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4.1 Million Impacted by AdaptHealth Data Breach

AdaptHealth disclosed a breach affecting 4,115,802 people after a socially engineered attacker stole health and insurance data from cloud-based patient systems.

A threat actor used social engineering to hijack a user session at a third-party contractor and gained access to AdaptHealth cloud applications, including patient management and document storage systems, in early June. Names, contact and demographic information, and health and health insurance data were exfiltrated; Social Security numbers and financial information were not affected. AdaptHealth reported 4,115,802 affected individuals to HHS, whose breach portal listed the incident this week; Baylor Genetics separately reported 2,810,878 individuals affected in a related June healthcare breach.

SecurityWeek · 6d agoData breach 2 sources

HHS Releases Updated Security Risk Assessment Tool

HHS OCR and ONC released version 3.7 of the Security Risk Assessment Tool for healthcare organizations.

The U.S. Department of Health and Human Services Office for Civil Rights (OCR) and the Office of the National Coordinator for Health IT (ONC) released version 3.7 of the Security Risk Assessment (SRA) Tool. The tool helps covered entities conduct HIPAA security risk assessments. ONC and OCR provided guidance on the updates.

DataBreaches.net · 3d agoTools

Threat Assessment: Ryuk Ransomware

Unit 42 assesses Ryuk ransomware amid a CISA/FBI/HHS alert on threats to U.S. healthcare, including the UHS attack that disrupted hospital operations.

A joint CISA, FBI, and HHS alert on October 28, 2020 warned of an imminent threat to U.S. healthcare from operators deploying Trickbot and Ryuk ransomware. Universal Health Services reported a Ryuk attack that disrupted all U.S. UHS sites for weeks, with similar incidents at hospitals in Oregon and New York. Ryuk typically arrives after Trickbot or BazaLoader infections delivered via malicious email, and operators enumerate networks with PowerShell and WMI before encryption. The Trickbot Anchor_DNS module performs DNS tunneling for C2, using connectivity checks to benign domains like ipinfo.io and checkip.amazonaws.com.

Palo Alto Unit 42 · Aug 17, 2026Ransomware in the wild

Attackers Access Aesto Health AWS Infrastructure, Exposing 9.5 Million Records

Attackers accessed part of Aesto Health's AWS infrastructure between December 2-18, 2025, exposing personal and health data of over 9.5 million patients.

Aesto Health, a Birmingham, Alabama healthcare technology company, disclosed a breach affecting 9,540,683 individuals whose protected health information was stored in its AWS infrastructure. Attackers had access from around December 2 to December 18, 2025; the incident was discovered on December 18, 2025 and confirmed on May 26, 2026 after a forensic investigation. Exposed data may include names, birth dates, medical and insurance details, financial account information, government ID numbers and, for a limited number of people, Social Security numbers. Aesto reported the incident to HHS and says it found no evidence of identity theft or financial fraud.

Security Affairs · 15d agoData breach

FTC rescinds policy requiring health apps to notify customers after a breach

The FTC unanimously rescinded its 2021 policy statement that required health and fitness apps to notify users after health-data breaches.

The FTC voted to rescind a September 2021 Biden-era policy statement that extended federal health-data breach notification rules to health apps, fitness trackers, and connected devices, which had exposed violators to fines of $43,792 per violation per day. The 2021 statement, adopted in a divided 3-2 vote under then-chair Lina Khan, cited HIPAA coverage gaps for consumer health applications. The commission said the statement provided minimal benefit, was superseded by rulemaking, and aligns with the White House deregulatory agenda.

CyberScoopupdated · 6d agofirst · 6d agoPolicy & legal 2 sources

Medusa ransomware tallies hundreds of new victims, says updated advisory on group’s tactics

CISA, FBI, and HHS updated their Medusa ransomware advisory, reporting over 500 victims and detailing the gang's access-broker and exploit tactics.

A joint advisory update from CISA, the FBI, and HHS expands the March 2025 Medusa guidance, drawing on a year of FBI investigations. The ransomware-as-a-service group's known victim tally grew from more than 300 to more than 500 between March 2025 and April 2026, with the Healthcare and Public Health sector frequently hit. Medusa pays access brokers $100 to $1 million, has exploited flaws such as Fortra GoAnywhere and BeyondTrust vulnerabilities, and leverages newly announced exploits within 24 hours, sometimes a week before public disclosure. The group uses living-off-the-land techniques, remote monitoring and management software, and RDP for lateral movement, and has been linked to actors including Microsoft-tracked Storm-1175 and North Korean hackers targeting healthcare.

CyberScoop · 29d agoRansomware in the wild

Medusa ransomware gang has hit over 500 organizations, CISA warns

FBI, CISA, and HHS warn Medusa ransomware has hit over 500 organizations across critical infrastructure since June 2021, using phishing and unpatched flaws.

An updated joint advisory from CISA, FBI, and HHS states Medusa ransomware has affected more than 500 organizations, spanning healthcare, defense, manufacturing, government, IT, financial services, education, insurance, and legal sectors. Since early 2023 Medusa has operated a ransomware-as-a-service affiliate model and buys access from initial access brokers for $100 to $1 million. Affiliates gain entry via phishing and unpatched internet-facing software, exploiting newly disclosed flaws in ScreenConnect, Fortinet EMS, Fortra GoAnywhere, and BeyondTrust within 24 hours. The group runs double extortion, giving victims 48 hours before leak-site publication, with $10,000 in cryptocurrency buying a one-day delay.

Help Net Security · 28d agoRansomware in the wild

Large Language Models for HVAC Operations in Building Energy Systems: A Critical Review of Methods, Applications, and Deployment Readiness

Systematic review of 66 studies finds LLMs for HVAC operations are mostly research-stage, with no ready-now deployment and only four pilot-level studies.

A critical review of 66 peer-reviewed studies from 2023 to March 2026 examines LLMs for HVAC operations in building energy systems. Only four studies reach pilot-level evidence, none reports sustained operational deployment, and 63 of 66 are research-only. Conventional ML, MPC, and RL remain dominant for high-frequency control and short-horizon forecasting, and the evidence supports LLMs primarily as semantic and workflow layers rather than autonomous controllers.

arXiv cs.AI / cs.LG / cs.CL · 12d agoAI research

280,000 Impacted by Premier Medical Group Data Breach

New York healthcare provider Premier Medical Group is notifying 282,075 patients that personal and medical information was stolen in a June breach.

New York healthcare provider Premier Medical Group is notifying 282,075 patients whose personal and medical data was stolen in a June breach. Attackers accessed certain files on June 14 after some systems were disrupted, but PMG has not disclosed how the attack occurred or who was responsible. Exposed data includes names, contact information, dates of birth, treatment and diagnostic details, medication information, and health insurance details. PMG reported the incident to HHS, which added it to its public breach portal this week.

SecurityWeek · 6h agoData breach in the wild

Hackers Frequently Target Healthcare and Finance Orgs

A new Huntress survey indicates threat actors frequently target healthcare organizations and banks because of the highly personal data they hold.

Huntress published survey findings indicating that healthcare organizations and banks are frequent targets for threat actors. The piece attributes this to the highly personal information these sectors handle. The article is framed around cyberattack readiness rather than a specific incident.

Huntress · 15d agoIndustry

Japan’s Health Ministry to Strengthen Cybersecurity Measures at Hospitals

Japan's Health Ministry requested ¥13.7 billion for fiscal 2027 to strengthen hospital cybersecurity with network protections and dedicated specialists amid rising attacks.

Japan's Health, Labor and Welfare Ministry included ¥13.7 billion in its fiscal 2027 budget request to strengthen cybersecurity at hospitals. The measures aim to protect hospital networks and deploy cybersecurity specialists, responding to a surge in cyberattacks on medical institutions. The plan was reported by The Yomiuri Shimbun.

DataBreaches.net · 9d agoPolicy & legal

Show HN: Panel – A research workspace where the agent can build its own panes

Panel is an open-source research workspace where AI agents dynamically build their own panes, posted on Hacker News.

Panel, shared as a Show HN project on GitHub, is a research workspace in which the agent can construct its own panes rather than using a fixed interface. The post received 41 points and 8 comments on Hacker News. It targets agentic research workflows with a dynamically generated UI.

Hacker News · AI · 1d agoAI tools & infraHN 41↑ · 8 comments

Week in review: Records allegedly stolen from Azure tenants, Medusa ransomware hits 500+ orgs

Week in review: Medusa ransomware hit 500+ orgs per CISA, millions of Azure tenant records allegedly stolen, SafePal and French tax authority breaches disclosed.

Help Net Security's weekly roundup covers the FBI, CISA, and HHS joint advisory update reporting Medusa ransomware has breached more than 500 organizations since June 2021, and threat actor TheHatman's claim of millions of employee records stolen from Azure tenants of Fortune 500 firms including McDonald's, Vodafone, Kyndryl, and Tata Consultancy Services, per Hudson Rock. It also covers the SafePal breach affecting 39,798 customers, France's DGFiP breach exposing data on 678,000 individuals, and UT San delaying its fall semester after a cyberattack. Security items include critical unauthenticated GitLab flaw CVE-2026-19478, an actively exploited patched macOS Screen Sharing flaw deploying a cryptominer, US charges against 17 Mabna Institute Iranian hackers over 31TB of stolen academic data, and Google Mandiant's AI agents finding 100+ high-severity vulnerabilities.

Help Net Security · 24d agoData breach in the wildCVE-2026-19478

Officials disrupt Chinese espionage operation that hit multiple federal agencies

FBI and DOJ seized QTFY infrastructure, disrupting a Chinese state-sponsored group that compromised federal agencies and critical infrastructure since 2018.

Authorities seized three domains powering QScan and QTRouter, the hacking suite of QTFY, a Chinese government-funded group operating through front company Nanjing Xinjiuwei Network Technology. Targets include the Departments of Energy, Justice, and Health and Human Services, the Federal Reserve, NASA, NIH, financial institutions, defense contractors, utilities, telecoms, and hospitals; the group exploited zero-days in Ivanti, Pulse Secure, Fortinet, Citrix, and others, intruding three DOE national labs in September 2024. QScan carried over 200 proof-of-concept exploits and processed more than two million scanning tasks in a single day in 2024.

CyberScoop · 20d agoThreat actor in the wild1

Show HN: LLM Attention Visualization

A developer released a browser-based tool that visualizes which past tokens influence each LLM output token using aggregated, value-weighted attention scores.

A Show HN project presents a React application built on Transformers.js that renders per-token attention influence by aggregating attention weights scaled by value-vector magnitudes across all attention heads and layers. To expose internal tensors, the author instrumented the ONNX computation graph, hosted a modified model on Hugging Face, and pre-generated prompts to avoid long model downloads in the browser. Demos with a 600-million-parameter model show how verbatim copying draws heavily on source tokens and how single outputs blend information from multiple phrases.

Hacker News · AI · 8d agoAI tools & infraHN 41↑ · 9 comments

Change Healthcare Cyber

Change Healthcare's ransomware attack disrupted US healthcare payments and exposed data of roughly 190 million people.

Infosecurity Magazine covers the cyberattack on Change Healthcare, the UnitedHealth Group subsidiary hit by ALPHV/BlackCat ransomware. The attack disrupted US pharmacy and payment processing services and led to the exposure of data belonging to about 190 million individuals. It ranks among the largest healthcare sector cyber incidents on record.

Infosecurity Magazine · 28d agoRansomware in the wild

Kids’ online safety bill faces dim prospects of passage this session despite progress

Kids Online Safety Act clears Senate committee but passage looks unlikely this session amid House-Senate deadlock over the duty-of-care provision.

KOSA advanced out of the Senate Commerce Committee, but the chambers remain split on a duty-of-care provision requiring platforms to act with reasonable caution to prevent foreseeable harm, which House leadership opposes over First Amendment and negligence-lawsuit concerns. The Senate passed KOSA 91-3 last Congress before it died in the House, and the House passed its own version without the duty of care in June as part of a larger package, after stripping a state-law preemption provision. Observers say even Senate passage this year is a struggle given the short calendar, with a lame-duck window between November and January the more plausible path, and Majority Leader John Thune controlling whether a roll-call vote happens.

The Record · 23d agoPolicy & legal

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 · 2d agoAI research

Delaware Consumer Privacy and Data-Breach Law Updates

Delaware's governor signed HB 380 and HB 381 amending the state privacy act and breach notification law.

On September 2, 2026, Delaware's Governor signed House Bill 380 and HB 381. HB 380 amends the Delaware Personal Data Privacy Act (DPDPA), enacted in 2023 and effective January 1, 2025. HB 381 separately amends Delaware's computer security breach notification law. Joseph J. Lazzarotti of JacksonLewis summarizes the changes.

DataBreaches.net · 3d agoPolicy & legal

Risky Bulletin: White House lets private companies carry out offensive cyber ops

A White House memo directs DHS to create a program letting vetted private companies conduct US-government-directed offensive cyber operations against cybercrime.

A presidential memo tasks the DHS National Coordination Center with building a program, under DOJ and DHS oversight, through which private-sector companies can conduct offensive cyber operations against large-scale cybercrime organizations. Requirements include secure facilities, vetted personnel, a $1 million escrow for damages, and written approvals co-signed by DHS and DOJ executive directors. The program must launch within 60 days, around October 11, expanding a March executive order targeting scam compounds, ransomware, and other large-scale cybercrime.

Risky Business News · Aug 14, 2026Policy & legal

UniH^3: Unifying Hierarchical Homogeneity and Heterogeneity for All-in-One Medical Image Restoration

UniH3 unifies hierarchical homogeneity and heterogeneity modeling for all-in-one medical image restoration across modalities and degradation types.

UniH3 introduces a Hierarchical Homogeneity Memory module that distills shared anatomical priors from high-quality images, injected via a Homogeneity-Guided Attention mechanism. A Hierarchical Heterogeneity Balancer mitigates inter- and intra-task conflicts during multi-task optimization. It achieves state-of-the-art on MedIR-2D-500K and MedIR-3D-3D benchmarks for both all-in-one and single-task restoration, with code released on GitHub.

Hugging Face daily papers · 6d agoAI research

Show HN: Geiger – See every AI agent on your machine and what it can touch

Geiger, a new open-source tool, surfaces AI agents running on a machine and the files and resources they can access.

Geiger launched on Hacker News as an open-source utility that shows every AI agent operating on a local machine and the scope of what each agent can touch. The Show HN post drew early community attention with 21 points and 11 comments, with the code hosted on GitHub under the Atomburstofficial account.

Hacker News · security · 7d agoToolsHN 21↑ · 11 comments

Emergency Department Revisit Quality Review Screening: Exploring Human Decision-Making and Artificial Intelligence Support

A retrospective study found GPT-4 over-flagged emergency department revisit cases while an LLM knowledge-graph screener achieved 83-100% positive predictive value.

In an exploratory retrospective study of 99 emergency department diagnosis pairs from a multihospital health system, clinicians and GPT-4 independently judged whether revisit pairs warranted further assessment. GPT-4 responses correlated poorly with clinicians, flagging 94% of pairs for follow-up, 4.4-13.3 times more than clinicians, though prompt engineering was minimal. An algorithm leveraging an LLM-populated knowledge graph (KGA) achieved 83-100% positive predictive value against at least one clinician rater, suggesting LLM-based screening could broaden revisit quality review without substantially increasing reviewer workload.

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

Safety for Whom? Boundary-Aware Self-Distillation for Controlled LLM Safety Refusal

A self-distillation safety framework tunes narrow-boundary refusals in Qwen3-8B, raising target-domain refusal to 84.75% while cutting over-refusal from 15.20% to 5.20%.

The paper formulates narrow-boundary safety, where deployments need refusals within specific topics rather than whole subjects, and proposes an offline self-generated framework with controlled topic generation, escalating retries, and harmful-benign boundary pairs. On political persuasion with Qwen3-8B, the method raised target-domain refusal from 9.47% to 84.75% and cut the mean unsafe-response rate across three broader benchmarks from 26.26% to 0.14%. Verified target-model responses reduced over-refusal from 15.20% to 5.20%, and boundary-pair data cut comply-side over-refusal on held-out pairs from 32.94% to 4.16%. Results show data composition controls the safety-usability trade-off and alignment should be evaluated on both sides of the refusal boundary.

Hugging Face daily papers · 13d agoAI safety & security1

NOAH: Learning the Full Patient Journey. A Longitudinal Multimodal Time-Aware Model for Representation and Forecasting

Researchers introduce NOAH, a generative time-aware transformer trained on 559 million MIMIC clinical events to model and forecast patient trajectories.

NOAH is a task-agnostic, time-aware generative transformer designed to represent and forecast the full multimodal patient journey across medical images, time-series signals, categorical events, and clinical text. It was trained on over 559 million clinical events from 431,000 hospital visits covering 299,000 patients in the MIMIC dataset family. The architecture combines bidirectional time integration with a variational latent space to capture continuous patient state evolution and clinical stochasticity. NOAH supports autoregressive forecasting with time control, zero-shot classification, and counterfactual intervention simulation, with evaluations on 15 ICD chapters, 29 comorbidities, and time-to-event prediction.

arXiv cs.AI / cs.LG / cs.CL · 7d agoAI research2

WearableQA: A Benchmark for Health Reasoning over Real-World Wearable Data

WearableQA benchmark introduces 4,084 questions over real longitudinal wearable data, showing 14 LLMs score 19.6-72.9% on health reasoning, far from solved.

WearableQA is a benchmark of 4,084 10-option multiple-choice questions built from wearable time series, blood biomarkers, and demographics of 200 real users with up to 500 days of daily measurements. It defines 16 question types along two axes: data versus health reasoning, and single- versus cross-signal reasoning, using a dual-grounding framework combining literature and population-validated patterns. Evaluations of 14 proprietary and open-source LLMs show accuracy ranging from 19.6% to 72.9% against a 10% chance baseline, with most models below 60%.

Hugging Face daily papers · 12d 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 · 6d agoAI research

WearableQA: A Benchmark for Health Reasoning over Real-World Wearable Data

WearableQA benchmark tests LLM health reasoning over longitudinal wearable data; the best of 14 evaluated LLMs reaches 72.9% accuracy.

WearableQA comprises 4,084 ten-option multiple-choice questions built from wearable time series, blood biomarkers, and demographics of 200 real users with up to 500 days of daily measurements. It defines 16 question types along two axes: data versus health reasoning, and single- versus cross-signal reasoning. Evaluation of 14 proprietary and open-source LLMs shows performance from 19.6% to 72.9% against a 10% chance baseline, with most models below 60%.

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

Securing Your Business: The Vital Role of Cyber Insurance | Huntress

Huntress explains cyber insurance coverage types, insurer security requirements, and the shift toward documented evidence of controls.

Huntress outlines first-party and third-party cyber insurance coverage, including business interruption, data recovery, extortion, privacy liability, and regulatory fines. Insurers now commonly require EDR, MFA, security awareness training, patching, tested backups, least-privilege access, and incident response plans. With ransomware accounting for 91% of insurance losses in H1 2025 and average US breach costs at $10.22 million, underwriters increasingly demand evidence packs rather than self-attestation.

Huntress · 15d agoIndustry

NOAH: Learning the Full Patient Journey. A Longitudinal Multimodal Time-Aware Model for Representation and Forecasting

Researchers introduce NOAH, a time-aware generative transformer trained on 559 million MIMIC clinical events to forecast multimodal patient trajectories.

NOAH is a task-agnostic, time-aware generative transformer trained on over 559 million clinical events from 431,000 hospital visits by 299,000 patients across the MIMIC dataset family. It uses bidirectional time integration and a variational latent space to model the stochastic evolution of patient states, natively processing medical images, time-series signals, categorical events, and structured or unstructured clinical records. The model supports autoregressive forecasting with optional time control, zero-shot classification, and counterfactual intervention simulation, with strong probing performance across clinical outcomes, 15 ICD chapters, and 29 comorbidities.

Hugging Face daily papers · 8d agoAI research1

Verifiable by Construction: Claim-Level Evaluation of Verbatim Citation in Clinical Question Answering

Evaluation of twelve LLMs on 222 clinical questions shows verbatim quotes rarely substantiate claims; claude-opus-5 fully substantiates only 37.1%.

The authors build a standardized harness over four clinical practice guidelines and evaluate twelve LLMs on 222 synthetic clinical questions, measuring citation attachment, verbatim quote production, and claim substantiation. Most models attach verbatim quotes to over 90% of claims from prompting alone, though lightweight models like claude-haiku-4.5 struggle. Quotes frequently fail to substantiate claims: claude-opus-5 quotes 98.0% of claims but fully substantiates only 37.1%, exposing a capability gap for verifiable clinical QA.

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