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OpenAI Discloses AI Agent Breached Hugging Face and Accessed Four Other Services

  OpenAI has disclosed that an autonomous AI agent involved in an internal cybersecurity evaluation accessed four accounts across four publi...

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Healthcare Data Security
advanced ransomware techniques Cyber Attacks Cyber Security Ransomware Attacks Healthcare Cyber Attack Healthcare cybersecurity Healthcare Data Security

AnMed Health Ransomware Attack Highlights Growing Patient Safety Risks in Healthcare

 

AnMed Health is the latest healthcare organization to be disrupted by a ransomware-related cybersecurity incident after having to cancel procedures and appointments while transitioning to paper-based operations. AnMed’s healthcare network was impacted by the ransomware attack, which led to the closure of some offices and the diversion of patients while administrators work to bring operations back online. 

AnMed closed its offices on Monday and reopened them on Tuesday under downtime procedures as employees use paper-based records and other manual processes to continue providing care. In the meantime, the healthcare organization has been using transfers, diversions and triage to manage the impact on operations while cybersecurity experts work to secure its systems. This incident serves as yet another reminder that ransomware-related cybersecurity incidents can disrupt the critical operations of healthcare organizations long after the initial financial and technological repercussions. 

Without access to electronic health records and other digital applications, clinicians may find it much harder to access patient health information or make timely decisions, which increases the likelihood of diagnostic and treatment errors. A similar consequence can also be observed in pharmacies, where the inability to access digital databases and communication platforms can cause delays in dispensing medication. 

AnMed has opened phone lines for patients to request prescription refills while its normal operations are suspended, and it has asked patients to rely on its online portal for more information about the closure. AnMed has revealed limited information about the ransomware incident, confirming that it is a cyber security incident involving malicious software while noting that it is working with federal and state officials to secure its network and resume normal operations. 

The healthcare organization has not commented on how the ransomware infiltrated its system or if patient data was compromised or encrypted. The ransomware attack comes at a time when healthcare organizations are being targeted with unprecedented cybersecurity aggression worldwide. Cybercriminals are increasingly using ransomware to interrupt the critical operations of healthcare organizations by encrypting or stealing patient data and threatening to make the information public unless a ransom is paid. 

Threat actors typically infiltrate healthcare systems through phishing attacks, compromised credentials, insecure remote access tools, or system vulnerabilities before deploying ransomware or encrypting data to demand payment of a ransom. Healthcare systems and organizations can be especially vulnerable to such an incident, considering the fact that they cannot halt their operations to mitigate the ransomware attack or contain it while working to restore normal operations. Hospitals and clinics typically rely on interconnected systems that facilitate the exchange of patient health information and other operations, including scheduling, laboratory tests, pharmacy operations, billing and communication platforms.

All these systems and applications can be disrupted during a ransomware attack, forcing medical professionals to rely on manual, paper-based alternatives. Cybersecurity experts typically recommend multifactor authentication, regular software updates, network segmentation, monitoring, security awareness training and offline backups to secure interconnected systems and ensure business continuity following a ransomware attack. 

However, those measures cannot offer absolute protection, which means that organizations need to respond appropriately to ransomware incidents while strengthening their defenses. It is increasingly evident that ransomware incidents are no longer just technology issues but also patient safety ones.

That is why healthcare organizations should focus on responding to ransomware incidents by identifying the point of infiltration and ransomware type, isolating affected systems and applications, determining if any patient data was compromised, and taking appropriate mitigation steps.
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Ransomware Attacks
AI Model Ransomware AI Model Weights AI Security ENCFORGE Ransomware JadePuffer Ransomware Langflow Vulnerability malware Ransomware Attacks

New Ransomware Targets AI Model Weights but Fails to Collect Ransom


An updated ransomware campaign is targeting an important but often overlooked asset in artificial intelligence environments: trained AI models and their supporting data. Researchers have discovered a ransomware strain that encrypts AI model weights, vector indexes, and training data, but no ransom payment mechanism appears to have been established. 


The Threat Research Team at Sysdig attributed the activity to the threat actor JADEPUFFER, who previously compromised the same internet-facing Langflow server. This attack exploited the critical vulnerability CVE-2025-3248 that allows remote Python code execution due to a critical missing authentication vulnerability in Langflow's code-validation endpoint. 

Although Langflow fixed the vulnerability in version 1.3.0, the targeted server remained vulnerable even after it was publicly reported. An ENCFORGE binary was deployed in the second campaign that searched for 180 different file extensions using a compiled Go-based ransomware binary. As opposed to conventional ransomware that may incidentally encrypt model files, ENCFORGE identifies AI-related assets specifically, including PyTorch and TensorFlow checkpoints, Hugging Face SafeTensors weights, GGUF files for large language models within the local region, FAISS vector indexes, as well as training data stored in Parquet and NumPy formats. 

During the second campaign, ENCFORGE was deployed, a Go binary powered by UPX that searches for 180 file extensions across a wide range of machine-learning applications. In contrast to conventional ransomware, which may encrypt model files incidentally, ENCFORGE is specifically designed to identify AI-related assets, such as PyTorch and TensorFlow checkpoints, Hugging Face SafeTensor weights, GGUF files associated with local large language models, FAISS vector indexes, Apache Parquet and TFRecord training datasets, and NumPy arrays, among others. 

A command-line interface for adding custom file extensions has been provided by attackers, along with examples of LoRA fine-tuning adapters and legacy GGML weights, further demonstrating that the malware was specifically designed for artificial intelligence environments. According to researchers, the ransomware encrypts portions of files with AES-256-CTR encryption keys protected by embedded RSA-2048 keys, although there appears to be no network functionality to facilitate data theft or ransom collections. 

ENCFORGE was not identified by Sysdig as a leak site, outbound communication, or payment portal. Instead of a Proton Mail address in the ransom note, a Proton Mail address was included, suggesting that the operation was primarily oriented toward rendering the victim's AI assets useless, rather than stealing them to conduct double extortion. ENCFORGE differs from double-extortion ransomware by lacking an exfiltration mechanism.

A leak site and functional capability for stealing and publishing victim data were not discovered by researchers. Instead, the primary objective of the campaign is to destroy AI assets by rendering model files and related data unusable. JadePuffer's earlier campaign also included a contact address that corresponded to the malware, indicating that this campaign is related to JadePuffer. 

Due to the fundamental difference between restoring a trained AI model and restoring a conventional database, the potential impact is significant. Sysdig estimates that it could cost between $75,000 and $500,000 to rebuild a production-ready fine-tuned model directly, depending on GPU resources and engineering efforts. If training data is compromised, recovery becomes even more challenging. 

Model artifacts and associated training data are particularly difficult to recover when the system hosting them contains both. In this case, restoring the model may not be possible until the dataset has been recovered and the necessary training processes have been repeated. Because organizations often maintain multiple model variants on shared storage, one encryption event can have a significant impact on several production or development assets concurrently. 

It is also evidenced in the campaign that attackers are increasingly adapting their attacks around artificial intelligence infrastructure. The attacker generated multiple Python scripts using the compromised Langflow environment, as the ransomware could not initially be downloaded from the command-and-control server. During the first five minutes, the scripts were able to develop a method for exiting the container environment through the exposed Docker socket and executing the ransomware on the host machine. 

Rapid escalation is a result of broader trends in ransomware operations in which attackers are increasing the speed at which they can gain access and deploy ransomware. As a result of the JadePuffer incident, the delivery mechanism was rebuilt within minutes after the original download failed, leaving little time to detect and contain the intrusion before it began encryption. Six Python scripts progressively refined the escape procedure during the escape process. 

By launching a privileged container over the mounted Docker socket, the ransomware was moved across the container boundary through the host's proc file system and executed against the host file system outside the original container's isolation using the mounted Docker socket. Following encrypting the targeted files, ENCFORGE terminated processes holding file locks and deleted itself once the encryption was complete. The incident highlighted an increasing security vulnerability in the AI asset ecosystem. 

The backups should be separated from the systems that host production models to ensure that a compromise of the artificial intelligence environment does not also compromise the recovery copies. Organizations should ensure model checkpoints, vector indexes, and training data are backed up in immutable, tested versions, remove unnecessary Docker sockets, rotate credentials that are accessible from compromised systems, and monitor for mass encryption of AI-specific files. 

In response to the increasing value of artificial intelligence models in businesses, ransomware operators have begun targeting the files containing the accumulated work behind the systems. As a result of the ENCFORGE campaign, AI infrastructure must now be protected as critical assets rather than as ordinary files, by treating model weights and associated datasets accordingly.

Among other things, ENCFORGE emphasizes the importance of treating artificial intelligence model weights, training data, and related artifacts as critical digital assets for organizations. In order to limit the impact of future attacks, it will be necessary to protect these assets with isolated backups, enhanced access controls, and timely vulnerability remediation. As attackers increasingly tailor ransomware to emerging technologies, it is imperative to protect these assets.
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Security Patch
Business Security Cyber Security Ransomware Security Patch

Ransomware Attacks Fall as Business Defenses Improve

 

Ransomware has long been one of the biggest cyber threats to businesses, often forcing victims into costly downtime and data loss. Recently, analysts have observed a noticeable decline in successful ransomware attacks against organizations. This shift is not happening by chance. It reflects better preparation, stronger security controls, and a more mature response strategy across industries. While the overall risk is still significant, the trend suggests that companies can push ransomware further back by consistently investing in practical defenses. 

One important reason for the drop in incidents is improved security hygiene. Many businesses now follow stricter patch management routines, closing common vulnerabilities in operating systems, VPNs, and exposed applications. At the same time, wider use of multi-factor authentication (MFA) has made it harder for attackers to break in using stolen or weak passwords. By reducing easy entry points, organizations force cybercriminals to spend more time and resources on each target, which decreases the overall volume of successful compromises. 

Another key factor is better visibility into networks and endpoints. Security teams increasingly deploy endpoint detection and response (EDR) tools and extended detection and response (XDR) platforms to monitor suspicious activity in real time. Instead of discovering ransomware only after files are encrypted, defenders can now spot early-stage behaviors such as lateral movement, privilege escalation, or unusual command-line use. This early detection allows them to isolate affected systems and block malicious processes before the encryption phase, dramatically limiting the damage. 

Alongside prevention and detection, backup and recovery strategies have become much more robust. Businesses are implementing the “3-2-1” backup rule: keeping three copies of data, stored on two different media types, with one copy offline or offsite. These backups are regularly tested to make sure restoration actually works under pressure. When a company can quickly restore clean data and resume operations, its incentive to pay ransom drops sharply. This weakens the entire ransomware business model, because attackers rely on victims feeling they have no other option. 

Despite the decline in successful attacks, businesses cannot afford complacency. Ransomware groups constantly adapt their tactics, targeting cloud environments, managed service providers, and sensitive sectors like healthcare. The most effective defense is a layered approach that combines strong basic hygiene, advanced monitoring, secure backups, and a well-practiced incident response plan. Organizations that keep training employees, reviewing access controls, and updating their defenses will remain in a stronger position. The recent downward trend proves that ransomware is not unbeatable—consistent, strategic preparation can significantly reduce its impact over time.
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StormEncryptor
China malware Microsoft Ransomware StormEncryptor

Hackers Linked to China Install StormEncryptor Ransomware


Threat actor links to China

Microsoft has revealed that a financially motivated hacker linked to China, called Storm-1175 has installed an earlier undocumented ransomware strain known as StormEncryptor. Storm-1175 is believed to exploit a critical flaw in a cybersecurity supply-chain campaign where threat actors can install custom ransomware throughout large list of target networks.  

Storm-1175 began installing a new ransomware strain, Microsoft Threat Intelligence warned this week. Threat actors earlier deployed Medusa ransomware to take money from finance organizations, healthcare providers, and professional services in the US, Australia, and Britain. 

About the attack

In April 2026, the threat actors operated  “high-velocity ransomware campaigns,” abusing both recently revealed zero-day exploits and flaws, “in some cases a full week before public vulnerability disclosure.” Microsoft warned it had observed the gang transition from initial access to full encryption in less than 24 hours.

In the recent campaign, according to Microsoft, the group may be exploiting CVE-2026-18577- a flaw in the N-central, a remote monitoring and management (RMM) console used by various service providers to supervise client endpoints. 

Attack tactic

Microsoft has not officially verified the access vector, but found that StormEncryptor installations started the same day the bug was revealed. The flaw allows threat actors “unauthenticated, ‘god-mode’ access,” warned cybersecurity firm Huntress.

The flaw permits threat actors with no credentials to get full administrative command over the N-central server to handle clients’ machines remotely’. The single hacked server becomes an entry point to every endpoint it commands. A single provider can offer dozens of ransomware incidents throughout its entire client base. 

A similar supply-chain attack on an RMM tool in 2021 from software provider Kaseya permitted Revil ransomware group to hack 60 of Kaseya’s direct consumers before attacking 1,500 downstream organizations. 

In 2024, another supply chain attack on an RMM, affected ConnectWise’s ScreenConnect product. It resulted in various downstream ransomware campaigns. According to Microsoft, Storm-1175 was amid the various gangs attacking ScreenConnect during that phase.

Estimates of impacted firms have not been confirmed. Parent company N-central’s N-able software company said it reached out to a limited number of impacted customers. Huntress has acknowledged few of its own consumers were affected and posted a timeline demonstrating how the threat actors travelled across downstream hosts in two cases, but Huntress did not verify the number of downstream organizations impacted from the ransomware attacks.

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spear phishing
AI Hacking Kimsuky Hacking Group LNKs malware us treasury PowerShell spear phishing

Kimsuky Brings AI Closer to Its Malware and Phishing Operations

 



North Korean cyber-espionage group Kimsuky appears to be moving beyond occasional use of public AI services by assembling a local artificial intelligence environment that could eventually support phishing, data analysis and malware development.

South Korean cybersecurity firm Genians identified the setup after months of monitoring infrastructure linked to Kimsuky, a hacking unit subordinate to North Korea's Reconnaissance General Bureau. Its investigation found multiple tools capable of running AI models locally, alongside document-retrieval software, AI development libraries, speech-to-text components and an AI-assisted coding environment.

Genians found no evidence that Kimsuky had trained its own AI model. Instead, the activity indicates that the group is experimenting with existing technologies and assembling the components needed to incorporate AI into its established espionage workflow.

Among the strongest evidence were Ollama, GPT4All and Msty, applications that can run or interact with language models locally. Genians said the tools appeared to have been configured or used rather than merely downloaded. Ollama had generated keys associated with its initial setup, while GPT4All contained a configured "localdocs_v3.db" database used by its LocalDocs retrieval-augmented generation (RAG) feature.

RAG allows an AI model to retrieve information from a private document collection while generating responses. The database indicates an attempt to connect documents available to the operator with an AI system, although Genians could not establish that the documents were stolen.

Researchers also recovered an operator request asking for a dataset to be examined for cryptocurrency wallet information, Gmail credentials and website-registration history. The request demanded detailed analysis, but investigators could not confirm that it had actually been submitted to an AI service.

The infrastructure contained further evidence of AI development. Genians found LLamaSharp, Microsoft's Semantic Kernel and Microsoft.Agents.AI, frameworks that can help developers integrate AI capabilities into C# and .NET applications. OpenAI Whisper files and documentation for extracting text from audio were also recovered, alongside traces of Cursor, an AI-powered coding editor.

None of these tools is inherently malicious. Their relevance comes from their deliberate assembly on infrastructure associated with a nation-state espionage group. Together, they could provide building blocks for automating software development, document processing, transcription and information analysis.

The activity is linked by Genians to Operation GitPower, a Kimsuky campaign that has used GitHub repositories as command-and-control channels in an LNK-to-PowerShell infection chain and distributed encrypted AsyncRAT payloads disguised as image files. Fortinet has separately documented GitHub-based command-and-control activity targeting South Korean users, supporting the wider technique family, although it does not independently verify Genians' newly discovered AI artifacts.

AI could also make Kimsuky's phishing campaigns harder to identify. Generative systems can reduce linguistic weaknesses such as poor grammar, awkward translations and formatting errors that defenders have historically used as phishing indicators.

Kimsuky has already demonstrated interest in generative AI. In 2025, Genians reported that the group used ChatGPT to create a fake South Korean military identification card for a spear-phishing campaign.

The latest discovery suggests a further step toward keeping AI capabilities within infrastructure controlled by the attackers. Local models can process information without relying on public AI services, potentially giving operators greater control over sensitive material and reducing dependence on external platforms.

Kimsuky has historically targeted governments, researchers, think tanks, academics and other organisations for intelligence collection. The U.S. Treasury sanctioned the group in 2023 and described it as subordinate to North Korea's Reconnaissance General Bureau.

However, the findings should not be overstated. Genians has not demonstrated that the local AI stack has been deployed against victims, trained a proprietary model or autonomously developed malware. No GitPower victim count has been disclosed, and Reuters reported that the findings could not be independently verified.

For defenders, Genians recommends correlating LNK execution, PowerShell activity, hidden scheduled tasks, GitHub communications and subsequent payload execution rather than relying primarily on the quality of a phishing email.

The immediate development is therefore less about autonomous AI hacking and more about preparation. Kimsuky appears to be assembling the infrastructure that could allow AI to become an integrated layer across its existing phishing, malware and intelligence-collection operations.


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Inforstealers
cybercrime gangs CyberSecurity Ransomware Attacks Cyble Cyble research Data Breach Data Leaks data misuse data security Inforstealers

Tanaka Emerges as Leading Data Leak Broker as Stolen Information Fuels Cybercrime

 

Ransomware attacks are undoubtedly one of the most notorious security threats today. Yet it seems that information itself has become a very popular target among cybercriminals. Particularly, the threat actor called Tanaka has appeared to be the most successful data dealer during the first half of 2026, according to the research conducted by Cyble. Overall, 367 confirmed cases of corporate data leaks or breaches happened worldwide during the first half of 2026, the experts from Cyble have found. 

While the activity of Tanaka appeared to be less prominent than that of many well-known ransomware groups, he has been the most active data dealer according to Cyble research. His activity has resulted in 25 leak posts, which is more than double than the number of posts of other famous data-leak organizations. The threat actor has been targeting organizations in various fields, pursuing different goals. While the Banking, Financial Services and Insurance sector remained the most attractive for criminals with 38 data breach incidents recorded, governments and technology companies have also been frequently targeted by Tanaka. 

It implies that data theft is no more limited by regional or economic factors and can happen to organizations of any size or any industry. In particular, Tanaka has been very active in North America, where 7 leak posts related to the criminal have been discovered this year. Meanwhile, Europe and the UK have witnessed 6 leak posts related to Tanaka, as well. In these regions, financial services, telecom, and retail companies have experienced the most significant challenges, as customer and financial data of these organizations are highly attractive to data prospectors. 

In general, data prospecting has become a significant threat to organizations worldwide, as there are now more opportunities to benefit from the data belonging to other organizations. It is a part of the ransomware attack chain, as ransomware criminals can use the data belonging to the victim as leverage to demand more significant ransoms. However, data extortion is not the only way to monetize data theft, as leaked databases can be further sold on dark web forums and marketplaces. 

In addition, the stolen data can be used for extortion, reconnaissance, and other nefarious purposes. It is necessary for companies to realize that the detection of one’s data being sold or showcased on underground forums should be treated as a serious security incident. It can be a sign of the potential ransomware attack, which should be responded to accordingly. Monitoring the dark web for signs of reconnaissance activities is one of the essential aspects of cybersecurity, which is why professionals may want to consider detecting their organization’s potential exposure to ransomware attackers.
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