3.8-27B derivative using 58.3% fewer thinking tokens with <1% performance loss and ~1.95x speed-up.

UkisAI released Swift-Qwen3.8-27B, a reasoning-efficient derivative of Qwen3.8-27B that cuts thinking-token usage by 58.3% while staying within 1% of base performance, yielding a 1.95x speed-up on several tasks. The model was fine-tuned by penalizing reasoning-marker tokens that trigger overthinking, plus a transfer component from BottleCap AI's ThinkingCap-Qwen3.6-27B. Benchmarks include GPQA-Diamond 88.28% (base 88.38%), MMLU-Pro 84.95% (base 85.47%), and AIME 2026 94.00% (base 98.67%), with mean-token reductions of roughly 27-46% across tests. GGUF weights are available on Hugging Face alongside enterprise licensing options.

Hugging Face trending modelsSep 8, 13:35 UTC · 7d agoModel release

m-a-p/YuE2-3B — new model trending #30 on Hugging Face

M-A-P released YuE2-3B, an open music generation model that outperforms Suno v5 on WildSongBench and runs locally on a 24GB GPU.

The M-A-P (multimodal-art-projection) team released YuE2-3B, an open-weights music generation model that turns lyrics and a style prompt into full songs with vocals and accompaniment. It uses an AR-NAR Mixture-of-Transformers backbone with symbolic planning and flow matching through a VAE, and supports editable scores (melody and chords, including ABC notation) plus agentic editing workflows. On 192 WildSongBench prompts it reports a SongBench average of 6.9632 (best-of-8) versus 6.8721 for Suno v5, claimed as state of the art among evaluated open and proprietary models. It runs 48 kHz stereo inference locally on a single 24GB NVIDIA GPU without quantization, with companion releases including YuE2-Vae, MERT-v2 encoders, the WildSongBench dataset, and SheetSage2.

Hugging Face trending modelsupdated Sep 12, 05:56 UTC · 4d agofirst Sep 9, 18:30 UTC · 6d agoModel release 6 sources1

Identifying a BOLA Vulnerability in Harbor, a Cloud

Unit 42 found a BOLA flaw, CVE-2024-22278 (CVSS 6.4), letting Maintainers improperly alter Harbor project metadata; fixed in versions 2.9.5, 2.10.3, and 2.11.0.

Unit 42 researchers identified a broken object-level authorization flaw, CVE-2024-22278, in Harbor, a CNCF-graduated cloud-native container registry with 1.8 million downloads. The flaw (CVSS 6.4) lets users with the Maintainer role create, update, and delete project metadata, actions reserved for ProjectAdmin, risking data exposure, integrity compromise, and circumvention of vulnerability scanning. Harbor patched the issue in versions 2.9.5, 2.10.3, and 2.11.0. The finding came from Unit 42's automated BOLA detection tool built on generative AI.

Palo Alto Unit 42Aug 17, 12:35 UTC · 29d agoVulnerability CVE-2024-22278

ISTA-DASLab/Qwen3.8-27B-GSQ-RCO-GGUF — new model trending #3 on Hugging Face

ISTA-DASLab releases GSQ-RCO non-uniform GGUF quantizations of Qwen3.8-27B down to 2.5 bpw, with task-lossless IQ3_S matching BF16 benchmark scores.

ISTA-DASLab released GGUF quantizations of Qwen3.8-27B produced with GSQ (Gumbel-Softmax Quantization) and RCO (Riemannian Constrained Optimization), non-uniform methods that allocate per-tensor precision via gradient-based search under a total size budget. Four checkpoints range from 2.50 bpw (8.4 GB) to 3.50 bpw (11.8 GB), plus a BF16 vision projector (mmproj) enabling multimodal use. The recommended IQ3_S build is task-lossless, matching the BF16 base exactly on AIME25 (100.00) and LiveCodeBench v6 (85.71) at roughly one fifth of the BF16 size. Optional -mtp variants add a Multi-Token Prediction head for speculative decoding in llama.cpp.

Hugging Face trending modelsAug 28, 18:38 UTC · 18d agoModel release1

Rosetta at AlexandriaX-2026: LoRA-Adapted NileChat for Context-Aware Dialectal Arabic Dialogue Translation

Rosetta ranks 4th and 5th in AlexandriaX-2026 dialectal Arabic dialogue translation using a LoRA adapter on NileChat-3B, finding limited pretraining benefit.

The Rosetta system for the AlexandriaX-2026 shared task fine-tunes a LoRA adapter on NileChat-3B for context-aware English-to-dialectal Arabic dialogue translation. The adapter was additionally pretrained on MADAR and PADIC dialect corpora for the unconstrained track. It achieved spBLEU 26.10 (4th, constrained) and 25.09 (5th, unconstrained). External dialect pretraining improved only two of thirteen dialects while slightly degrading overall performance, indicating negative transfer.

arXiv cs.AI / cs.LG / cs.CLSep 9, 16:15 UTC · 6d agoAI research1

Harnessing LLMs for Automating BOLA Detection

Unit 42's BOLABuster methodology uses LLMs to automate detection of broken object-level authorization vulnerabilities, uncovering flaws in Grafana, Harbor, and Easy!Appointments.

Palo Alto Unit 42 details BOLABuster, a methodology combining large language models with heuristics to automate detection of broken object-level authorization (BOLA) flaws, which traditional fuzzing and static analysis struggle to find. The approach uses LLM reasoning to understand application logic, map endpoint dependency relationships, and generate and interpret test cases. It found CVE-2024-1313 in Grafana, CVE-2024-22278 in Harbor, and 15 CVEs in Easy!Appointments. The team is continuing to hunt for BOLAs in open-source and internal projects.

Palo Alto Unit 42Aug 17, 12:34 UTC · 29d agoResearch CVE-2024-1313 CVE-2024-22278 CVE-2023-3285+14 CVEs

New Microsoft Defender 'ShieldCrash' zero-day grants SYSTEM access

Researcher Nightmare Eclipse released 'ShieldCrash', a zero-day exploit for Microsoft Defender that grants attackers SYSTEM-level access.

An anonymous researcher known as Nightmare Eclipse published a zero-day exploit for Microsoft Defender, dubbed 'ShieldCrash', that yields SYSTEM-level access. The release came immediately after Microsoft rolled out its September 2026 Patch Tuesday security updates. No CVE identifier has been assigned publicly and no in-the-wild exploitation has been reported yet. Microsoft Defender ships by default on Windows, so potential exposure is broad until Microsoft patches the flaw.

BleepingComputerSep 9, 07:30 UTC · 7d agoExploit / PoC

Researcher Drops New Microsoft Defender PoC Showing ShieldBreak Patch Can Be Bypassed

Researcher Chaotic Eclipse released a PoC showing CVE-2026-69414's patch is bypassable, allowing arbitrary file reads as SYSTEM on current Windows.

The researcher known as Chaotic Eclipse published a proof-of-concept for a zero-day in Microsoft Defender, dubbed ShieldCrash, assessed as a patch bypass for ShieldBreak (CVE-2026-69414, CVSS 7.8). The PoC demonstrates an arbitrary file read as SYSTEM with the latest Windows installed, and all supported desktop versions are said to be impacted. Microsoft patched the original issue in Microsoft Malware Protection Engine 1.1.26080.3, which updates automatically. The same researcher recently released PoCs for flaws in CrowdStrike Falcon Sensor, Kaspersky, Avast Antivirus and NVIDIA.

The Hacker NewsSep 9, 06:47 UTC · 7d agoExploit / PoC CVE-2026-694141

When the prompt becomes the payload: A practical pen-testing guide for GenAI, LLM and RAG applications

CSO Online publishes a practical penetration-testing guide for GenAI, LLM, and RAG applications, covering prompt injection, retrieval poisoning, and tenant isolation testing.

The guide frames LLM applications as attack graphs spanning prompts, retrieval layers, vector stores, tools, identities, and downstream APIs, arguing that conventional web testing misses instruction-vs-data channel risks. It builds on OWASP prompt injection guidance (direct vs. indirect injection) and NIST's 2025 adversarial machine-learning taxonomy, noting that RAG and fine-tuning do not remove injection risk. Recommended practices include documenting trust transitions across components, using canaries and synthetic records to avoid test side effects, running multi-turn and obfuscated injection campaigns, and verifying chains from poisoned documents to observable state changes. It also details testing RAG pipelines via controlled document poisoning across metadata, OCR layers, and code comments, plus cross-tenant isolation checks on retrieved document IDs.

CSO OnlineSep 9, 10:00 UTC · 7d agoAI safety & security1

Breaking the Seal: Static Deobfuscation of JSCeal’s Compiled V8 Bytecode

Check Point's hasherezade details static deobfuscation of JSCeal, a V8-bytecode stealer targeting cryptocurrency applications since March 2024.

JSCeal is an infostealer distributed as compiled V8 bytecode (.jsc) executed by a bundled Node.js runtime, aimed at cryptocurrency applications. Other vendors track the same family under the names WEEVILPROXY or MeadowLocust. Check Point Research has tracked the campaign since early 2024, with activity dating back to March 2024. The write-up presents a static approach to unpacking the bytecode without executing it.

Check Point ResearchAug 31, 13:38 UTC · 15d agoMalware in the wild1

Researchers Use Claude to Port Pre-Auth RCE Exploit From One PLC Model to Another

Forescout used Anthropic's Claude to port a working pre-auth RCE exploit for CVE-2021-31886 between WAGO PLCs, executing ARM shellcode on live hardware.

Forescout Vedere Labs used Claude interactively to port an RCE exploit for CVE-2021-31886, a CVSS 9.8 stack buffer overflow in the Nucleus FTP server's USER command, from a WAGO 750-852 to a WAGO 750-831 PLC, running attacker-supplied ARM shellcode. The final RCE stage cost $535.74 in API usage over 8 hours 32 minutes, and a follow-up attempt to build a C2 implant permanently bricked the device. CERT@VDE lists many Nucleus V1-based WAGO models as vulnerable with no updates available; Siemens plans no Nucleus NET remediation. The work follows a joint NSA/CISA/FBI/DOE/EPA advisory warning of AI-generated exploitation scripts targeting internet-exposed Siemens S7 PLCs.

The Hacker NewsSep 2, 07:47 UTC · 14d agoResearch CVE-2021-318862

From Intent to Execution Grant: An Execution-Boundary Conformance Profile for High-Risk AI Actions

Researchers specify EBL-Core, an execution-boundary conformance profile binding AI agent intents, policies, and evidence into verifiable execution grants, validated with bounded tests.

The paper defines EBL-Core, a conformance profile deciding whether one fully materialized AI-generated candidate action may receive action-scoped execution authority. It binds a structured intent object, Root and Operational Policies, typed evidence, and a verifiable Decision Derivation through an Execution Release Contract, with lifecycle rules for Redemption and Revocation. Evaluation included 34 static vectors, 15 lifecycle checks, and 100 trials of 32 concurrent Redemption attempts yielding exactly one winner per trial. The authors state these bounded results demonstrate executability of the specified subset, not production readiness or complete mediation.

arXiv cs.CRSep 10, 14:21 UTC · 5d agoAI safety & security1

Attackers Exploit PaperCut Flaws to Steal Credentials From Schools and Universities

Attackers exploit newly disclosed PaperCut auth bypass CVE-2026-81578 and RCE CVE-2026-82078 to steal credentials from schools and universities in the US and Europe.

Arctic Wolf observed threat actors chaining CVE-2026-81578 (authentication bypass) and CVE-2026-82078 (remote code execution) in PaperCut to execute commands, perform reconnaissance, and create privileged accounts on servers at K-12 schools and universities in the US and Europe. Post-exploitation includes registry hive collection with lsa_collect.exe delivered via certutil, Meterpreter Java payloads from 194.180.48.134, and searches of PaperCut config files for passwords, LDAP bindings, and tokens. Stolen logins could provide a pathway into other critical systems across compromised environments.

The Hacker NewsSep 5, 07:31 UTC · 11d agoExploit / PoC in the wildCVE-2026-81578 CVE-2026-820781

X-AuT: Progressive Audio-Encoder Compression for Speech LLMs with Cross-Scale Distillation

XPeng AI's X-AuT prunes speech LLM audio encoders, cutting Qwen3-ASR-0.6B error from 5.61% to 5.27% with fewer parameters.

X-AuT is a progressive compression framework for speech LLM audio encoders that selects layer combinations via short behavioral probes and restores pruned models using cross-scale distillation and LoRA finetuning while keeping the language-model backbone frozen. Compressing Qwen3-ASR-0.6B from 18 to 16 audio-encoder layers lowered macro-average error from 5.61% to 5.27% on ten Chinese-English benchmarks. A 14-layer model reached 5.75% error with 20.7% fewer audio-tower parameters, and progressive pruning outperformed direct pruning (5.75% vs 6.73%).

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

Training a 3.8B LLM to 0.384 CORE for $998 – Hugo Vergnes

Independent developer Hugo Vergnes trained a 3.8B-parameter Llama-style model to 0.384 CORE on 65B tokens for $998 in 43 hours on rented B200s.

Hugo Vergnes trained little-lm, a 3.848B-parameter decoder-only LLM, on 65.3B tokens in 43 hours for $998 using rented NVIDIA B200s, scoring 0.384 on the CORE benchmark and beating nanochat d32 (0.310) at similar cost. The Llama-style architecture uses RMSNorm, RoPE, GQA with 24 query and 8 KV heads, relu-squared MLPs, QK-norm, and ResFormer-style value embeddings that account for 19% of parameters. Key wins included the Muon optimizer for matrix parameters, a trapezoidal learning-rate schedule with linear cooldown, FP8 training plus vocabulary padding for roughly 33% throughput gains, and the ClimMix dataset over FineWeb-Edu. The project, inspired by Karpathy's nanochat, was built as a config-driven YAML framework for small LLM training.

Hacker News · securitySep 10, 02:04 UTC · 6d agoAI research HN 28↑ · 2 comments1

OpenBMB Releases MiniCPM5-2B: A 2.52B Dense Model Averaging 53.9 Across 34 Benchmarks and Built to Run On Device

OpenBMB released MiniCPM5-2B, a 2.52B-parameter Apache 2.0 on-device model averaging 53.9 across 34 benchmarks, ahead of Qwen3.5-4B.

OpenBMB released MiniCPM5-2B, a 2,516,756,480-parameter dense LlamaForCausalLM model with grouped-query attention and a 131,072-token context, under Apache 2.0, runnable via vLLM, SGLang, llama.cpp, and Ollama. It averages 53.9 across 34 benchmarks versus 51.1 for Qwen3.5-4B, with strong tool-use (97.1 on tau2-Bench Telecom) and code results (69.1 LiveCodeBench v6, 46.4 SWE-bench Verified). Training combined 400B tokens of deep-thinking SFT, critic-based JustRL II RL teachers, and on-policy distillation merging 16 RL experts; datasets and intermediate checkpoints were published alongside the weights.

MarkTechPostSep 7, 19:18 UTC · 8d agoModel release