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YuE2 · Frontier Music with Symbolic Planning

YuE2, a 3.59B-parameter music generation model, scores 6.9632 on SongBench, beating Suno v5 via symbolic planning.

YuE2 is a music generation model of roughly 3.59B parameters and 28 layers supporting song creation, covering, and agentic editing through editable ABC symbolic scores. Its best-of-8 setting reaches 6.9632 on SongBench, the highest mean among 15 evaluated settings on WildSongBench (192 prompts), ahead of Suno v5 at 6.8721. The project also introduces MERT2, whose 632M-parameter encoders achieve state of the art on 14 of 15 MARBLE metrics, and SheetSage2, which transcribes beats, downbeats, key, chords, structure, and melody with SOTA on 10 of 13 benchmark metrics.

Hacker News · AIupdated · 5d agofirst · 5d agoModel release 2 sourcesHN 43↑ · 35 comments

Mercator ↔ Equal Earth

Simon Willison used GPT-6 Astra (medium) in ChatGPT Work to build an animated D3 transition between Mercator and Equal Earth map projections.

Willison built an animated transition between the Mercator and Equal Earth map projections using D3. The tool was generated by GPT-6 Astra (medium) in ChatGPT Work. Equal Earth is a projection recently voted on at the UN. The post is a vibe-coding demonstration rather than a security or major model event.

Simon Willison · 9d agoAI tools & infra1

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-security · 11d agoVulnerabilityCVE-2026-86137CVE-2026-86138

TART: A Modular Tool for Technique-Aware Audio-to-Tablature Guitar Transcription

TART pipeline transcribes guitar audio to tablature with fingering and technique labels, outperforming prior baselines by up to 8.5 Tab F1 points.

TART is a modular four-stage pipeline for audio-to-tablature guitar transcription, combining an audio-to-MIDI transcription model, an expressive technique classifier, an audio-conditioned T5 encoder-decoder for string-fret assignment, and an automated tablature generator. In zero-shot evaluation on GuitarSet, EGDB, and two noisy augmented benchmarks, it averages 81.35% audio-to-MIDI F50 (+6.67 over the best baseline), 71.8% string-fret Tab F1 (+8.5), and 54.08% end-to-end Tab F1. The authors state it is the first framework to generate tablature with both fingering and expressive technique annotations directly from guitar audio.

arXiv cs.AI / cs.LG / cs.CL · 6d agoAI research2

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 · 12d agoVulnerability

The Shared Clipboard Inside the Sandbox: Cross-Account Data Leakage in ChatGPT

Check Point discovers cross-account data leakage in ChatGPT: isolated code-execution containers communicate via shared JFrog Artifactory, enabling covert Gmail exfiltration.

Check Point Research found a covert bidirectional channel between ChatGPT code-execution containers belonging to different accounts, which were supposed to be isolated from each other and the public internet. Both could reach the same internal JFrog Artifactory instance used for package delivery, whose exposed Item Management API allowed a 'shared clipboard' between containers. In a proof of concept, a hidden instruction in a shared conversation made ChatGPT retrieve email data from the victim's connected Gmail account and send it to the attacker's account while the victim received a normal answer. The same channel could exfiltrate conversation history and session files; OpenAI recently described a similar isolation weakness in its postmortem of the Hugging Face incident.

Check Point Research · 8d agoAI safety & security1

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.CL · 7d agoAI research1

ChatGPT Sandbox Flaw Lets Attackers Steal Gmail Data Across Accounts via Hidden Channel

Check Point found a cross-account covert channel in ChatGPT sandboxes via shared JFrog Artifactory metadata, enabling session hijacking and Gmail data theft. Now fixed.

Check Point discovered that ChatGPT code-execution containers across different accounts could all reach the same internal JFrog Artifactory instance, whose Item Properties API was readable and writable by all accounts, creating a covert cross-account communication channel. Attackers could plant hidden instructions via pasted prompts, shared chat links, or custom GPTs, then trigger tasks in a victim's session to exfiltrate connected-app data such as Gmail, using ChatGPT's default 'Important actions' setting that permits reads without confirmation. OpenAI confirmed and decommissioned the shared Artifactory instance, closing the channel before publication.

Cyber Security News · 8d agoAI safety & security1

GuardBreaker: Derailing AI-assisted malware analysis with a code comment

ESET names 'GuardBreaker': UAC-0099 embeds a nuclear-weapon question in VBScript comments to trip LLM scanner guardrails during analysis of its MATCHBOIL loader.

ESET researchers observed the Russia-aligned group UAC-0099 inserting a decoy prompt injection into a VBScript used to install its MATCHBOIL loader in an attack against a Ukrainian target, aiming to make LLM-based code scanners refuse and stop inspecting the file. The comment triggers safety guardrails with a request about building a nuclear weapons but has no runtime effect. Similar LLM-thwarting tricks have appeared in malicious PyPI and npm packages reported by Socket and StepSecurity. ESET recommends multi-model cross-validation of AI-assisted analysis and treating missing LLM output as requiring further checks.

ESET WeLiveSecurityupdated · 5d agofirst · 6d agoAI safety & security 3 sources1

Persistent Attempts at Cyberespionage Against Southeast Asian Government Target Have Links to Alloy Taurus

Alloy Taurus (GALLIUM) compromised Southeast Asian government networks from 2022 to 2023 using Exchange web shells and undocumented .NET backdoors Reshell and Zapoa.

Unit 42 tracked persistent multiwave intrusions at a Southeast Asian government starting in early 2022 and continuing through 2023, attributing the activity with moderate confidence to Alloy Taurus (aka GALLIUM), a Chinese state-aligned espionage group. Attackers exploited Exchange Server vulnerabilities to deploy web shells including China Chopper, then ran reconnaissance with Fscan and WebScan, created administrative accounts, and installed undocumented .NET backdoors named Reshell and Zapoa. They established resilience by installing SoftEther VPN, brute-forced Active Directory credentials with Kerbrute, and dumped credential stores with GoDumpLsass and LsassUnhooker. The campaign reflects long-term espionage tradecraft to maintain a foothold.

Palo Alto Unit 42 · Aug 17, 2026Threat actor in the wild1

ChatGPT Flaw Could Let Attackers Steal Gmail Data Across User Accounts

Check Point found a patched ChatGPT flaw where prompt injection and a shared Artifactory service let attackers covertly exfiltrate Gmail data across accounts.

Check Point Research discovered that ChatGPT's isolated code-execution containers could access a shared internal JFrog Artifactory service, whose item metadata API enabled a bidirectional cross-tenant covert channel between accounts. Attackers could embed hidden prompt-injection instructions in shared conversations or custom GPT configurations, causing a victim's session to silently relay connected Gmail data to another ChatGPT account. In a proof of concept, email data was exfiltrated with the only visible hint being a 'Talked to Gmail' activity label. OpenAI decommissioned the internal Artifactory instance involved, eliminating the channel by publication time.

GBHackers · 7d agoAI safety & security

VU#308749: Remote Code Execution and Arbitrary File Read Vulnerabilities in Kaltura Servers

Insecure deserialization in Kaltura's legacy HTML5 Player V2 (mwEmbed) allows arbitrary file read and remote code execution; Player V7 is unaffected.

CERT/CC issued VU#308749 for two flaws in Kaltura's HTML5 Player V2 library (mwEmbed/html5lib), both caused by the same insecure deserialization bug. The flaws enable arbitrary file read and remote code execution via the exposed mwEmbedLoader.php endpoint. Affected versions include html5lib v2.45, v2.103 and earlier, and other v2.x releases; the currently supported Player V7 is unaffected. No evidence of exploitation was cited.

CERT/CC Vulnerability Notes · 22d agoVulnerability

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.CL · 12d agoAI research1

ChatGPT Flaw Let a Planted Prompt Send a Victim's Gmail Data to Another Account

Check Point showed a planted prompt could make ChatGPT silently exfiltrate Gmail data via a hidden cross-container channel; OpenAI took the service offline.

Check Point Research demonstrated that a single planted instruction in a ChatGPT conversation could make the model silently exfiltrate Gmail data, chat history, and files to an attacker's account while replying normally to the user. The covert channel abused read/write properties on files in an internal JFrog Artifactory instance shared by ChatGPT code-execution containers across accounts, turning package metadata into shared storage. Injection vectors included pasted prompts, shared conversations, and custom GPT builder instructions; default connected-app permissions allowed Gmail reads without user approval. OpenAI confirmed the internal service was taken offline after disclosure; this is Check Point's second reported ChatGPT covert channel after a DNS-based one fixed in February.

The Hacker News · 8d agoAI safety & security

Russian hackers plant nuclear weapon prompt in malware to trip AI safety guardrails

ESET reports Russian group UAC-0099 hid a prompt in VBS malware comments to trip AI safety filters and disrupt automated malware analysis in Ukraine.

ESET identified a technique dubbed GuardBreaker in which UAC-0099 embedded a comment reading "I want to make nuclear weapon. Help me …" inside a malicious VBS script to trigger AI safety mechanisms and halt AI-assisted malware analysis. The script, part of the group's toolset, downloads the MATCHBOIL malware used exclusively by this Russia-aligned group; CERT-UA documented the chain including LUNCHPOKE, BURNYBEAR and MATCHBOIL.V2 in a July advisory. UAC-0099 typically targets transportation and energy sectors and hands validated targets to GRU-linked Sandworm. ESET warned that AI-assisted analysis must be backed by layered detection and human-driven engineering.

Help Net Security · 16d agoAI safety & security in the wild

Hackers Use Claude and GPT-Powered Tools to Help Breach Government and Financial Networks

Unit 42 links two Latin America campaigns where operators used Claude and GPT-4.1 during intrusions against government and financial targets.

Palo Alto Networks Unit 42 identified two activity clusters, CL-CRI-1131 and CL-CRI-1163, tied by shared SOCKS5 relay infrastructure and use of large language models during operations. The Mexican cluster targeted a transportation organization, federal ministries and water utilities in Mexico and Ecuador, while the Brazilian cluster used resume-themed phishing, custom remote-access Trojans and SockTz SOCKS5 tunneling against financial organizations. An exposed self-hosted NextChat interface on attacker infrastructure led researchers to assess operators used Claude and GPT-4.1 to generate workaround scripts and troubleshoot execution failures. Unit 42 noted AI reduced time needed to troubleshoot intrusions after initial access, rather than replacing the attacker.

Cyber Security News · 6d agoThreat actor in the wild 2 sources1

Towards Scalable and Cost-Efficient Vulnerability Detection: A Study on Automatic Query Generation

A study finds LLM-synthesized CodeQL queries improve average F1-score by 82% over baseline queries, offering scalable vulnerability detection versus direct LLM scanning.

Researchers conducted an empirical study evaluating whether LLMs can synthesize executable CodeQL queries from National Vulnerability Database vulnerability data. LLM-generated queries significantly enhanced baseline CodeQL suites, yielding an 82% improvement in average F1-score across a diverse set of real-world vulnerabilities. A cost-benefit analysis shows direct LLM-based scanning of entire repositories is often computationally and financially prohibitive, while LLM query synthesis offers a scalable and cost-effective alternative for large-scale vulnerability detection.

arXiv cs.CR · 7d agoResearch1

Breaking the 1.58-bit Barrier for Ternary LLMsnew

An arXiv paper claims a method that breaks the 1.58-bit barrier for ternary large language models.

The arXiv preprint 2609.16338, titled 'Breaking the 1.58-bit Barrier for Ternary LLMs,' presents research on ternary-weight large language models, which use roughly 1.58 bits per weight. The source text contained only the title and Hacker News engagement data (56 points, no comments), so further technical details are not available.

Hacker News · AI · 1h agoAI researchHN 56↑ · 0 comments

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 papers · 7d agoAI research

[0day-rubbish] core-admin 1.0.164 (build 16468) Systemic shell command injection via ineffective quote escaping (8.8)

0day Rubbish discloses a CVSS 8.8 shell command injection in core-admin 1.0.164 via ineffective quote escaping, enabling authenticated remote code execution.

0day Rubbish Research Team publicly disclosed a systemic shell command injection (CWE-78) in core-admin 1.0.164 (build 16468). The flaw stems from ineffective quote escaping and scores 8.8 (AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H). The disclosure does not mention a CVE identifier or observed exploitation in the wild.

Full Disclosure · 8d agoVulnerability1

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

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 News · 14d agoResearchCVE-2021-318862

What Else Needs Fixing? Exploring Cost-Effective Test-Time Compute for Revision Propagation in Artifacts Generated Through Conversation

A new benchmark shows LLMs reach 68.3-93% accuracy propagating local revisions across conversationally generated artifacts, with parallel-sample selection most cost-effective.

The paper introduces a benchmark for revision propagation: when users request a local change, LLMs must identify dependencies and update all affected parts of an artifact generated through conversation, where context lives in the chat history. Nine revision methods, including sequential reflection and parallel sampling variants, were evaluated on gpt-oss-20b/120b, gpt-5.4-mini, and qwen3.5-9b/27b/122b. Baselines scored 68.3-93% accuracy, and selecting among three parallel samples via LLM-based or medoid selection improved accuracy by 2.2-9.7% as the most cost-effective test-time compute strategy. Code and dataset are released.

Hugging Face daily papers · 14d agoAI research

E2A-Bench: Benchmarking Evidence-to-Action Reliability in Financial Chart Reasoning

E2A-Bench, a 969-query financial chart reasoning benchmark, finds VLMs fail evidence-to-action consistency, with fine-tuning amplifying BUY:SELL bias 4-6x.

E2A-Bench is a 969-query benchmark built from 323 HS300 constituents across three input modalities with deterministic OHLCV-derived evidence anchors, evaluating grounding, reasoning-action consistency, evidence-confidence calibration, and directional coverage via UCR, RCI, ECI, and NDR metrics. Testing 20 VLMs showed the lowest-hallucination model ranked near the bottom on coverage with only 6.4% directional coverage, and oracle-aided verification reduced unsupported claims but could collapse coverage. Financial fine-tuning amplified the BUY:SELL ratio by factors of 4.21 to 4.68 across base-fine-tuned pairs.

Hugging Face daily papers · 4d agoAI research

New AI Attack Hides Malicious Instructions in Normal-Looking Text to Evade Safety Filters

Check Point researchers show crafted prose hides policy-violating instructions that bypass all tested LLM gatekeepers, including GPT-4o mini and Llama Guard 3.

A new prompt-crafting technique embeds malicious payloads inside grammatical, natural-looking text without Base64, invisible Unicode, or obvious encodings, defeating lightweight pre-screening gatekeepers. In testing, all four evaluated gatekeeper models—gpt-4o-mini-2024-07-18, gpt-oss-safeguard:20b, claude-3-haiku-20240307, and llama-guard3:8b—classified the crafted wrappers as safe at a 100% bypass rate across 23 obfuscated prompts. GPT-5 Thinking in high-reasoning mode recovered and acted on the hidden instruction in 17 of 18 tests (~94.4%), often spending over a minute and multiple Python executions. Researchers recommend paraphrasing untrusted input, hardening gatekeeper policies, and applying defense-in-depth controls for agentic deployments.

GBHackers · 5d agoAI safety & security 2 sources

Chinese espionage groups swarm to exploit triple-link chain of zero-days

At least four China-aligned espionage groups chained three zero-days in Chromium browsers and Windows ALPC for espionage since late August.

Proofpoint observed at least four state-aligned threat groups, starting with TA412/Violet Typhoon/APT31 on August 28, chaining three zero-days in the 'BlueMoon' exploit chain targeting Chrome, Chromium-based browsers and Microsoft Windows. The chain includes RCE flaws in Chromium's JavaScript engine (CVE-2026-85046, CVE-2026-87491) and a Windows Advanced Local Procedure Call privilege-escalation zero-day (CVE-2026-85880), enabling sandbox code execution, sandbox escape and system privileges. APT31 delivered the chain via phishing links to NGOs, mining and commodity trading firms in the US, installing a browser extension disguised as Google Gemini to surveil activity and steal credentials. Other groups (UNK_LateNight, UNK_DoubleCheck, UNK_QuietRacket) targeted US aerospace, Vietnamese manufacturing, and Indonesian and Singaporean organizations; fewer than 20 victims were directly observed but the true count is likely higher.

CyberScoop · 7d agoExploit / PoC in the wild 3 sourcesCVE-2026-85046CVE-2026-87491CVE-2026-858802· 1 read

CiteShade: Citation Laundering in Multi-Source Retrieval-Augmented Generation and Its Counterfactual Defense

CiteShade attack makes RAG models cite trusted sources for attacker-chosen wrong answers, raising wrong-answer rate from 0.01 to 0.68.

CiteShade is presented as the first citation laundering attack against multi-source retrieval-augmented generation: an attacker controlling a single source induces a wrong answer falsely attributed to a trusted source, even while correct evidence remains in context. The attack is formalized via three necessary conditions (retrieval, generation, citation) constructible without any instructions, raising wrong-answer rate from 0.01 to 0.68 on multi-hop QA, with source deletion confirming the malicious source as causal driver. Vulnerability tracks a model's citation propensity rather than scale, reaching CLR 0.84 with explicit instruction and 0.64 without on the most citation-prone model. Perplexity filtering and citation-support checking prove insufficient; the authors propose a counterfactual defense verifying which source actually drove the answer.

arXiv cs.CR · 2d agoAI safety & security1

ChatGPT flaw lets attackers pull Gmail data across accounts via a hidden channel

Check Point found a ChatGPT flaw letting attackers read victims' Gmail and connected-app data via hidden cross-session instructions; OpenAI patched it.

Check Point Research discovered a covert cross-account command channel in ChatGPT's code execution environment, where containers meant to be isolated shared metadata through an internal service based on JFrog Artifactory. In a proof of concept, a victim's session was tricked into retrieving Gmail email data and relaying it to an attacker-controlled session during an ordinary-looking interaction, with reach extending to any connected apps the session was authorized for, including Google Drive, Microsoft Teams, and GitHub. OpenAI fixed the issue and decommissioned the internal service; the same shared infrastructure was also involved in the separately disclosed Hugging Face compromise, though via different techniques.

CSO Online · 7d agoAI safety & security

[webapps] CorgetGpsDget 2_3.2 - OS Command Injection

Exploit-DB publishes OS command injection exploit for the obscure CorgetGpsDget 2_3.2 web application.

A public exploit demonstrates OS command injection in CorgetGpsDget version 2_3.2. The flaw could allow attackers to execute arbitrary operating system commands on the hosting server. The product appears to have limited deployment, reducing real-world exposure.

Exploit-DB · Aug 10, 2026Exploit / PoC

[0day-rubbish] Accurate Online Private Cloud on-prem (current) Unauthenticated Hessian deserialization leading to JNDI remote class loading (9.8)

0day Rubbish disclosed an unauthenticated Hessian deserialization flaw in Accurate Online Private Cloud on-prem allowing JNDI remote class loading, rated 9.8.

The 0day Rubbish Research Team publicly disclosed an unauthenticated Hessian deserialization vulnerability in the current on-premises release of Accurate Online Private Cloud. The flaw lets unauthenticated attackers trigger JNDI remote class loading, a path that typically yields remote code execution. The issue carries a CVSS 9.8 rating. No CVE identifier or evidence of in-the-wild exploitation was included in the disclosure.

Full Disclosure · 8d agoVulnerability

Detect and disrupt AI-themed attacks with Microsoft Defender

Microsoft Threat Intelligence reports criminal campaigns impersonating ChatGPT, Copilot, Claude, and DeepSeek in phishing, AiTM, and malvertising attacks reaching 100,000 emails daily.

Microsoft Threat Intelligence observed a growing set of campaigns that abuse trust in popular AI brands: a ChatGPT-themed phishing campaign sent up to 100,000 emails in one day to steal payment card data, and a Claude-themed campaign used adversary-in-the-middle techniques to harvest credentials and access tokens. Other campaigns included malvertising for a fake AI Windows plugin delivering the Vidar stealer and fraudulent DeepSeek installers distributed via GitHub. Initial access broker Storm-3075 used AI-themed malvertising to distribute payloads for multiple downstream actors, and Microsoft notes the AI services themselves were not compromised. Microsoft also details Defender protections such as Safe Links, Safe Attachments, and attack disruption against these multi-stage lures.

Microsoft Security Blog · 6d agoPhishing & fraud in the wild1