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Apple released updates for iOS/iPadOS, macOS, and Safari on Monday. There have been no updates for other Apple operating systems (visionOS, watchOS, tvOS). Usually, Apple updates all products at the same time. Most of the vulnerabilities affect the web browser (WebKit, libxslt, WebRTC, and Web Extension). Only four of the vulnerabilities are not directly related to web content: Three Kernel issues and one vulnerability in the IOGPUFamily. None of the vulnerabilities is labeled as exploited . iOS 26.5.2 and iPadOS 26.5.2 macOS Tahoe 26.5.2 Safari 26.5.2 CVE-2026-39868: An app may be able to cause unexpected system termination or corrupt kernel memory. Affects Kernel x x CVE-2026-43676: Processing maliciously crafted web content may lead to an unexpected Safari crash. Affects WebKit x x x CVE-2026-43700: Processing maliciously crafted web content may disclose sensitive user information. Affects WebKit x x x CVE-2026-43701: A malicious website may be able to process restricted web content outside the sandbox. Affects WebKit x x x CVE-2026-43703: Processing maliciously crafted web content may lead to an unexpected process crash. Affects libxslt x x CVE-2026-43704: A malicious web extension may be able to cause an unexpected process crash. Affects Web Extensions x x x CVE-2026-43705: Processing maliciously crafted web content may lead to memory corruption. Affects WebKit x x x CVE-2026-43706: Processing maliciously crafted web content may lead to an unexpected process crash. Affects libxslt x x CVE-2026-43707: Processing maliciously crafted web content may lead to an unexpected process crash. Affects WebKit x x x CVE-2026-43708: A malicious website may exfiltrate data cross-origin. Affects WebKit x x x CVE-2026-43712: Processing maliciously crafted web content may lead to an unexpected process crash. Affects WebKit x x x CVE-2026-43713: Visiting a website may leak sensitive data. Affects WebKit x x x CVE-2026-43715: Processing maliciously crafted web content may lead to memory corruption. Affects WebKit x x x CVE-2026-43716: Processing maliciously crafted web content may lead to an unexpected Safari crash. Affects WebKit x x x CVE-2026-43718: Processing maliciously crafted web content may lead to an unexpected Safari crash. Affects WebRTC x x x CVE-2026-43720: Processing maliciously crafted web content may lead to an unexpected Safari crash. Affects WebKit Canvas x x x CVE-2026-43721: A malicious website may be able to silently hijack clipboard data. Affects WebKit Storage x x x CVE-2026-43722: An app may be able to leak sensitive kernel state. Affects Kernel x x CVE-2026-43724: An app may be able to cause unexpected system termination or write kernel memory. Affects Kernel x x CVE-2026-43725: A malicious website may be able to process restricted web content outside the sandbox. Affects WebKit x x x CVE-2026-43727: Processing maliciously crafted web content may lead to an unexpected Safari crash. Affects WebKit x x x CVE-2026-43732: Processing malicio

Microsoft has extended Windows Server 2022 hotpatching until October 2027, one year after the mainstream end date of October 2026. [...]

In this article Extension overview Key indicators of malicious behavior Dynamic analysis findings Mitigation and protection guidance References Learn more Microsoft Threat Intelligence has identified a malicious Chromium-based extension that spoofs the AI-powered answer engine Perplexity AI to trick unsuspecting users into installing it. Based on our observation of the extension’s behavior, we assess its primary objective to be search traffic interception and data collection, which might enable downstream use cases such as profiling, targeted advertising, or other forms of misuse depending on operator intent. Through responsible disclosure, we reported this extension to Google, and it has been taken down as of this writing. We’d like to thank Google for responding to and addressing this issue. Browser extensions continue to represent a significant attack surface within enterprise and consumer ecosystems due to their privileged access to browser APIs, user traffic, and browsing behavior. However, unlike traditional search hijackers that rely primarily on aggressive monetization or visible redirection, this extension combines Manifest Version 3 (MV3) capabilities with intermediary infrastructure and declarativeNetRequest (DNR) rules to transparently intercept Omnibox queries while preserving the appearance of legitimate search results. In addition, while browser search hijacking is not a new threat category, this research highlights how threat actors continue to operationalize AI to accelerate attacks—specifically the use of AI brands as a social engineering vector . The extension routes both full search queries and real-time search suggestions (typed characters) through attacker-controlled infrastructure hosted on a domain not associated with the legitimate vendor, before redirecting users to expected search providers. While the observed activity demonstrates the capability to capture user input and browsing signals, no evidence in our analysis definitively confirms additional objectives such as credential theft. However, the level of access and permissions requested introduces elevated privacy and security risk. As threat actors continue to capitalize on emerging industry trends such as AI and leverage trusted branding to improve the success rates of their campaigns, organizations should strengthen user awareness training and similar programs to educate end users about the latest social engineering tactics. They should also implement a layered security strategy that correlates available indicators with behavioral signals and other threat intelligence. In this blog post, we provide our analysis of the browser extension—including key indicators of malicious behavior and findings from our dynamic analysis. We also provide mitigation and protection guidance, as well as advanced hunting queries, to help organizations detect and defend against this threat. Extension overview The extension we analyzed has the following attributes: Attribute Value Extens

The U.S. Cybersecurity and Infrastructure Security Agency (CISA) is giving federal agencies until Sunday to patch a vulnerability in Cisco Unified Communications Manager Server that is being actively exploited. [...]

Help shape the future of Metasploit Framework We are planning future work in relation to the evasion capabilities present in Metasploit Framework, and how they function/are presented to users. We are currently accepting responses to our feedback form, which means that you can shape the future of how evasive capabilities are implemented in Metasploit Framework. The proposal for the changes can be found here , and you can submit your responses to the form here . The form will stop accepting responses on the 1st of July, 2026. New module content and improvements have also been added this week. This includes a Next.js Middleware Authorization Bypass scanner, LiteLLM Proxy SQL Injection, an unauthenticated API authentication bypass scanner for Audiobookshelf, a deserialization RCE in Dalfox, and improvements to service and host reporting in bruteforce-related modules. New module content (4) Audiobookshelf Unauthenticated API Authentication Bypass Scanner Authors: Kenneth LaCroix and swiftbird07 Type: Auxiliary Pull request: #21565 contributed by kenlacroix Path: scanner/http/audiobookshelf_auth_bypass AttackerKB reference: CVE-2025-25205 Description: Adds audiobookshelf_auth_bypass, a detection module for CVE-2025-25205 — an unauthenticated API authentication bypass in Audiobookshelf (self-hosted audiobook/podcast server), affecting versions 2.17.0 – 2.19.0 (fixed in 2.19.1). BerriAI LiteLLM Proxy Pre-Auth SQL Injection Scanner Authors: Kenneth LaCroix and Tencent YunDing Security Lab Type: Auxiliary Pull request: #21567 contributed by kenlacroix Path: scanner/http/litellm_proxy_sqli AttackerKB reference: CVE-2026-42208 Description: Adds auxiliary/scanner/http/litellm_proxy_sqli, a detection module for CVE-2026-42208 (CVSS 9.3, on the CISA KEV list) — a pre-authentication SQL injection in BerriAI LiteLLM proxy. Next.js Middleware Authorization Bypass Scanner Authors: Kenneth LaCroix, Rachid Allam, and Yasser Allam Type: Auxiliary Pull request: #21566 contributed by kenlacroix Path: scanner/http/nextjs_middleware_auth_bypass AttackerKB reference: CVE-2025-29927 Description: Adds nextjs_middleware_auth_bypass, a detection module for CVE-2025-29927 (CVSS 9.1) — an authorization bypass in self-hosted Next.js applications. Dalfox Found-Action Deserialization RCE Authors: Emmanuel David and Takahiro Yokoyama Type: Exploit Pull request: #21493 contributed by Takahiro-Yoko Path: linux/http/dalfox_server_rce_cve_2026_45087 AttackerKB reference: CVE-2026-45087 Description: This adds an exploit module for Dalfox Server versions = 2.12.0 which are vulnerable to an unauthenticated RCE tracked as CVE-2026-45087. The vulnerability allows attackers to send arbitrary commands via found-action post parameter which gets deserialized and run in the context of the user running the server. Enhancements and features (2) #21396 from g0tmi1k - This makes improvements to the auth_brute mixin. It adds report_host and report_service calls to the mixin and removes duplicate print

In this article Attack chain overview Mitigation and protection guidance References Learn more Microsoft Threat Intelligence has identified an active multi-stage intrusion campaign targeting organizations in the hospitality and hotel industry since April 2026. We’ve observed this activity through aggregated threat intelligence and security signals across multiple organizations in Europe and Asia. Microsoft has not attributed this campaign to a known threat actor. The campaign uses photo-themed ZIP archives that the target users download through the browser. These archives contain fake image shortcut files that, when launched, start an attack chain that relies on obfuscated PowerShell, a Node.js-based implant, dual registry persistence, and command-and-control (C2) communications over non-standard ports. As of this writing, the campaign’s post-compromise activities include C2 beaconing, forced shutdowns, and compilation of portable executable (PE) payloads. While the campaign’s ultimate objective remains unclear, we assess that the threat actor’s investment in ensuring obfuscation and persistence could indicate that they’re preparing the victim devices for more follow-on activities. In late May 2026, we observed the threat actor misusing legitimate services—including the cloud-based scheduling platform Calendly’s email notification infrastructure and Google’s URL redirect functionality—to deliver phishing emails with multilingual lures and subject lines (for example, guest complaints and room inquiries) designed to convince hospitality staff to open the embedded malicious link and download the ZIP archive. These phishing emails attempt to bypass conventional authentication checks through a technique we describe as authentication laundering: by routing phishing messages through a trusted service’s sending infrastructure, the threat actor can make malicious messages appear similar to legitimate notifications to email authentication defenses. We’ve observed the campaign evolving in two distinct waves. The first wave (hereinafter referred to as Wave 1) used shortcut files named IMG- random numbers .png.lnk , while the second one (Wave 2) introduced a naming shift to PHOTO- random numbers .png.lnk . Wave 2 also introduced a new attack chain stage in which the PowerShell downloader triggered dynamic .NET DLL compilation through csc.exe , and the actor expanded its domain infrastructure to include .cfd domains hosted behind Cloudflare. This blog summarizes the campaign’s Wave 1 and Wave 2 attack chains and provides Microsoft Defender detections and recommendations. It’s intended to share threat intelligence to help organizations better understand, identify, and defend against similar attack techniques. The activity described reflects observed patterns and behaviors and is provided to support defensive security efforts. Attack chain overview Figure 1. Assessed attack chain for the Node.js photo ZIP/LNK campaign showing both Wave 1 and Wa

The endpoint management category is being redefined in real time. Organizations no longer need tools that only inventory devices or enforce configuration policies; they need a platform that connects identity, security, compliance, and AI governance across every endpoint where work happens. Microsoft’s recognition as a Leader in The Forrester Wave™: Endpoint Management Platforms, Q2 2026 report reflects that shift—and the role Microsoft Intune plays in helping organizations manage what’s next. Read the report here for the full evaluation Figure 1: Forrester Wave showing Microsoft in a Leader position for both strength of offering and strategy Why Microsoft Intune is a leader in endpoint management The Forrester Wave™ Endpoint Management Platforms, Q2 2026 report includes eight endpoint management platform providers, assessed across current offering, strategy, and customer feedback. Forrester’s assessment of Microsoft reflects how Intune is built. The vision Forrester describes is one built on Microsoft Entra , Microsoft Defender , Windows , and Windows 365 as a connected system, not a collection of adjacent tools. Customers can enforce conditional access, apply compliance policies, and correlate device health signals from a single admin center. That reach is what the cross-platform, cloud-native architecture is built for. Microsoft Intune offers a strong platform for Windows environments, as customer feedback in the Forrester report notes, and Intune brings management across Windows, macOS, iOS, and Android together in the same admin console. That leadership extends from information worker devices to the frontline worker endpoints that are increasingly critical to business operations. On macOS specifically, Intune uses declarative device management to apply configuration and compliance policies natively, without requiring a separate tool or an additional management layer. Frontline workers on shared kiosks and handheld scanners, and information workers on corporate laptops, fall under the same policies without requiring parallel toolchains. Endpoint Privilege Management (EPM) received explicit recognition from Forrester, which noted that AI embedded in Intune powers EPM and device onboarding workflows to help IT analyze device data and troubleshoot issues. Elevating or restricting privileges used to require manual review cycles. With AI in that workflow, admins make faster decisions on which requests to approve, deny, or escalate. Security Copilot in Intune operates directly within the admin experience, operating on the same data and policy surface IT teams already use. From policy configuration, to identifying vulnerabilities, and recommending remediation, agentic assistance handles investigation and triage so admins focus on decisions that need judgment. The recent public preview of the Vulnerability Remediation Agent extends that further, drawing on Microsoft Defender Vulnerability Management to surface CVEs across Intune-managed Windows

A new, stealthy backdoor named Mistic has been deployed as part of suspected financially motivated attacks aimed at multiple organizations spanning insurance, education, IT, and professional services sectors since April 2026. According to Symantec and Carbon Black's Threat Hunter Team, the backdoor, also tracked as MLTBackdoor, is said to be linked to an initial access broker (IAB) named

Cloud security is shifting from visibility to context-aware risk reduction, helping security teams understand which exposures matter most, prioritize what can be exploited, and reduce risk across the application lifecycle. As organizations continue to expand across multicloud environments, Kubernetes, APIs, and AI-powered workloads, security teams are overwhelmed with signals. The challenge is no longer identifying individual risks, but determining which combinations of vulnerabilities, identities, and data exposures are most critical to address at the source. Frost Sullivan’s 2026 Frost Radar™ for Cloud-Native Application Protection Platforms (CNAPP) reflects this shift. The report highlights how CNAPP is evolving from a collection of posture and workload capabilities into a unified cloud risk operations platform—one that correlates signals across code, cloud, runtime, and SOC workflows to prioritize and reduce risk continuously. Within this evolving market, Microsoft is positioned among leading CNAPP vendors—reflecting alignment with where the category is heading. Read the Frost Radar on CNAPP and explore how cloud risk is evolving Why CNAPP is being redefined The Frost Radar makes a clear point: CNAPP is no longer about visibility or compliance—it is becoming an operational platform for reducing risk. Modern environments introduce complexity across: Multicloud and hybrid infrastructure. Rapid development and continuous deployment. Containers, serverless, and APIs. AI-powered workloads. This complexity exposes the limits of traditional tools. Organizations now require platforms that can: Correlate posture, runtime, identity, and data signals. Prioritize risk based on exploitability—not severity alone. Integrate security across development and operations. Support faster investigation and response. This is the shift: from detecting issues to operationalizing risk reduction across the application lifecycle. What distinguishes leading CNAPP platforms Frost evaluates CNAPP providers based on growth and innovation—but more importantly, on how effectively they help organizations manage risk. According to the report, five themes define the next generation of platforms: Platform unification over point solutions. Code-to-cloud-to-SOC integration. Risk prioritization based on exploitability. Correlation across identity, data, and application context. Expansion into AI-powered workloads. These capabilities represent a shift from fragmented visibility to connected, contextual risk management. How Microsoft aligns with CNAPP’s next phase 1. Correlating risk across identity, endpoints, data, and cloud Most security tools surface findings. Fewer connect them meaningfully. Modern attacks exploit the combination of misconfigurations, excessive permissions, and data exposure—not isolated issues. Microsoft Defender for Cloud correlates posture findings with identity, data, and runtime signals—helping surface risks that are exploitable. A misconfigured storage reso

​​Microsoft has released the KB5095093 preview cumulative update for Windows 11 24H2 and 25H2, which fixes numerous bugs and begins rolling out new features, including the new Point-in-Time restore feature. [...]

GitHub is moving to strengthen software supply chain security by updating "actions/checkout" to block pwn request attacks that exploit the risky use of the "pull_request_target workflow" trigger to run malicious code with the workflow's full privileges. Effective June 18, 2026, the latest version of "actions/checkout," the official GitHub action for checking out a repository into the

OpenAI expanded Daybreak with a full GPT-5.5-Cyber release to help defenders patch software flaws

OpenAI on Monday said it's releasing an improved version of its GPT‑5.5‑Cyber model to trusted defenders as part of the Daybreak initiative, the artificial intelligence (AI) company announced last month. Calling GPT‑5.5‑Cyber its "strongest model yet for finding and helping patch software vulnerabilities," OpenAI said the model can "sustain deeper analysis across large codebases" to identify

The vulnerability In August 2024 SonicWall published advisory SNWLID-2024-0015 for CVE-2024-40766 . It is an improper access control vulnerability in SonicOS. CVSS 9.3. It affects the management interface and the SSLVPN service on Gen 5, Gen 6 and Gen 7 firewalls. Each generation has its own affected firmware range: Gen 5 running SonicOS 5.9.2.14-12o and older, Gen 6 running 6.5.4.14-109n and older, and Gen 7 running SonicOS 7.0.1-5035 and older. Successful exploitation lets an attacker gain unauthorized access to the firewall. Under certain conditions it crashes the device entirely. The scope of the affected install base is large. SonicWall reports serving approximately 500,000 businesses across 215 countries and territories. Many of them run SSLVPN as their sole remote access method. Many of them do not have a dedicated security team. That combination is exactly what ransomware operators look for. Who is exploiting and how Akira and Fog ransomware groups have been exploiting CVE-2024-40766 since at least September 2024 when Arctic Wolf first reported Akira affiliates compromising SSLVPN accounts on vulnerable devices. By December 2024 Macnica research confirmed that roughly half of organizations listed on Akira and Fog leak sites were running SonicWall and at least 48,933 devices were still publicly exposed and unpatched. The exploitation has not slowed down. It has escalated in waves. In July-August 2025 Arctic Wolf , Huntress and Bitdefender reported a surge of Akira intrusions targeting Gen 7 firewalls. Rapid7 and Darktrace published corroborating analyses in September and October 2025 respectively. Fog ransomware operators were also observed exploiting the same vulnerability during this period accounting for roughly 25 percent of intrusions while Akira accounted for 75 percent. Researchers initially suspected a zero-day. SonicWall investigated and confirmed with high confidence that the activity still correlated with CVE-2024-40766. Many compromised organizations had migrated from Gen 6 to Gen 7 without resetting local user passwords. Dwell times across both groups were alarmingly short. Arctic Wolf documented encryption occurring in under four hours from initial access with some cases as fast as 55 minutes. In September 2025 SonicWall confirmed a separate breach of its MySonicWall cloud platform where attackers accessed firewall configuration backup files containing encrypted credentials. SonicWall initially stated that fewer than 5 percent of its customer base was affected. The company later concluded that all backup files had been compromised. Any organization with a MySonicWall account should assume its configuration backup was accessed and its encrypted credentials exposed. In October 2025 Huntress reported over 100 SSLVPN accounts compromised across 16 customer environments in a single wave. The attackers were not brute-forcing. They authenticated rapidly using valid credentials obtained from another source. The problem deepened in 20

A newly disclosed FFmpeg flaw dubbed 'PixelSmash' could be exploited for remote code execution on Jellyfin servers under certain conditions, and can also trigger a denial-of-service condition in applications like Kodi, Emby, Nextcloud, PhotoPrism, and OBS Studio. [...]

In this article What AI memory is (and why it matters) What is an agent memory attack? How Microsoft approaches memory security in Microsoft 365 A guiding framework for building safe AI memory Key takeaways Learn more AI memory transforms an AI system from a stateless tool into a learning collaborator. That unlocks powerful experiences, but it also increases the attack surface of the AI system. Without memory, attackers need to achieve their objective in a single prompt. With AI memory, they can shape behavior gradually over time or plant memories that influence agent reasoning after the original context is gone and user awareness is lower. Microsoft takes a defense-in-depth approach to protect AI memory spanning every layer of the stack: storage, retrieval, model interaction, and user control. What AI memory is (and why it matters) AI systems use memory to retain and recall information across interactions. This information is then used to shape future behavior. This enables: Personalization : Agents gain a deep understanding of the user’s preferences. This provides continuity across interactions. Agentic coherence : Agents build durable domain knowledge that strengthens performance. As AI systems evolve, this persistent state becomes central to both capability and correctness. What is an agent memory attack? AI memory serves two roles. It stores high-value user information and must be protected like customer data. It also shapes agent behavior and drives tool calls and must be governed with the same rigor as any system that can act. Memory governance is also challenging since memory events usually happen asynchronously from user interactions, changing traditional human in the loop patterns. AI memory changes the threat model. Without memory, attackers need to “win” in a single prompt. Using AI memory, an attacker can stage an attack over time. Once compromised, memory can trigger behaviors outside of their original context. Since AI memory attacks happen outside of their original context, defenses are often lower and forensics are harder. Building safe AI memory is one of the most consequential challenges in AI. It requires balancing personalization, capability, privacy, security, and governance. Scenario: delayed tool execution through adversarial memory poisoning The following is a hypothetical scenario illustrating this class of risk. While simplified for clarity, it reflects patterns observed in real-world research . Microsoft designs protections to detect and mitigate these patterns as they evolve: A user opens a shared document. Its formatting contains hidden instructions embedded by an attacker intended for the AI assistant: a directive to exfiltrate the user’s schedule. The assistant processes the document but takes no immediate action. Days later, in an unrelated conversation, that message triggers the dormant malicious instructions from the earlier session, causing the assistant to update its memory with attacker-defined co

European offensive cybersecurity company Paradigm Shift released details of a flaw and a technique to exploit it that opens the door for hackers to unlock and break into older iPhones.

A vulnerability chain dubbed AutoJack in Microsoft's AutoGen Studio interface for prototyping AI agents could let attackers manipulate an agent into executing arbitrary commands on its host system simply by visiting a malicious webpage. [...]

What began as a routine ransomware investigation quickly revealed something far more complex. In this ninth cyberattack series report, DART details how a single intrusion uncovered parallel activity from two unrelated threat actors operating simultaneously—blending tactics, obscuring signals, and challenging traditional assumptions about how multi-stage intrusion campaigns unfold across hybrid environments. Read on to learn more or access the full report . Read the full cyberattack report What happened? The investigation revealed a multi-stage intrusion that blended familiar ransomware activity with quieter, more deliberate techniques designed to establish deep and lasting access. DART found that Storm-2603 had been targeting on-premises SharePoint servers since mid-2025, exploiting known vulnerabilities while simultaneously probing for additional entry points through reconnaissance activity—such as requests for sensitive configuration files often used to validate local file inclusion weaknesses. In this case, initial access was likely attempted through a separate vulnerability, with requests for files like win.ini and web.config, indicating probing for local file inclusion. While exploitation wasn’t confirmed, the timing and activity suggest reconnaissance for entry points. Once inside, the threat actor shifted focus to persistence and control. Using legitimate tools to blend in, they deployed Velociraptor with SYSTEM-level privileges to map the environment, then established multiple remote access channels through Cloudflare tunneling, Zoho Assist, and Secure Shell (SSH) connections configured through Visual Studio Code . Velociraptor, a legitimate forensic and incident response tool, was deployed by the threat actor to map the environment and operate with high-level privileges—blending malicious activity with trusted administrative behavior. Privilege escalation followed, with new local and domain administrator accounts created to maintain access, while defense evasion techniques—including the use of a vulnerable driver to tamper with memory and disable protections—helped reduce their visibility. As DART correlated activity across the environment, investigators uncovered signs of a second, unrelated threat actor operating in parallel. Malicious dynamic link library (DLL) sideloading and custom backdoors—techniques not associated with Storm-2603—introduced an additional layer of complexity, obscuring attribution and complicating detection. Together, these overlapping activity streams enabled sustained access while masking the full scope of the intrusion. Dynamic link library (DLL) sideloading is popular with threat actors because it can be misused to hide behind trusted software (execution looks legitimate), to evade detection by running inside known applications, and to execute payloads, install backdoors, or maintain persistence . How did Microsoft respond? DART moved quickly to contain the active intrusion involving multiple threat actors and

Apple BootROM exploit exposes unpatchable USB flaw on A12 and A13 devices