There is some positive news from the data collected by cybersecurity firm SonicWall, as cyberattacks have declined by up to 57% in some sectors; however, the healthcare industry has seen the smallest decline out of all tracked verticals, registering just a 17% year-over-year decline, compared to -23% for professional services, -42% for education, -46% for retail and -57% for manufacturing. Healthcare is still persistently targeted by cyber actors, and the gap between healthcare and other sectors is growing, according to the SonicWall 2026 Healthcare Protect Brief.

There are more active ransomware groups (10) attacking healthcare organizations than any other sector, indicating the industry is being actively targeted rather than falling victim to spray-and-pray attacks, and in H1 2026, there were four times as many malware hits per firewall in healthcare as the next most attacked sector. UltraVNC buffer overflow attacks generated 13.3 million hits in just 5 months, as hackers primarily targeted remote desktop tools to attack healthcare organizations – no other vertical experienced remote desktop exploitation at that scale.

Healthcare organizations rely on remote desktop tools to support their distributed clinical environments, telemedicine platforms, and third-party vendor access. If remote access credentials are compromised, it gives threat actors a path to clinical systems and patient data, which can be exfiltrated and held to ransom. While network-level controls can limit data access, and multifactor authentication (MFA) can prevent compromised credentials from providing access, MFA is often not implemented, and a single set of credentials does not just unlock one application; they often grant access to the full network.

SonicWall also identified 243 unique attack methods targeting connected medical devices, with the Internet of Things (IoT) the fastest-growing and hardest-to-patch exposure. Healthcare organizations have a huge range of deployed connected devices, including infusion pumps, patient monitors, imaging systems and more, which means a huge attack surface to defend. Unfortunately, the attack surface is growing faster than security teams can govern it. IoT devices are often not routinely patched, cannot run endpoint agents, and often share network segments with clinical systems that contain protected health information.

“Healthcare does not have a cybersecurity problem. It has three of them,” explained Michael Crean, SonicWall SVP of Managed Services. Remote desktop tools without layered controls and MFA; a huge IoT footprint containing vulnerable devices; and targeted ransomware attacks. “Attackers have figured out how to use all of them at the same time.”

Hackers continue to target the sector as the returns are too reliable and the defenses too predictable. “What our research makes clear is that attackers have done the math. Hospitals cannot go dark, downtime is measured in patient outcomes, and the pressure to pay is unlike anything in any other sector. None of that changes until healthcare stops relying on security architectures built for a world that no longer exists, and starts treating Zero Trust not as a future initiative, but as the baseline they needed yesterday.”

The immediate steps recommended by SonicWall are to restrict UltraVNC and RDP to internal VLANS and ensure that MFA is implemented for all remote access, with no exceptions for vendors and no break-glass credentials. Connected medical IoT devices must be placed on isolated networks, away from clinical systems. Healthcare organizations need to implement application-level Zero Trust and ensure that legacy vulnerability exposure is addressed. SonicWall recommends conducting a comprehensive inventory of clinical middleware and IoT firmware and then ensuring that vulnerabilities are patched or devices isolated on a defined schedule.

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A high-severity vulnerability has been identified in OHIF (Open Health Imaging Foundation) Viewers DICOM, which could be exploited to steal an authenticated clinician’s token via a crafted link.

The Server-Side Request Forgery (SSRF) vulnerability is tracked as CVE-2026-12473 and has a CVSS base score of 8.2 (v3.1) and 8.3 (v4.0). The vulnerability is due to two data sources – DICOMWebProxy and DICOMJSON –  shipped in the default configuration fetching an arbitrary URL parameter without validation.

A global authentication service in OHIF injects the authenticated user’s OIDC Bearer token into the resulting requests, which could be sent to an attacker-controlled server, allowing the OIDC Bearer token to be obtained. The vulnerability does not impact DICOMweb data sources.

The vulnerability affects OHIF DICOM Web Viewer Framework prior to v3.12.0. The vulnerability has been fixed by the maintainer in version 3.12.2, which was released on May 18, 2026. The fix is located at OHIF/Viewers#5985 (master), OHIF/Viewers#5978 (release/3.12).

Users are advised to update to the fixed version as soon as possible. There are additional requirements for users running OHIF with authentication and those that need dicomwebproxy or dicomjson in authenticated deployments, as detailed in the CISA security advisory.

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A review of the use of generative artificial intelligence (GenAI) tools by Department of Veterans Affairs (VA) staff has identified potential patient safety risks from a lack of safeguards and oversight. The review was conducted by the VA Office of Inspector General (OIG) between October 2025 and January 2026 and found that more than 15,000 VA staff members were using general-purpose GenAI chat tools authorized for use by the Veterans Health Administration (VHA) – VA GPT and Microsoft 365 Copilot Chat.

The reviewers identified broad staff engagement with the AI chat tools. An analysis of an internal prompt‑sharing application identified 135 prompts for the GenAI chat tools, 79 of which were clinical. The drafting of clinical notes and summarization of patient care were among the most common uses of the tools. The VA OIG notes that the tools were not specifically developed for clinical use, and while the VA provides clinical users with general training and resources, the VA does not centrally curate or evaluate prompts or the generative output, which may be applied to clinical decision making. The VA OIG notes that studies of genAI usage in medical settings found that prompt techniques can play a critical role in output errors that could impact diagnoses and care management if not corrected.

The Office of Management and Budget’s 2025 memorandum (Accelerating Federal Use of AI through Innovation, Governance, and Public Trust) requires all agencies to identify high-impact AI use and implement safeguards to manage risk. The VA did not identify the use of VA GPT and Copilot Chat as high-impact, and therefore, the required risk management actions did not apply.

The VHA had determined that Ambient AI Scribe was high-impact, which triggered safety requirements such as pre-deployment testing of the AI tool and providing human oversight before use. Ambient AI Scribe is a targeted clinical documentation tool that listens to clinical visits and drafts medical record notes. The VA-OIG said the tool had functionality similar to the clinical documentation prompts VA staff were using with VA GPT and Copilot Chat, which were not considered high-impact.

The VA OIG made three recommendations to the VHA regarding the use and assessment of GenAI chat tools: Evaluating these tools as high-impact, implementing the required safeguards, and integrating monitoring of AI-related risks into existing patient safety programs. The VHA concurred in principle with the recommendation to evaluate the tools as high -impact and concurred with the other two recommendations. The VHA has provided the VA OIG with an action plan, will develop guidance on the use of the GenAI chat tools, and is working on addressing the recommendations by April 2027.

As the use of GenAI tools in healthcare accelerates, concern is growing that sensitive patient data may be shared with publicly accessible chatbots, and that AI tools could generate output that puts patients at risk of harm or even death. Earlier this year, Health-ISAC and the Health Sector Coordinating Council Cybersecurity Working Group issued guidance on developing effective AI governance frameworks – Health-ISAC’s White Paper: Policies and Safeguards for a Safe Use of AI and the HSCC Health Industry AI Cyber Governance Framework Implementation Guide to help healthcare organizations create an effective AI governance and safeguards framework and responsibly use GenAI and LLMs while minimizing risk.

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The Cybersecurity and Infrastructure Security Agency (CISA) has issued a Binding Operational Directive (BOD  26-04) establishing new deadlines for vulnerability remediation for federal civilian agencies. Defenders have long been struggling to keep on top of patching due to the frequency with which new vulnerabilities are identified, the pace of which has increased dramatically due to artificial intelligence.

According to the Verizon 2025 Data Breach Investigations Report, organizations were only able to fully remediate around 38% of vulnerabilities in CISA’s Known Exploited Vulnerability (KEV) Catalog in 2024. The 2026 DBIR report shows that the percentage of fully remediated vulnerabilities in 2025 fell to 26%, with a median resolution time of 43 days. Artificial intelligence has massively increased the pace of vulnerability discovery, defenders are becoming overwhelmed, and critical vulnerabilities are remaining unpatched for longer periods, increasing the window of opportunity for exploitation. CISA’s solution is to patch smarter, not harder.

CISA has released a new risk-based vulnerability remediation framework to help vendors assess vulnerabilities and prioritize patching effectively, concentrating their efforts on mitigating vulnerabilities in the most at-risk assets and addressing vulnerabilities that carry the greatest risk of exploitation.

CISA has determined that the greatest risk is associated with vulnerabilities with four characteristics:

1. Public exposure via the internet
2. The ability to fully automate exploitation
3. If the vulnerability gives an attacker full control of a system, and
4. Evidence of real-world exploitation (KEV inclusion)

Based on this framework, any vulnerability that meets all four criteria must be mitigated in the shortest possible timeframe – no more than 3 days. If the vulnerability is publicly exposed, is in the KEV, is automatable, and gives an attacker partial control of a system, the vulnerability must be remediated within 3 days. If the vulnerability gives an attacker full control of a system, following remediation within 3 days, a forensic triage is required to determine if the vulnerability has already been exploited.

New timelines have been provided for mitigating lower risk vulnerabilities of two weeks or two months, with the lowest severity vulnerabilities not requiring remediation until the next system upgrade. An analysis at one large civilian agency found that only 1% of vulnerabilities fell into the 3-day category, while 60% of vulnerabilities could be deferred unitl the next system upgrade. By following the new framework, organizations will be able to ensure that the most critical vulnerabilities are addressed first.

The new framework prioritizes mitigation of vulnerabilities at the network edge. While vulnerabilities in the network core may be high risk and under active exploitation, CISA generally does not observe threat actors compromising core networks through product vulnerabilities; they use living off the land (LOTL) techniques, which CISA says are best addressed through other means, such as system hardening, network segmentation, and implementing phishing-resistant multi-factor authentication.

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Patches have been issued to fix a critical vulnerability affecting Check Point Mobile Access, SSL VPN, Remote Access VPN, and Spark Firewalls, and a high-severity vulnerability in Google Chrome, both of which are being actively exploited in the wild.

Check Point Remote Access VPN Vulnerability

On June 8, 2026, the cybersecurity firm Check Point issued a security advisory about a critical authentication bypass vulnerability tracked as CVE-2026-50751 (CVSS 9.3), which has been actively exploited in zero-day attacks since May 7, 2026. Exploitation of the vulnerability accelerated over the weekend, with a few dozen organizations falling victim to attacks. In one attack, Check Point associated the post-exploit activity with a Qilin ransomware affiliate that has previously targeted vulnerabilities in other VPNs.

The vulnerability affects Check Point Mobile Access, SSL VPN, Remote Access VPN, and Spark Firewalls; however, only if deployments are configured to use the deprecated IKEv1 key exchange protocol. In vulnerable deployments, unauthenticated remote attackers can exploit a logic flaw in certificate validation, which allows them to establish a VPN connection without a valid password, bypassing authentication requirements.

Check Point also identified a second vulnerability while investigating the actively exploited zero day. The vulnerability is also associated with the deprecated IKEv1 key exchange, which can allow a man-in-the-middle attack on VPN site-to-site connections. The vulnerability is tracked as CVE-2026-50752, has a CVSS score of 7.4, and affects Security Gateways and Spark Firewalls. At the time of issuing the patch, there had been no known exploitation of the flaw.

Customers using the IKEv1 key exchange protocol have been advised to apply the security updates as soon as possible. If the hotfixes cannot be immediately applied, users should follow Check Point’s mitigation guidance detailed in the security alert. The U.S. Cybersecurity and Infrastructure Security Agency (CISA) has added the vulnerability to its Known Exploited Vulnerability (KEV) Catalog and ordered all government agencies to secure their deployments by applying the security updates or mitigations within 3 days. or to discontinue use of the product.

Google Chrome Zero-day

Google has released an emergency patch to fix an actively exploited high-severity zero-day vulnerability in Google Chrome. The vulnerability, tracked as CVE-2026-11645, is due to an out-of-bounds read and write flaw in the Chrome V8 JavaScript engine. The vulnerability can be exploited by a remote attacker via specially crafted HTML pages. Successful exploitation allows the attacker to execute arbitrary code inside the web browser sandbox, exposing sensitive information or crashing Chrome.

Google is aware of an exploit for the vulnerability in the wild, and has rolled out updates for users in the Stable Desktop channel for Windows, Mac, and Linux Systems. Further information about the bug is being withheld until the majority of users have updated Chrome.

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The Health Sector Coordinating Council (HSCC) AI cybersecurity governance task force has published new guidance for healthcare CISOs and other leaders to help them establish cybersecurity governance frameworks for secure AI implementation.

Adoption of AI-based technologies in healthcare is progressing at a pace, with AI tools increasingly embedded into critical healthcare functions; however, these tools introduce new and often poorly understood cyber risks into already complex ecosystems. AI-specific cyber risks, such as data poisoning, model drift, and bias, can threaten successful implementation and HIPAA compliance, and the tools can create vulnerabilities that can be exploited by threat actors in attacks that impact patient privacy, safety, and care.

Healthcare organizations should implement a strong governance structure that integrates cybersecurity principles into the full AI product lifecycle, from assessment, design, development, deployment, and decommissioning of AI systems. The guidance can be used to implement a cybersecurity governance framework for identifying and mitigating AI-specific cyber risks associated with all AI technologies, from traditional machine learning systems to generative AI and agentic AI systems capable of autonomous action.

The AI Cyber Governance Framework Implementation Guide guidance establishes core AI cybersecurity governance objectives for enterprises, ecosystems, and third-party adoption scenarios, and includes AI cyber-specific industry best practices and protocols for secure data handling, model protection, continuous monitoring, and threat detection, including model evasion, model inversion, data leakage, and data poisoning. The guidance provides practical tools for organizing roles and responsibilities, inventory management, contractual language for vendor relationships, and includes a five-level AI autonomy framework and an AI-specific incident response playbook.

The 87-page guidance document is focused on establishing a governance framework for addressing AI-specific cybersecurity risks, and while the guidance covers clinical safety, ethics, and patient engagement when they intersect with cybersecurity risk, a broader AI governance program should be maintained for addressing the full spectrum of AI-related risks beyond cybersecurity, and should therefore be used in combination with existing organizational governance activities.

The playbook is part of a series of AI-specific documents for the healthcare industry, with previous publications including a guide for addressing supply chain risk. Further publications are expected in the coming months to address other healthcare-specific AI considerations.

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Healthcare organizations have embraced AI and are using AI agents to perform a range of functions, including handling IT support desk tickets, automating software workloads, authenticating data exchanges, and performing various security tasks. While there are clear benefits to be gained from using AI agents in healthcare, each new AI agent is a potential entry point for attackers, and a successful compromise could result in a devastating attack.

Each AI agent is given permissions to carry out its functions, and when AI agents are used to perform security functions, those permissions can be significant. Any attack that succeeds in compromising an AI agent will see the attacker gain those same permissions. For instance, an AI identity on a local machine may have access to the password manager, browser sessions, Secure Shell, and encryption keys. An AI agent could disclose admin credentials to an attacker, leading to a crippling attack with significant data theft.

To learn about AI deployments and integrations and how they are affecting identity security, the cybersecurity firm Semperis commissioned Censuswide to conduct a survey of 1,100 IT and IT security professionals across several industries, including healthcare. The survey confirmed that AI agents are being extensively deployed, which pose significant risks to identity infrastructure. Three-quarters of healthcare respondents believe that there will be AI-driven attacks on identity infrastructure, 69% believe that AI attackers will use identity systems to target their infrastructure, but only one-quarter of respondents think that they would be able to fully recover if an AI agent exposed administrative credentials.

On average, more than one-third of the healthcare workforce has at least one AI agent installed on a local machine that has permissions to access Secure Shell and encryption keys, and one in three healthcare respondents said they are using AI agents to handle security-related tasks, with 60% of respondents anticipating deploying AI agents for security tasks in the next 12 months.

According to Semperis, AI agents should be treated as non-human identities (NHIs) in the identity fabric; however, only 66% of respondents said AI identities were registered, authenticated, and authorized within the organization, and of those that do, almost half (48%) register, authenticate, and authorize them separately from human identities. While organizations may be applying security best practices such as the principle of least privilege for human identities, that is not always the case with AI identities, which are often overpermissioned.

“AI support agents are often overpermissioned in ways that may have unintended consequences — such as ‘helpfully’ reconfiguring security settings or granting access that can lock entire teams out of their identity systems or punch holes in corporate VPNs,” explained Semperis. As deployment of AI agents increases, so does the risk. Since AI agents often have the ability to do anything, it is vital to implement disciplined controls. While sufficient controls may not yet have been implemented, 90% of respondents said AI identity governance is a top security priority for the organization.

Semperis stresses that security controls need to be implemented to reduce risk, such as applying the principle of least privilege to AI identities, designating identity infrastructure, implementing backup and recovery controls, and segregating agent and human trust boundaries where appropriate. Organizations need to work on the assumption that AI identities will eventually be compromised, so they must therefore need to plan for that eventuality and ensure that they have the policies and procedures in place to allow them to rapidly respond and make a quick and full recovery.

“What’s striking isn’t just how quickly AI is being integrated into identity systems but how unprepared many organizations are to recover when things go wrong,” explained Grace Cassy, Partner, Ten Eleven Ventures. “Introducing AI at the identity layer offers operational advantages, but it must be accompanied by guardrails, observability, and recovery readiness. It’s a new dimension of an old question, really: Are you resilient enough to respond in the event of critical disruption?”

The Semperis State of Identity Security in the AI Era Report can be downloaded here.

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