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Prolific Microsoft 0-day hunter drops CrowdStrike Falcon exploit PoC

Researcher Nightmare Eclipse released a PoC for FalconFlank, a privilege escalation zero-day in CrowdStrike Falcon's Office macro remediation feature.

Researcher Nightmare Eclipse published a zero-day PoC dubbed FalconFlank targeting CrowdStrike Falcon's Microsoft Office malicious macro removal feature, achieving privilege escalation on fully updated Windows 11 25H2 and Windows Server 2025 with Optimal Protection and macro removal enabled. Kevin Beaumont independently confirmed the exploit works. The same researcher also released HardBreacher, an elevation-of-privilege bug in Kaspersky Endpoint (since fixed via update), PrettyPrague, an Avast Sandbox flaw that dumps the SAM database for a SYSTEM shell (Gen Digital is developing a patch), and GreenSection, an Nvidia memory corruption bug that crashes systems. CrowdStrike advises customers to disable the Suspicious Macro Removal Windows policy while it investigates.

The Register · Security · 12d agoExploit / PoC

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 papers · 11d agoAI research1

I Am No One: Style-Aware Paraphrasing for Text Anonymization

Prompt-driven style-aware paraphrasing with LLMs cuts authorship attribution F1 by 60-70% while preserving content quality.

The paper proposes a style-aware, prompt-driven anonymization approach using pretrained LLMs to build compact stylistic profiles from minimal samples and rewrite text to suppress identifiable style markers while preserving meaning. It addresses stylometric re-identification risks in anonymized text, including ASR transcripts of meetings and call-center calls where leakage persists after acoustic anonymization. Across blog and review datasets, the approach reduces authorship attribution F1 by 60-70%, substantially outperforming both DP-based and non-DP baselines while maintaining readability.

arXiv cs.CR · 5d agoResearch

Authorities arrest 2 alleged members of prolific hacking group TeamPCP

Authorities arrested two alleged TeamPCP members whose hacking group infected over 1,000 organizations via supply-chain attack campaigns.

Law enforcement arrested two individuals suspected of membership in TeamPCP, a prolific hacking group. According to Ars Technica, the group infected more than 1,000 organizations through a relentless supply-chain attack campaign. The arrests mark a notable step in efforts to disrupt the group's operations.

Ars Technica · Security · 18d agoPolicy & legal in the wild

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 · 11d agoAI research1

Re: AI slops from Eve

David Wheeler's oss-security reply argues AI will make attacks far cheaper and more prolific, urging defenders to protect all IT systems, not just critical ones.

David A. Wheeler posted an opinion reply on the oss-security mailing list in a thread titled 'AI slops from Eve'. He agrees critical IT systems need protection but stresses that all systems have always required defense, since many who assumed they would not be attacked were successfully attacked. He predicts AI-enabled attacks will be painful for many over the next few years because AI greatly reduces the cost of attacks. He also notes AI simultaneously helps with finding and fixing issues.

oss-securityupdated · 2d agofirst · 3d agoIndustry 12 sources1

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.CL · 6d agoAI research

Engineered Persuasion: Evaluating Personalized Pretexts in LLM-Generated Spear Phishing

A study of 180 US workers found each LLM phishing personalization level raised click-intention odds by 28%, but credibility depends on context fit.

The arXiv paper evaluates how personalized pretexts in LLM-generated spear phishing affect perceived credibility, using 180 US working adults across 1,436 evaluations of emails with four cumulative personalization levels, from workplace context to shared-project details. Convincingness rose 2.40 points per level in sensitivity analysis and click-intention odds increased 28% per level, while non-clickers shifted toward deleting rather than reporting. Qualitative coding showed details matching the recipient's role and routines supported credibility, whereas incorrect, vague, or channel-inappropriate details raised suspicion. The authors argue personalization effectiveness depends on pretext fit, with implications for workplace security training.

arXiv cs.CR · 12d agoResearch

ATF confirms cyberattack hit system containing info on its investigation targets

Qilin ransomware group claimed breaching the ATF, exposing data on investigation targets; the agency says a standalone system was hit with no mission impact.

The Bureau of Alcohol, Tobacco, Firearms and Explosives confirmed a cyberattack on a standalone system holding information about targets of ATF investigations, designated a major incident, with no impact on case management, lab, or eForms systems. Qilin, a Russian-speaking affiliate-based ransomware group, claimed responsibility, though ATF declined to confirm involvement or the root cause. Qilin has claimed hundreds of victims across 60+ countries since 2022 and partners with Scattered Spider and Moonstone Sleet.

CyberScoop · 18d agoRansomware in the wild

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

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.CL · 5d agoAI research

Fine-tuning a 350M Model for Better Structured Outputs in 100 GRPO Steps

Hugging Face guide fine-tunes a 350M-parameter model with 100 GRPO steps to improve structured output reliability.

A Hugging Face blog post demonstrates fine-tuning a 350M-parameter model using GRPO (Group Relative Policy Optimization) with TRL over 100 training steps. The stated goal is more reliable structured outputs from small language models. No article body was available, so details beyond the title are limited.

Hugging Face Blog · 13d agoAI tools & infra

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

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

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

arXiv cs.AI / cs.LG / cs.CL · 8d agoAI research

What We Learned by Reproducing 2,200 papers from ICML

Hugging Face shares lessons from openly reproducing 2,200 ICML 2026 papers, examining reproducibility and open implementation practices in machine learning research.

Hugging Face published a retrospective on its open reproduction effort covering 2,200 papers from ICML 2026. The post summarizes lessons learned about reproducibility and building open, community-driven implementations of published machine learning research. No detailed article text was available in the feed.

Hugging Face Blog · Aug 13, 2026AI research

Ukrainian hacker gets four years in US prison over Conti ransomware attacks

Oleksii Lytvynenko was sentenced to four years in the US for his role in Conti ransomware attacks against 1,000+ victims.

Ukrainian national Oleksii Lytvynenko, 44, was sentenced to four years in a US prison for his role in the Conti ransomware operation, having pleaded guilty in June. He worked as a hacker and developer for Conti, personally targeting at least a dozen companies and building a malware loader, and stolen data from eight US victims and four others overseas was found in his accounts. Between 2020 and 2022, Conti attacked organizations across 47 US states and 31 countries, with the FBI estimating victims paid more than $150 million in ransoms by January 2022. Lytvynenko was arrested in Cork, Ireland in July 2023 and extradited after several years in Irish custody; four other alleged Conti members were charged in a separate September 2023 indictment.

The Recordupdated · 4d agofirst · 4d agoPolicy & legal 7 sources1

Companies may be measuring phishing resilience the wrong way

Pistachio's 2026 report analyzing 648 organizations finds click rates alone mislead; combining clicks, credential submission, and reporting better measures phishing resilience.

Pistachio's Phishing Behaviour Report 2026 analyzed 648 organizations and 123,692 users across 354,962 simulations between June 1, 2025 and May 31, 2026. It found click and credential-submission rates rose during the first six months of training before declining, and from the six-month peak to the 12-month stage clicks fell 27% while credential leaks dropped 41%. The report-to-click ratio increased from 1.3 at three months to 1.8 at 12 months, framing employees as an active detection channel. Departmental analysis showed Construction had the highest cumulative click rate (41.31%) and Health the lowest report rate (13.17%), supporting more targeted training.

Help Net Security · 5d agoPhishing & fraud

Early 764 member sentenced to 77 years, longest prison term to date for a nihilistic violent extremist

Kyle Spitze, an early 764 member, was sentenced to 77 years for producing CSAM, the longest sentence for a nihilistic violent extremist.

Kyle William Spitze, an original member of the 764 nihilistic violent extremist network and administrator of the Harm Nation offshoot, was sentenced to 77 years in federal prison. He pleaded guilty in December 2024 to producing child sexual abuse material, possession of CSAM, and distributing animal crush videos, victimizing dozens of girls through coercion, doxing and swatting threats. Investigators found roughly 25 photo albums of abuse imagery on his phone and evidence of animal torture. The Justice Department framed the sentence as a signal in a broader enforcement push against 764, which has seen multiple members arrested or sentenced since 2025.

CyberScoop · 26d agoPolicy & legal

Plug 'n' Pray: Agentic LLM-based Detection of Potential Log File Exposures in Third-Party Content Management System Plugins

Agentic LLM analysis validates 79 log file exposures across 62 of the 300 most-installed WordPress plugins, covering 250M+ active installations.

Researchers built an agentic LLM-based framework combining static and dynamic analysis to automatically detect insecure log files created by WordPress plugins. Scanning the 300 most-installed plugins, which account for roughly 75% of all active installations in the official ecosystem, it produced 81 findings with 79 manually reproduced across 62 plugins. Insufficiently secured log files can disclose credentials and personal data and have led to website compromises. The authors derive a taxonomy of log path and protection patterns and best practices, finding multi-layered protection often absent.

arXiv cs.CR · 20h agoResearch

McKesson copes with fallout from data theft extortion attack

McKesson discloses a data theft extortion attack by ShinyHunters affecting oncology and medical-surgical customers, with a reported $55 million demand.

McKesson disclosed that attackers gained access to some of its third-party applications and stole data associated with a subset of customers in its oncology, multispecialty, and medical-surgical business units; the intrusion ran for four days from August 21 and was discovered August 25. ShinyHunters claimed responsibility and listed McKesson on its data-leak site, reportedly demanding more than $55 million with a September 1 deadline. Flashpoint analysts say the group typically uses social engineering and identity weaknesses with valid credentials to access cloud-hosted environments, making the intrusion hard to detect. McKesson, which distributes about one-third of pharmaceuticals used in North America with $403.4 billion in annual revenue, says operations continue and it has reasonable assurance of no ongoing unauthorized activity.

CyberScoop · 15d agoData breach in the wild

ActReview: Rebuttal-Guided Training Data and Rubric Rewards for Actionable Peer Review Generation

ActReview post-trains Qwen3-8B-Base on OpenReview rebuttals to generate actionable peer-review feedback with grounded revision suggestions, benchmarked on 1,000 curated instances.

The paper defines Actionable Peer-review Generation as diagnostic claim generation plus revision suggestion generation and introduces ActReview, a rebuttal-guided post-training framework. From OpenReview review-rebuttal threads the authors build ActReview-40K, aligning reviewer weaknesses with author responses grounded in localized paper evidence, and post-train Qwen3-8B-Base with multi-task SFT followed by GRPO using weakness-specific rubric rewards. They also release ActReview-Bench, a human-curated 1,000-instance benchmark, on which ActReview outperforms prior specialized review-generation models on actionability and grounding while remaining competitive with strong prompt-based LLMs. Human evaluation confirms improved revision usefulness but identifies a remaining gap in technical accuracy.

Hugging Face daily papers · 8d agoAI research

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 Online · 7d agoAI safety & security1

The story behind the intelligence

Cisco Talos newsletter features adversary-engagement podcast, flags AI guardrail 'safety penalty' slowing defenders, and recaps McKesson breach and PaperCut patching headlines.

The Threat Source newsletter spotlights the Beers with Talos podcast, in which researcher Azim Khodjibaev describes maintaining eight dark-web personas to identify prolific cybercriminals and support disruption efforts. Talos also argues frontier AI guardrails impose an AI 'safety penalty', citing a July 2026 incident where Hugging Face's primary cloud LLM refused to analyze forensic breach data and delayed response. Recapped headlines include ShinyHunters claiming theft of 284 million patient records from McKesson via vishing and Okta account takeover, Anthropic warning Claude users about infostealer malware, and PaperCut issuing emergency patches for chained vulnerabilities.

Cisco Talos · 12d agoIndustry

Bulk AbuseIPDB reporting using command-line tools

A blogger shows how to bulk-report distributed botnet IPs scraping a self-hosted Gitea instance to AbuseIPDB using bash, awk, and jq.

The author's self-hosted Gitea instance was scraped by distributed bots using random IPs worldwide and randomized, often nonexistent User-Agent strings, generating heavy request load for days. The write-up demonstrates filtering Traefik access logs (CLF and JSON) with grep, awk, and jq to extract offending IPs, tagging them with AbuseIPDB category 19 (Bad Web Bot), deduplicating them, and building a CSV for the Bulk Reporter tool. Reports can then be submitted through the AbuseIPDB bulk-report API, respecting the 5,000-report daily limit.

Lobsters · security · 6d agoTools1

Y Combinator’s Garry Tan wants U.S. open-weight AI labs to ‘distill’ frontier models, too

Y Combinator CEO Garry Tan urges US open-weight labs to distill frontier models and regulators to stay out, countering Anthropic's crackdown calls.

Y Combinator CEO Garry Tan told CNBC he would "do nothing" about Chinese labs distilling frontier models and floated an "American distillation regime" letting US open-weight labs do the same to American frontier labs. Anthropic this week released its second report alleging Chinese labs conduct "illicit distillation attacks" using hidden identities, fraud, and stolen credentials, and CEO Dario Amodei has called for US regulators to crack down. Tan argued closed labs cannot dictate what customers do with API outputs, noting frontier labs trained on copyrighted material without permission, and called a single monolithic proprietary provider the true AI doomer scenario.

TechCrunch · AI · 4d agoAI industry

Meta FAIR Introduces AI Research Preference Models (RPMs): Ranking ML Experiments Before Spending GPU Hours

Meta FAIR, Oxford and UCL introduce Research Preference Models that rank unexecuted ML experiments, lifting AIRS-Bench scores from 0.684 to 0.729 and cutting compute ~1.6×.

Researchers from Meta FAIR, Oxford, and UCL introduce Research Preference Models (RPMs), which use frozen pretrained LLMs (Qwen3.6-27B backbone, no fine-tuning) to rank unexecuted experiment candidates and execute only the winner of a pairwise knockout tournament. Two variants shipped: an inference-only LLM-as-a-judge and an agentic variant that runs small pilot experiments in an H200 sandbox. On AIRS-Bench (20 tasks, 24 hours on one H200, 10 seeds), scores rise from 0.684 (random) to 0.711 and 0.729 versus a 0.748 validation oracle, and both variants reach the baseline's 24-hour score in roughly 15 hours. The team reports new SOTA on WinoGrande (94.1% with Agentic RPM) and SVAMP (95.7% with inference-only).

MarkTechPost · 9d agoAI research

Nutex Health Says Patient Data Stolen, Hackers Threaten Leak

The Gentlemen ransomware gang claims breach of US healthcare provider Nutex Health, exfiltrating patient and employee data and threatening publication.

Nutex Health disclosed in an SEC 8-K filing that an unauthorized third party accessed and exfiltrated patient, employee, credentialed provider, business, and financial data from company servers, and threatened to publish it. The Gentlemen ransomware group listed Nutex on its leak site; a class action was filed August 27 and Edelson Lechtzin LLP is separately investigating. Nutex operates over 27 facilities in 12 states and served nearly 100,000 patients in the first half of 2026, with no material operational impact identified so far.

Infosecurity Magazine · 13d agoRansomware

LongAgent: History-Guided Agentic Search for Longitudinal Outcome Prediction

LongAgent autonomously searches variable sets and temporal windows to predict longitudinal medical outcomes, beating the strongest non-agent baseline on synthetic data.

The paper proposes LongAgent, an agent-based method that searches over combinations of variable sets, temporal windows and aggregation functions for outcome prediction on heterogeneous medical longitudinal data. It uses a history memory of previous searches and numerical evidence to guide exploration. On synthetic data it achieves mean RMSE 1.7376, improving over the best non-agent baseline by 0.0151 (95% CI [0.0045, 0.0260]; p=0.0273), and performs comparably to the best baseline on a real clinical dataset.

arXiv cs.AI / cs.LG / cs.CL · 1d agoAI research

ShinyHunters hackers claim breach of Florida "DAVID" DMV database

ShinyHunters claims it breached Florida's DAVID DMV database via a password-reset flaw, stealing 200,000+ driver records including SSNs.

The ShinyHunters extortion gang added Florida FLHSMV to its leak site, claiming theft of over 200,000 driver records from the DAVID platform since September 3. As proof, the group published a screenshot of Jeffrey Epstein's DMV record showing address, Social Security number, driver's license ID, and registered vehicles. The gang says it compromised DMV employee and FBI agent accounts via a password-reset flaw and iterated through records by ID. Access has reportedly been lost and the flaw is being patched, but ShinyHunters expects to announce breaches of other states' DMV platforms.

BleepingComputer · 7d agoData breach

IdeaAMBIG: Benchmarking Implementation-Critical Gaps in Research-Idea Specifications

IdeaAMBIG benchmark with 660 instances measures whether LLMs can spot and fix underspecified research-method details for faithful implementation.

Researchers introduce IdeaAMBIG, a benchmark of 660 evidence-grounded instances (163 real-world gaps from reproducibility reports and GitHub issues, 497 controlled synthetic gaps) built from papers, codebases, and reproduction artifacts. It evaluates codification-readiness assessment, defect localization, and clarification action generation. Across 13 LLMs, the best model achieved only 9.6% Macro Defect Recovery Rate on real-world instances but 80.6% clarification success when given the annotated defect. An oracle study showed gold resolutions raise the codification-ready rate from 14% to 98%, identifying defect localization as the main bottleneck.

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

Two Alleged ‘TeamPCP’ Hackers Arrested in Australia

Australian Federal Police arrested two alleged TeamPCP members, a data extortion group tied to prolonged software supply chain attacks.

The Australian Federal Police arrested two unnamed suspects from Western Australia, aged 21 and 23, believed to be members of TeamPCP. The group is described as a cybercrime and data extortion syndicate blamed for the longest-running spree of software supply chain attacks, allegedly creating malicious open-source software that hit thousands of global businesses. KrebsOnSecurity had identified the 21-year-old suspect in June and had been in contact with him.

Krebs on Security · 19d agoPolicy & legal

Phishing Research Challenges Conventional Security Awareness Testing

Pistachio's 2.47 million phishing simulations across 1,200 organizations show click rates alone mislead, with 30% of IT staff clicking and leak rates more predictive.

Between June 2025 and May 2026, Pistachio sent 2.47 million simulated phishing attempts to more than 123,000 employees at over 1,200 organizations, analyzing click, credential-leak and reporting behavior. Click rates ranged from 26% in Design to 41% in Construction; 30% of tech development and IT staff clicked at least once, while financial services were the most resilient sector. The report argues that click rate alone creates a false sense of security and that combined click, leak and report trends are better resilience indicators.

SecurityWeek · 4d agoResearch

⚡ Weekly Recap: AI-Powered PLC Attacks, GitLab Attacks, Stripe Key Leaks and More

US agencies warn of AI-assisted attacks on exposed Siemens PLCs; the week also saw GitLab CVE-2026-19478 exploited and trojanized npm packages found.

The weekly recap leads with a US government warning that threat actors use AI-generated scripts and Censys/ZoomEye scanning to attack internet-exposed Siemens S7 PLCs in water, energy and manufacturing, calling it an active threat. Other stories include active exploitation of GitLab CVE-2026-19478 (CVSS 9.4, unauthenticated project rewriting), 14 trojanized npm packages delivering the RedC2 4.0 Linux backdoor, and the Zombie Card attack that revives expired Visa cards for contactless payment fraud. It also covers suspected Russian clusters UNC6293, UNC7005 and UNC5976 phishing campaigns, a faster Cloudflare Workers Spectre JWT leak, and a bespoke Cl0p JSP web shell deployed after exploiting PTC Windchill flaws.

The Hacker News · 19d agoThreat actor in the wildCVE-2026-194781

StepAudio 3 Music Technical Report

StepAudio 3 Music introduces long-form text-controlled music generation using ABC-notation planning and flow-matching diffusion, ranking near the top music arena.

StepAudio 3 Music generates long-form, text-controlled music using a 50-Hz single-codebook tokenizer with 65,536 entries and a flow-matching diffusion Transformer over VAE latents. A Mixture-of-Experts autoregressive model first plans an arrangement in ABC notation (ABC-CoT) before predicting music tokens. With DPO fine-tuning, it tops AudioBox content and production quality scores and reaches Quality Elo 1105 on the Artificial Analysis Music Arena, behind Suno V5.5 and Mureka. Generation covers songs, accompaniment from dry vocals, and cover synthesis up to 5 minutes 30 seconds at 48-kHz output.

Hugging Face daily papers · 5d agoAI research

Subgroup Membership Inference Audits of Differentially Private Synthetic Text

Audits of 32 differentially private synthetic-text releases show subgroup membership leakage is concentrated in few records and systematically underestimated by average-case attacks.

The paper defines a subgroup-targeted membership inference game in which the target pool is an explicit parameter, to audit residual leakage in differentially private synthetic text releases. The audit instantiates 32 proxies across four datasets, three generators (DP-SGD fine-tuning, API-based prompting, and activation steering), and five privacy budgets. DP substantially reduces average leakage at every budget, but remaining leakage is concentrated: roughly a tenth of records carries about 40% of it, and the noise removes more measured leakage from random records than from high-risk ones. Which records leak depends on the release mechanism, so record-level risk cannot be assessed independently of the release.

arXiv cs.CR · 7d agoResearch