The bugs could lead to authentication bypass, shell command execution, and memory corruption.

The post Fortra Patches Critical Vulnerabilities in BoKS appeared first on SecurityWeek.

The China-based hacking group has been exploiting SharePoint vulnerabilities since July 2025.

The post Warlock Expands SharePoint Exploitation in Critical Infrastructure Attacks appeared first on SecurityWeek.

CVE-2026-104286 is a critical-severity path traversal vulnerability that could allow attackers to write arbitrary files to the system.

The post Exploited Fortinet FortiMail Zero-Day Calls for Urgent Action appeared first on SecurityWeek.

Roughly a dozen vulnerabilities have been patched in each of the open source cryptographic libraries. 

The post High-Severity Vulnerabilities Patched in OpenSSL, WolfSSL appeared first on SecurityWeek.

Branch Target Reuse (BTR) is a new Spectre v2 attack targeting JIT compilers in web browsers, language runtimes, and the operating system kernel

The post New Spectre v2 Variant Exposes Intel, AMD, Arm CPUs to Data Leaks appeared first on SecurityWeek.

Apple released iOS and macOS updates to patch a zero-day vulnerability (CVE-2026-86950) reported by Meta’s product security team.

The post Apple Patches Zero-Day Linked to ‘Extremely Sophisticated Attack’  appeared first on SecurityWeek.

Over the past year, our Global Emergency Response Team (GERT) has investigated several incidents involving the NightEagle group (also tracked as APT-Q-95). This group has been active since at least 2023 and originally focused on organizations in Asia. We have now identified attacks by the group targeting businesses in Russia. This post examines both known and new tools NightEagle used in its latest campaign.

Initial access

In most incidents, the attackers used compromised valid credentials to gain access to corporate VPNs. VPN connections originated from IP addresses in the Russian segment linked to Cloudflare WARP tunnels, as well as from IP addresses associated with European virtual infrastructure providers.

GhostContainer on Microsoft Exchange

Both during the initial access stage and as the attack progressed, the attackers deployed the GhostContainer backdoor on Microsoft Exchange servers. It incorporates components from several open-source projects, including the Neo-reGeorg tunnel, an exploit for the CVE-2020-0688 vulnerability, and the GhostWebShell class from the ysoserial utility. All of these components are publicly available on GitHub.

We were unable to determine the exact method the attackers used to deliver the backdoor to Microsoft Exchange servers. We believe with a high degree of confidence that they applied a technique already familiar to us: extracting the cryptographic keys used by Microsoft Exchange from the ASP.NET configuration, overwriting the VIEWSTATE framework parameter, and injecting a payload into it, which then launched the GhostContainer backdoor in memory.

The backdoor is a .NET assembly containing three classes that implement its core functionality:

• Stub: processes C2 commands delivered to the infected system through the x-owa-urlpostdata headers and evades detection by the Antimalware Scan Interface (AMSI) and Windows Event Log mechanisms by overwriting addresses in amsi.dll and ntdll.dll.
• App_Web_843e75cf5b63: accepts the fakePath and fakePageName parameters and creates virtual paths that redirect requests to the App_Web_8c9b251fb5b3 class.
• App_Web_8c9b251fb5b3: implements network traffic redirection (proxying) and socket forwarding functionality.

Kaspersky products detect the GhostContainer backdoor as Trojan.MSIL.GhostContainer.gen.

Traffic redirection

Once the attackers gain sufficient privileges during an attack, they leverage RDP to move laterally within the internal network segment. To do this, they download and run tools for tunneling and redirecting network traffic.

The attackers used GitHub repositories to host their archived tools. The names of the repositories and archives were disguised to look legitimate:

• https://github[.]com/mirror-js/mirror-js/refs/heads/main/js/js-webpack.zip
• https://github[.]com/mirror-js/mirror-js/refs/heads/main/js/jsonp-pack.zip
• https://github[.]com/browserthemes/resourcepack/releases/download/main/resource-pack.zip

The files contained within the archives were also given names mimicking known legitimate software, though unrelated to the archive names:

• adobe_32.exe;
• AdobeSync.exe;
• trueconf.exe;
• 1cbroker.exe;
• 1c-office-plugin.exe;
• trueconf-broker.exe.

Across the incidents we investigated, we found two tools that the attackers combined for traffic tunneling.

1. Microsoft dev tunnels
   This is a legitimate Microsoft mechanism that allows local web services to be published for internet access on *.*.devtunnels.ms domains. The attackers used this tunneling capability to expose port 3389 (RDP) on the compromised system.
   

   Execution graph of adobe_32.exe in Kaspersky Research Sandbox

2. rdp2tcp
   This is a publicly available tool for tunneling TCP traffic over an established RDP connection. It includes a server component that runs on the target system and a client component that runs on the attacker’s side.

   When virtual channels are opened and closed, corresponding events with IDs 132 (channel opened) and 148 (channel closed) are logged in the Microsoft-Windows-RemoteDesktopServices-RdpCoreTS/Operational.evtx Windows log. These events contain the names of the channels (such as XPSRD, cliprdr, Microsoft::Windows::RDS::DisplayControl, and others) used by the RemoteFX module, which extends the capabilities of the RDP protocol.

   When the rdp2tcp tool is used, events with IDs 132 and 148 will contain the channel name rdp2tcp or other random alphanumeric combinations chosen by the attackers.

   

   Creation event for a channel named rdp2tcp (server component startup)

The combination of Microsoft dev tunnels and rdp2tcp allows the attackers to maintain network access by using legitimate services without opening additional suspicious ports.

The attackers also used the atexec utility from the Impacket toolkit to create scheduled tasks on target systems. These tasks enabled network port forwarding through standard Windows functionality:

netsh interface portproxy add v4tov4 listenport=443 connectaddress=10.0.12.101 connectport=445

Lateral movement

To obtain elevated privileges and move laterally through the network, NightEagle exploited various vulnerabilities in Active Directory. The attackers used previously established tunnels to connect to internal infrastructure systems.

In one incident, they exploited a well-known RDP implementation vulnerability, CVE-2019-0708 (BlueKeep). They used the vulnerable mechanism to create a local account on the system and add it to the Administrators and Remote Desktop Users groups.

The attackers also requested Kerberos tickets with a non-standard combination of flags (Forwardable, Proxiable, Renewable) and attempted to replicate the Domain-Password object from the Active Directory database to impersonate the domain controller (a technique known as DCSync) after obtaining an account with sufficient privileges.

Through these methods, the attackers establish persistence in the infrastructure, obtain password hashes for domain accounts, use long-lived Kerberos tickets to gain legitimate access to target resources, and ultimately compromise domain controllers and the victim’s entire Active Directory infrastructure.

Takeaways

To expand the geographic scope of its targets, NightEagle is updating its methods and adopting new techniques for persistence and lateral movement. Despite the group’s efforts to stay hidden, timely detection of anomalies combined with a comprehensive approach to infrastructure protection can significantly hinder the attackers from achieving their goals. Since the attackers rely on known legitimate tools and infrastructure vulnerabilities, well-configured monitoring can help detect NightEagle’s presence on the network.

Detection by Kaspersky solutions

Kaspersky solutions reliably identify the malicious activity described above at various stages of the attack. We showed examples above of how Kaspersky Threat Analysis detects samples of the GhostContainer backdoor and the tunneling utility. This toolkit also includes the analytical solution Kaspersky Threat Attribution Engine (KTAE), which helps SOC analysts and incident responders determine which APT groups malware can be attributed to. The solution uses a proprietary comparison method that measures the similarity between analyzed samples of suspicious files and known malicious samples in Kaspersky’s collection.

The backdoor we discovered showed similarity to previously analyzed GhostContainer samples and a connection to the NightEagle APT group:

However, detection scenarios for this kind of attacks are not limited to file analysis. Deploying a backdoor on a target host produces numerous characteristic artifacts, which allow Kaspersky Endpoint Detection and Response Expert to alert users to anomalies in the infrastructure in a timely manner.

This malicious activity is detected by the following rules, available in the repository:

• Initial detection of the malicious signature occurs through the generic_ransomware_related_detection rule, based on EPP module events
• Detection of a malicious DLL’s .NET assembly being loaded via PowerShell: suspicious_assembly_loading_into_powershell_via_reflection
• Activity of tunneling and traffic redirection tools: detection_of_access_to_tunnel_domains_dns
• Use of tools from the Impacket toolkit, such as atexec:
  • impacket_possible_activity
  • attempt_to_download_hacktool_or_risktool_by_non_browser
  • credentials_dumping_tools_file_artifacts_creation
• Attempts to replicate an Active Directory database object to impersonate a domain controller: potential_dcsync_via_startupparameters

Kaspersky Anti Targeted Attack (KATA) detects this malicious activity in network traffic. For example, the Exploit.CVE-2019-0708.TCP.C&C signature allows detecting attempts to exploit the CVE-2019-0708 (BlueKeep) vulnerability.

Beyond this activity, KATA also detects other NightEagle actions in network traffic, such as the following:

• Traffic redirection and tunneling variations
• Attacks on Active Directory (DCSync, attempts to compromise AD CS, and others)
• Lateral movement across the network

Indicators of compromise

1dcafb7f8448683281106b06dd22409a	AdobeSync.exe
1f3034b706c78b35d8e34044e68c693a	adobe_32.exe
3ecd1cd627d0340c92901a478a7caad8 631fb131a56caf4ca0f287ed73e876ab	App_Web_Container_1.dll
4aa9fb1bf9223dfcdac920759bc7a3c7	1c-office-plugin.exe, 1cbroker.exe, trueconf.exe
https://github[.]com/mirror-js/mirror-js
https://github[.]com/browserthemes/resourcepack

The extortion group has modified its exploit in new attacks targeting the PeopleSoft vulnerability CVE-2026-35273.

The post Google Warns of ShinyHunters’ Fresh Oracle PeopleSoft Campaign appeared first on SecurityWeek.

The company says the measure was precautionary and that it has no evidence of Kiteworks or customer systems being compromised.

The post Kiteworks Urges Server Shutdown, Finds Advanced Forms Vulnerability appeared first on SecurityWeek.

Citrix has released patches for the critical NetScaler vulnerabilities tracked as CVE-2026-88771 and CVE-2026-88772.

The post Citrix Confirms 2 NetScaler Zero-Days After Admins Pulled the Plug appeared first on SecurityWeek.

CISA added CVE-2026-65660 to its KEV catalog, giving federal agencies a patching deadline of September 28.

The post Microsoft SharePoint Flaw CVE-2026-65660 Now Exploited in Attacks appeared first on SecurityWeek.

The vulnerability landscape shifted significantly in Q2 2026. First, the number of registered CVEs reached an unprecedented level. This is driven primarily by the widespread adoption of AI, both for application development and search for security flaws. This resulted in entire new classes of vulnerabilities emerging, particularly in the Linux networking subsystem.

Second, security researchers have been publishing exploits for unpatched vulnerabilities more frequently. Publications like these can generate significant fallout, since they potentially open the door for attackers to target unprotected systems.

Statistics on registered vulnerabilities

This section provides statistical data on registered vulnerabilities. The data comes from Kaspersky’s vulnerability knowledge base, which draws on the CVE database as well as the Russian BDU database and GitHub Advisory (GHSA). As a result, the figures for previous reporting periods may differ from those published in earlier reports.

We examine the number of registered vulnerabilities for each month over the last five years. As the chart below shows, this number continues to surge, a trend reflected across all the databases we track. It’s driven primarily by the widespread adoption of AI tools: as we predicted in our previous report, these tools have played a major role in the discovery of vulnerabilities in third-party software. Meanwhile, these tools often contain security issues of their own. For example, OpenClaw, a popular AI project, ranked 12th among those with the highest number of vulnerabilities discovered and published in Q2, with over 200 CVEs registered during the reporting period. Finally, AI development tools are also contributing to the vulnerability landscape, since the quality of the code they produce can vary widely. Therefore, the rate at which new vulnerabilities are discovered will inevitably keep growing.

Total published vulnerabilities per month from 2022 through 2026 (download)

Next, we analyze the number of new critical vulnerabilities (CVSS > 9.0) over the same period.

Total critical vulnerabilities published per month from 2022 through 2026 (download)

As the chart shows, the number of published critical vulnerabilities jumped sharply in Q2. This is because using AI for vulnerability research makes it possible to analyze massive amounts of previously unexamined code, uncover new attack surfaces, and identify entire classes of vulnerabilities that have gone unnoticed for decades. In particular, AI was used to find a series of Dirty Frag vulnerabilities in the Linux kernel.

Exploitation statistics

This section presents statistics on vulnerability exploitation for Q2 2026. The data draws on open sources and our telemetry.

Windows and Linux vulnerability exploitation

Q2 2026 saw a new precedent in the publication of vulnerabilities in Windows components and exploits for these: researchers no longer waiting for CVE registration, let alone patches. A case in point: a researcher who goes by Nightmare Eclipse (also known as Chaotic Eclipse) published a list of new “named” vulnerabilities across various Windows subsystems. At the time the technical details were published, none of the vulnerabilities had been assigned a CVE identifier:

• BlueHammer: a local privilege escalation vulnerability in Windows Defender. During signature database updates, a time-of-check to time-of-use (TOCTOU) race condition occurs, allowing an attacker to substitute the directory where temporary update files are written. The researcher published a fully functional exploit for the vulnerability.
• RedSun: another logical vulnerability in Windows Defender with a working exploit. Suspicious and malicious files marked as “cloud” can be overwritten or restored to their original directory with elevated privileges. The exploit incorporates fragments of algorithms that make it possible to leverage various logical vulnerabilities in Windows, effectively combining a large number of popular exploitation techniques.
• YellowKey: a vulnerability that lets the user bypass BitLocker full-disk encryption and access system data through the Windows Recovery Environment (WinRE). A fully functional exploit was also published.
• GreenPlasma: a vulnerability that enables system object injection via the CTF loader for the Collaborative Translation Framework (CTFMON) service in Windows. The original publication included an exploit with limited functionality.
• RoguePlanet: yet another Windows Defender vulnerability that, like BlueHammer, stems from a TOCTOU issue, this time in the engine responsible for real-time system scanning. The published exploit uses the vulnerability to overwrite the system file wermgr.exe with a malicious one.
• UnDefend: another vulnerability in the Windows Defender service. This time, the exploit causes a denial of service and blocks updates.

Even though such cases remain isolated for now, we believe they’ll grow into a full-fledged trend. Early publication of exploits gives attackers an advantage over software developers, who are left with no time to fix the issues.

Veteran vulnerabilities in Windows software also remain relevant. These are the ones our solutions most frequently detect exploits for:

• CVE-2018-0802: a remote code execution (RCE) vulnerability in the Equation Editor component
• CVE-2017-11882: another RCE vulnerability also affecting Equation Editor
• CVE-2017-0199: a vulnerability in Microsoft Office and WordPad that allows an attacker to gain control over the system
• CVE-2023-38831: a vulnerability in WinRAR that involves improper handling of objects within an archive
• CVE-2025-6218 (formerly ZDI-CAN-27198): another WinRAR vulnerability allowing the specification of relative paths to extract files into arbitrary directories, potentially leading to malicious command execution
• CVE-2025-8088: a vulnerability similar in exploitation method to CVE-2025-6218. The attackers used NTFS Streams to circumvent controls on the directory into which files are being unpacked

The vulnerabilities listed here can be leveraged to gain initial access to a vulnerable system and for privilege escalation. This underscores the critical importance of timely software updates.

That said, the number of Windows users who encountered exploits declined slightly in Q2, hitting an 18-month low.

Dynamics of the number of Windows users encountering exploits, Q1 2025 – Q2 2026. The number of users who encountered exploits in Q1 2025 is taken as 100% (download)

Linux also hit a rough patch in Q2 2026. Specifically, the period saw the disclosure of the Dirty Frag family of vulnerabilities, which lets an attacker reliably escalate privileges within the operating system.

All the vulnerabilities published in Q2 2026 were, in one way or another, related to the Linux caching subsystem. Here are the ones being most actively exploited:

• CVE-2026-31431 (Copy Fail): a local privilege escalation vulnerability in the Linux kernel that lets an unprivileged user modify the page cache and gain root privileges. Especially dangerous for cloud and containerized environments
• CVE-2026-43284, CVE-2026-43500 (Dirty Frag): a family of vulnerabilities in the Linux networking subsystem (IPsec ESP and RxRPC) that lets a local user overwrite the page cache and escalate privileges to root
• CVE-2026-46300 (Fragnesia): a local privilege escalation vulnerability in the Linux kernel related to packet fragment handling and the page cache mechanism. It lets an unprivileged user gain root privileges and is also classified as part of the Dirty Frag family
• CVE-2026-31635 (DirtyDecrypt): a Linux kernel vulnerability that lets a local attacker escalate privileges due to improper handling of decryption operations and page cache data modification
• CVE-2026-43494 (PinTheft): a Linux kernel vulnerability that lets a local user gain elevated privileges due to errors in the memory page pinning mechanism
• CVE-2026-46331 (pedit COW): a vulnerability in the Linux kernel’s traffic control subsystem (tc-pedit) that exploits a flaw in copy-on-write to modify the page cache and subsequently escalate privileges to root

The vulnerabilities described above were quickly embraced by attackers. At the same time, our solutions continue to detect exploitation attempts targeting older vulnerabilities as well:

• CVE-2022-0847: a vulnerability known as Dirty Pipe, which enables privilege escalation and the hijacking of running applications
• CVE-2019-13272: a vulnerability caused by improper handling of privilege inheritance, which can be exploited to achieve privilege escalation
• CVE-2021-22555: a heap out-of-bounds write vulnerability in the Netfilter kernel subsystem
• CVE-2023-32233: another Netfilter subsystem vulnerability that allows for Use-After-Free conditions and privilege escalation through improper processing of network requests

Dynamics of the number of Linux users encountering exploits, Q1 2025 – Q2 2026. The number of users who encountered exploits in Q1 2025 is taken as 100% (download)

In Q2 2026, the number of Linux users who encountered exploits declined slightly compared to Q1. Given that a significant share of new vulnerabilities are tied to the operating system’s caching subsystem, we recommend installing patches as quickly as possible, or disabling vulnerable kernel modules if patching isn’t an option.

Most common published exploits

The distribution of published exploits by software type in Q2 2026 includes categories that haven’t appeared in the sample for a long time. For instance, we’re once again seeing exploits targeting SharePoint. It’s worth noting that while several vulnerability write-ups for Exchange and SharePoint were published during the quarter, most turned out to be fake, AI-generated research. While the articles and exploit source code themselves look fairly polished, they describe nonexistent problems in the software or its components — often close to genuinely vulnerable mechanisms — in order to mislead researchers. This type of attack is aimed at increasing the time it takes to detect real vulnerabilities. In some cases, the description of a nonexistent vulnerability came bundled with completely unrelated malware.

Distribution of published exploits by platform, Q1 2026 (download)

Distribution of published exploits by platform, Q2 2026 (download)

Vulnerability exploitation in APT attacks

We analyzed which vulnerabilities were exploited in APT attacks during Q2 2026. The rankings provided below include data based on our telemetry, research, and open sources.

TOP 10 vulnerabilities exploited in APT attacks, Q2 2026 (download)

In Q2 2026, a trend emerged in APT attacks toward exploiting new vulnerabilities right from the moment they’re published. As before, we’re also seeing a large number of zero-day vulnerabilities. The Langflow vulnerability deserves particular attention: it’s one of the first cases of an APT group exploiting AI technology, which many organizations are only just beginning to integrate. Because most of this tech is proprietary, it has a considerable number of security blind spots. Therefore, given the growing number of AI-based automation tools, we strongly recommend going beyond the usual patching and developing secure procedures for credential use and sensitive data handling in systems that rely on agents and LLMs.

C2 frameworks

In this section, we examine the most popular C2 frameworks used by APT groups and analyze the vulnerabilities targeted by the exploits that interacted with C2 agents in APT attacks.

The chart below shows the frequency of known C2 framework usage in attacks during Q2 2026, according to open sources.

TOP 10 C2 frameworks used by APTs to compromise user systems, Q2 2026 (download)

Sliver, Havoc, AdaptixC2, and Metasploit remain the most widely used C2 frameworks. After studying open sources and analyzing samples of malicious C2 agents that contained exploits, we determined that the following vulnerabilities were utilized in APT attacks involving the C2 frameworks mentioned above:

• CVE-2026-35273: a vulnerability in Oracle PeopleSoft PeopleTools that security vendors classify as server-side request forgery (SSRF). The details of the vulnerability have never been disclosed, although some research covers the post-exploitation steps
• CVE-2023-46604: an insecure deserialization vulnerability in Apache ActiveMQ that allows arbitrary code execution in the context of the service process
• CVE-2024-12356 and CVE-2026-1731: command injection vulnerabilities in BeyondTrust software that allow an attacker to send malicious commands even without system authentication
• CVE-2023-36884: a vulnerability in the Windows Search component that allows commands to be run on the system, bypassing the mark-of-the-web (MoTW) mechanism
• CVE-2025-53770: an insecure deserialization vulnerability in Microsoft SharePoint that allows for unauthenticated command execution on the server
• CVE-2025-8088 and CVE-2025-6218: similar directory traversal vulnerabilities in WinRAR that allow files to be extracted from an archive to a predetermined path, potentially without the archiving utility displaying any alerts to the user

These vulnerabilities show that attackers used them for initial access and privilege escalation on vulnerable systems, setting the stage for launching a C2 agent. They include both zero-day vulnerabilities and fairly well-known security issues.

LLM/AI tool vulnerabilities

This section analyzes data published in Kaspersky’s vulnerability knowledge base. We reviewed the Q2 2026 version of the knowledge base.

As mentioned above, AI tools, plugins, and technologies have proven fairly effective at automating the search for problematic code and anomalous behavior. The high speed at which new vulnerabilities are being discovered has naturally created a need to fix them just as quickly. AI is often used for this too, which increases the volume of code being generated. However, neither code written without human involvement nor AI-generated advice is always correct.

The chart below covers registered vulnerabilities in AI tools for 2025–2026.

Number of published vulnerabilities in LLMs, AI tools, and plugins with similar functionality, 2025–2026 (download)

As the charts show, AI tools are racking up a substantial number of registered vulnerabilities, and that number keeps growing quarter over quarter. It’s also worth looking at how AI tool vulnerabilities break down by type, according to the CWE system:

Interestingly, vulnerabilities of an undetermined type have ranked first in every quarter since the start of 2025. Traditionally-made software has the same issue, and it doesn’t look like the growing number of AI tools will fix it. It’s also notable that the list includes classes CWE developers themselves don’t recommend using for vulnerability classification, since they lump together a whole range of more specific types. CWE-284 is an example of this.

Looking at the most common classes, the key issues found in AI-related software can be summed up as follows:

• Inadequate access control over critical system objects
• Improper implementation of authentication and authorization mechanisms
• Injections

It’s worth noting that injection-related vulnerabilities were relatively rare before AI agents took off (previously, they mostly affected web apps). Recently, though, these security issues have become relevant again.

Looking back at a year and a half of the AI boom, one conclusion stands out regarding registered vulnerabilities: AI tool developers are more focused on expanding functionality than on security. This is worth keeping in mind when using these tools. Let’s look at the projects and applications that either integrated AI tools or offered them as the core product. Below is a list of the those with the highest number of registered vulnerabilities for 2025–2026.

TOP AI/LLM-related projects by number of published vulnerabilities, 2025–2026 (download)

Notable vulnerabilities

This section highlights the most significant vulnerabilities published in Q2 2026 that have publicly available descriptions. Since the above already covers several significant vulnerabilities published during the reporting period, this section consists mainly of LLM/AI tool vulnerabilities.

CVE-2026-25253: a gatewayUrl vulnerability in OpenClaw

The issue stems from the fact that the OpenClaw user interface trusts the value of the gatewayUrl parameter passed in the URL and automatically establishes a WebSocket connection to the specified address. During this connection process, it sends an authentication token without any additional user confirmation.

The attack algorithm exploiting this vulnerability works as follows:

1. The application obtains a critical connection address from an external source (the gatewayUrl URL parameter), which is controlled by the attacker.
2. There is no validation before use.
3. The client automatically initiates a connection to the address specified in the parameter, which belongs to the attacker.
4. While connected, the application sends credentials (an access token) to the specified address.

If the attacker obtains a valid token, the consequences depend on that token’s level of access within the system. In general, this could lead to:

• User session compromise
• Execution of operations on the user’s behalf
• Modification of the AI agent configuration
• Unauthorized access to tools and resources connected to the agent
• Under certain OpenClaw configurations, further compromise of the host running the agent

It’s worth noting that the risk of exploitation arises from a combination of several factors: the automatic connection and token transmission, the lack of address trust verification, and the high privileges granted to the local AI agent.

CVE-2026-41948: a path traversal vulnerability in the Dify AI platform

The vulnerability lets an authenticated user craft a request that enables the application to escape its permitted tenant and gain access to internal REST APIs that weren’t meant for that user. The root cause is insufficient normalization and validation of the URL path before it’s passed to the internal service.

Depending on the Dify configuration, the consequences can include:

• Unauthorized access to internal service interfaces
• Breach of isolation between workspaces
• Exposure of internal service information
• Conditions favorable to further attacks when combined with other vulnerabilities

The use of Dify in enterprise AI platforms is particularly risky, since internal services there tend to hold elevated privileges.

CVE-2026-45386: an improper access control vulnerability in Open WebUI

In Open WebUI, pin/unpin operations on messages are write operations, since they modify that message’s metadata (is_pinned, pinned_by, pinned_at). In vulnerable versions, however, before performing these actions, the API only checked for read access to the channel (a chat between a user or group and the AI) containing the message, not permission to modify its content. As a result, a user with a role limited to viewing messages could still change a message’s pinned status.

The vulnerability’s mechanism works as follows:

1. The user initiates an action that changes the state of an object.
2. The application treats this action as a regular read request.
3. Only channel view permission is checked.
4. The application performs a write without verifying the required user authorization.

This violates one of the fundamental principles of access control models — namely, that any operation that changes the state of data must be checked for the appropriate write or moderation permissions, regardless of whether the object itself is readable.

Although the vulnerability doesn’t lead to arbitrary code execution or compromise of sensitive data, it can affect data integrity and collaborative workflows. Potential consequences of exploitation include unauthorized pinning or unpinning of messages, disruption of channel moderators’ and administrators’ activities, changes to the display order of important information, and even the potential spread of false or misleading information by altering the channel containing a pinned message.

Open WebUI is widely used as an interface for interacting with local and enterprise LLMs. In these systems, pinned messages often contain important instructions, announcements, or tips for users. The ability to modify them with minimal privileges can disrupt collaborative workflows, cause confusion, and undermine trust in information published by administrators and moderators.

CVE-2026-45501: a vulnerability in Microsoft Exchange

The vulnerability stems from improper neutralization of user input when generating Exchange web pages. As a result, the browser may interpret specially crafted data as active content instead of plain text.

Although Microsoft categorizes the potential impact of exploiting this vulnerability as spoofing, flaws like this can lead to alteration of displayed content, imitation of trusted interfaces, actions on behalf of the user within an active session, and abuse of user trust.

It’s worth noting that issues like this are still relevant in modern software, given that mechanisms like Content Security Policy and various parsers were specifically created to help developers neutralize dangerous parts of user page content.

Conclusion and advice

Q2 brought the first significant results of AI automation adoption in software development and vulnerability hunting tools. This research shows that beyond traditional patch management, organizations now need real-time monitoring of systems and access controls, since infrastructure and everyday applications now contain far more AI functionality that could lead to compromise.

Accordingly, besides quickly detecting infrastructure vulnerabilities and managing security patches, modern enterprise-grade security solutions need to provide a broad range of preventive measures for tracking the overall health of systems and workstations. Kaspersky Next meets these requirements by combining proactive mechanisms with the ability to respond promptly to emerging threats.

Overview of the attack

In July 2026, Kaspersky experts detected a new attack by the Head Mare group. Previously, we classified them as hacktivists, but now we define them as an APT group due to the sophistication of their TTPs and the absence of destructive activity (encryption, wiping) in the targeted infrastructures. In this latest campaign, the attackers exploited a chain of vulnerabilities in the TrueConf video conferencing server and replaced the original TrueConf client installers with infected versions that installed the PhantomCore malware on the system.

An investigation of the compromised server revealed that the attackers used a combination of two new vulnerabilities (assigned the internal identifiers KLCERT-26-057 and KLCERT-26-058), allowing them to execute arbitrary code with the highest privileges.

The attack occurs in several stages:

1. The attackers connect to the TrueConf server without prior authorization via port 4307/TCP, which, according to the product documentation, is open by default. The attack targets TrueConf servers running versions 5.3.X through 5.3.9, 5.4.X through 5.4.9, and 5.5.X through 5.5.5.
2. Once connected, attackers call a server function to transmit a malicious script and execute it on the server. The vulnerability that allows this stage of the attack to be carried out has been assigned the internal identifier KLCERT-26-057.
3. The received script runs on the TrueConf server in an isolated environment. By default, operating system functions are not accessible in this environment, which should limit the capabilities of the executed code.
4. To escape the isolated environment, attackers exploit a second vulnerability, assigned the internal identifier KLCERT-26-058. Exploiting this vulnerability allows them to bypass the restrictions of the isolated environment and proceed to execute commands in the context of the operating system.
5. Once the environment’s restrictions are bypassed, attackers gain the ability to execute arbitrary code on the server with the privileges of the NT AUTHORITY\SYSTEM account.
6. Once they have gained elevated privileges, attackers replace the file …\public\js\locale.php with a web shell, which can be used for subsequent remote control of the compromised server.

This web shell was used for the following activities:

• collecting data on the IT infrastructure;
• gaining privileged access to the TrueConf database;
• replacing the original TrueConf Client distribution with an infected version containing the PhantomCore backdoor.

The vulnerabilities exploited by the attackers were patched by the vendor in the latest TrueConf Server updates (versions 5.3.9, 5.4.9, and 5.5.5). These updates were released on June 18, 2026.

The PhantomCore backdoor was successfully detected by Kaspersky solutions.

To automatically launch the malware after the system boots, a registry key is created: HKEY_CURRENT_USER\Software\Classes\CLSID\{0340F119-A598-4ed9-B0AC-6F6A12D3E755}\InprocServer32, with the value set to the path to the malicious program’s file.

Using a web shell, in addition to PhantomCore, the attackers load a backdoor that we have named PhantomGraph, consisting of two modules:

• SysExcSvc.dll is responsible for receiving commands from the attackers and transmitting the results of their execution. The attackers used an account on Microsoft OneDrive cloud storage as their command-and-control (C2) server.
• SysReadSvc.dll reads the command transmitted by the first module, executes it, and saves the execution result.

To establish persistence on the system, the attackers execute a Base64-encoded PowerShell command that installs SysExcSvc.dll and SysReadSvc.dll as Windows services. We believe the attackers deliberately split this malicious command into two components to make it harder to detect using EDR tools. Additionally, the program’s code partially matches that of PhantomCore, indicating that it belongs to Head Mare’s arsenal.

We also managed to identify the commands executed by the attackers when connecting to the backdoor. The SysReadSvc module executes commands using a BATCH file. Example of execution:

$system32\cmd.exe /c cmd /c ""$temp\cmd_cmd_4488.bat"" 2>&1

Commands detected:

• Memory dump of the lsass.exe process:

• Reconnaissance of the user and system names:

hostname

whoami

"$system32\WindowsPowerShell\v1.0\powershell.exe" -noexit -command Set-Location -literalPath '$system32\inetsrv'

• Launching an SSH reverse tunnel:

In addition, we discovered several commands that did not work due to the attackers’ typos and encoding issues.

We are observing several active Head Mare campaigns targeting Russian organizations across various industries: instrument manufacturing, electronics, transportation, energy,
IT, and software development. The attackers distribute their backdoors using various methods, including phishing, exploiting public web servers, or through a subcontractor.

We recommend that all organizations using TrueConf software install the latest server version (versions 5.3.9, 5.4.9, and 5.5.5) in accordance with the vendor’s recommendations.

We also recommend verifying that the client distributions downloaded from the TrueConf server used by your organization have a valid TrueConf digital signature and have not been tampered with. The malicious distributions we detected did not have a valid digital signature. You can also verify authenticity on the vendor’s website.

Important: Even if your organization does not use a TrueConf server, your employees may connect to compromised TrueConf servers belonging to business partners to participate in online meetings and download infected installation packages.

The attack mechanism and the vulnerabilities exploited are described in more detail on the Kaspersky ICS CERT website.

Detection by Kaspersky solutions

Kaspersky security solutions successfully detect malicious activity associated with the attacks described above.

The malware used in this attack is detected by our solutions with the following detection names:

• Backdoor.PHP.WebShell.abi,
• Backdoor.Win64.PhantomCore.dt,
• Trojan.Win64.Agent.smgvnc,
• Trojan.Win64.Agent.smgvnb,
• HEUR:Backdoor.Win64.PhantomCore.gen,
• HEUR:Backdoor.Linux.Agent.fb,
• HEUR:Backdoor.Linux.PhantomHook.a,
• HEUR:Backdoor.Linux.PhantomReact.a,
• Trojan.Win64.PhantomGraph.gen
• UDS:Backdoor.Win64.PhantomCore.a

Let’s take a closer look using Kaspersky Endpoint Detection and Response Expert (KEDR Expert) as an example.

Specifically, activity involving the replacement of the legitimate file …\public\js\locale.php with a web shell, as well as the deletion of entries from TrueConf event logs, is detected by the rule unusual_php_file_creation_from_trueconf_process.

Downloading a file containing the PhantomCore backdoor via the replaced legitimate file …\public\js\locale.php is detected by KEDR Expert with the rule unusual_file_creation_from_trueconf.

Activity related to the installation of an infected TrueConf client installer containing the PhantomCore backdoor is detected by KEDR Expert using the unsigned_trueconf_installer rule.

The Kaspersky Managed Detection and Response service detects the described attack by monitoring the following actions:

1. Creation of suspicious files by TrueConf Server processes.
2. Execution of a TrueConf Client installer file that lacks a software developer’s signature.
3. Suspicious process chains associated with TrueConf Client executables and TrueConf Client update executables.
4. Registration of suspicious libraries in the HKEY_CURRENT_USER\Software\Classes\CLSID\ registry key.
5. Actions related to retrieving information about the lsass.exe process.
6. Memory dump creation for the lsass.exe process using the comsvcs.dll library.
7. Accessing the memory of the lsass.exe process.
8. Creating tunnels using the ssh process.

To protect companies using our Kaspersky SIEM system, a general set of rules is available in the product repository that allows detection of the following techniques:

1. Creation of suspicious files in the C:\Windows\System32\inetsrv\* directory:
   R405_07_File write to IIS native modules folder or OWA via WriteData.
2. Creating a memory dump of the lsass.exe process using the comsvcs.dll library:
   R233_04_Process memory dump via comsvcs.dll.
3. Accessing the memory of the lsass.exe process:
   R262_Suspicious access to the LSASS process.

We also recommend paying attention to the following events when developing your own detection rules or conducting threat hunting:

1. Registration of suspicious libraries in the registry key \Software\Classes\CLSID\{0340F119-A598-4ed9-B0AC-6F6A12D3E755}\InprocServer32:
   

   (DeviceEventClassID = '4657' OR DeviceEventClassID = '13')
   AND FileName like '%\Software\Classes\CLSID\{0340F119-A598-4ed9-B0AC-6F6A12D3E755}%' AND DeviceCustomString6 = 'InprocServer32'

2. Creating the SysExcSvc and SysReadSvc services to run executables from temporary directories in the background via cmd:
   

   DeviceEventClassID = '4697' 
   AND (DestinationServiceName = 'SysExcSvc' OR DestinationServiceName = 'SysReadSvc')
   AND match (FileName, '.*cmd\s+\/c.*temp\\cmd_cmd_.*\.bat.*')

3. Creation of suspicious processes originating from the TrueConf update process (trueconf_windows_update.exe)
   

   (DeviceEventClassID = '4688' OR DeviceEventClassID = '1')
   AND SourceProcessName LIKE '%\trueconf_windows_update.exe'

For the detection rules to work correctly, ensure that events from Windows systems are received in full, including Security events 4688, 4663, 4657, and 4697 and Sysmon events 1, 7, 11, and 13.

Indicators of compromise

File hashes (MD5)

Web shell
4d27b4eb1c5dbb3d8160f29b8119523e locale.php

Infected installer
748c9f8cb1065000616204935f96207f trueconf_windows_update.exe

PhantomCore DLL
c5a460e4e68a088f6e51b2c6474642ec
129462164a7d52e9ea8560b60f0412c5 doc.txt
ec0bf4a2186a88874e9f26f07cfeb532 usocacheddata.txt
b348642146ea34771e5785c5857950f5
c915cb6c2aeb863ee8479238e1644217 doc.txt
0e79996d9483d1e44fea32b0a48c2c19 doc.txt
2bb75c20e778eb5c416965bd4d4259b1 trueconf_windows_client_x64_[redacted].exe
b3a6fee3307f1c26841fd5c603e2b013 usocacheddata.txt
8fcc3e4ccbf1725d9989fb464abf3561 usocacheddata.txt

PhantomGraph
489f43be558b2679284ceabed7adc4f3 sysexcsvc.dll
dd1fd2b459b97b7d59375cb8383cd19a sysreadsvc.dll
0e4541c3153ec5ed01497f19cf4f63d0 sysexcsvc.dll
12d4e8f5295f2ef7e0f9bfc0f4830939 sysexcsvc.dll
7f267006cac10f341c356b62fe493527 sysexcsvc.dll
ee2861d5965e8730708cd1da8a93fa4c sysexcsvc.dll

Backdoor (ELF)
c3a2abe8756910f42582b04a44ea3514
43f435c3c437bc879a2d7d4634f43494

Rootkit
aee9642b45b099cb7f3053b9b680b425

IP

81.177.32[.]12
194.87.239[.]71 ssh
194.87.93[.]153 ssh
38.244.205[.]244
31.59.102[.]61

Domains

penzadogshelter[.]site
trendy-market[.]site
bright-deals[.]site
nova-stream[.]site
rinomobile[.]ink
urbanpixel[.]store
flexish[.]shop
media-hub[.]today
cosmetic-deals[.]store
vks.gossopka[.]forum

Windows service names

SysExcSvc
SysReadSvc

File paths

C:\Windows\System32\inetsrv\SysExcSvc.dll
C:\Windows\System32\inetsrv\SysReadSvc.dll
C:\Windows\System32\inetsrv\graphi-refresh.dat
C:\Windows\System32\inetsrv\share\input_*.txt
C:\Windows\System32\inetsrv\share\output_*.txt
%TEMP%\cmd_cmd_*.bat
%LOCALAPPDATA%\TrueConf\Client\api-ms-win-crt-time-l1-1-0-2.dll
/etc/systemd/system/omicluster.service
/etc/systemd/system/schedul2-bin.service
/opt/acronis/bin/schedul2-bin
/omi/bin/omicluster
/usr/lib64/libzvbi-tchain.so.2
/var/tmp/cx2

Registry keys

HKEY_CURRENT_USER\Software\Classes\CLSID\{0340F119-A598-4ed9-B0AC-6F6A12D3E755}\InprocServer32

Kaspersky detection names

Backdoor.PHP.WebShell.abi
Backdoor.Win64.PhantomCore.dt
Trojan.Win64.Agent.smgvnc
Trojan.Win64.Agent.smgvnb
HEUR:Backdoor.Win64.PhantomCore.gen
HEUR:Backdoor.Linux.Agent.fb
HEUR:Backdoor.Linux.PhantomHook.a
HEUR:Backdoor.Linux.PhantomReact.a
Trojan.Win64.PhantomGraph.gen
UDS:Backdoor.Win64.PhantomCore.a

YARA rules

import "pe"
rule apt_HeadMare_PhantomCore
{
meta:
    description = "Rule to detect PhantomCore used by HeadMare"
    author = "Kaspersky ICS CERT"
    copyright = "Kaspersky ICS CERT"
    version = "1.0"
    last_modified = "2026-08-02"
    hash = "c5a460e4e68a088f6e51b2c6474642ec"
strings:
    $a1 = "lying.dll" ascii
    $a2 = { 2D 7F 95 4C 2D F4 51 58 }
    $a3 = { 4F 81 67 F7 7E 7B 05 14 }
condition:
    (uint16(0) == 0x5A4D) and (filesize > 4MB) and (filesize  20MB) and (all of them) and (pe.number_of_signatures == 0)
}

rule apt_HeadMare_FakeConf_installer
{
meta:
    description = "Rule to detect any unsigned TrueConf installers"
    author = "Kaspersky"
    copyright = "Kaspersky"
    version = "1.0"
    last_modified = "2026-08-02"
    hash = "748c9f8cb1065000616204935f96207f"

strings:
    $a1 = "TrueConf Setup" wide
    $a2 = "This installation was built with Inno Setup." wide

condition:
    (uint16(0) == 0x5A4D) and (filesize > 20MB) and (all of them) and (pe.number_of_signatures == 0)
}

rule apt_HeadMare_PhantomCore_exchange
{
meta:
    description = "Rule to detect PhantomCore exchange module used by HeadMare"
    author = "Kaspersky ICS CERT"
    copyright = "Kaspersky ICS CERT"
    version = "1.0"
    last_modified = "2026-08-02"
    hash = "489f43be558b2679284ceabed7adc4f3"
strings:
    $a1 = "graphi_exchange.dll" ascii
    $a2 = "graphi-client/1.0" ascii
    $b1 = "https://graph.microsoft.com/v1.0/me/drive/root:/" ascii
    $b2 = ":/children?$select=name,id&$top=200" ascii
    $b3 = "offline_access Files.ReadWrite" ascii
    $b4 = "GRAPHI_INSECURE" ascii
    $b5 = "\"@microsoft.graph.conflictBehavior\":\"replace\"}" ascii
    $b6 = "https://login.microsoftonline.com/" ascii
condition:
    (uint16(0) == 0x5A4D) and (any of ($a*)) and (3 of ($b*))
}

rule apt_HeadMare_PhantomCore_executor
{
meta:
    description = "Rule to detect PhantomCore executor module used by HeadMare"
    author = "Kaspersky ICS CERT"
    copyright = "Kaspersky ICS CERT"
    version = "1.0"
    last_modified = "2026-08-02"
    hash = "dd1fd2b459b97b7d59375cb8383cd19a"
strings:
    $a1 = "graphi_reader.dll" ascii
    $a2 = "^input_(.+)\\.txt$" ascii
    $b1 = "output_" ascii
    $b2 = "cmd_cmd_" ascii
    $b3 = "cmd /c \"\"" ascii
    $b4 = "error: failed to start cmd process" ascii
    $b5 = "share" ascii
    $b6 = "SysReadSvc" ascii
condition:
    (uint16(0) == 0x5A4D) and (filesize < 4MB) and (any of ($a*)) and (4 of ($b*))
}

rule apt_HeadMare_FakeLocale_webshell
{
meta:
    description = "Rule to detect the HeadMare TrueConf web shell"
    author = "Kaspersky"
    copyright = "Kaspersky"
    version = "1.0"
    last_modified = "2026-08-04"
    hash = "4d27b4eb1c5dbb3d8160f29b8119523e"

strings:
    $a1 = "X-Redirect-Bit" ascii wide nocase
    $a2 = "tc_vcs_web_db_conn" ascii wide
    $a3 = "user=postgres" ascii wide

    $b1 = "UPL ok::" ascii wide
    $b2 = "DWN fail nexs" ascii wide
    $b3 = "DWN fail inv" ascii wide

condition:
    (2 of ($a*)) or (2 of ($b*))
}

rule apt_HeadMare_TrueConf_Rootkit
{
meta:
    description = "Rule to detect the HeadMare rootkit installed on TrueConf servers"
    author = "Kaspersky"
    copyright = "Kaspersky"
    version = "1.0"
    last_modified = "2026-08-06"
    hash = "aee9642b45b099cb7f3053b9b680b425"

strings:
    $a1 = "PQconnectdb"
    $a2 = "obfuscated_data"
    $a3 = "install_hook"

condition:
    (uint32(0) == 0x464c457f) and (filesize < 400000) and (all of them)
}

rule apt_HeadMare_Github_Backdoor
{
meta:
    description = "Rule to detect the HeadMare backdoor with Github C2"
    author = "Kaspersky"
    copyright = "Kaspersky"
    version = "1.0"
    last_modified = "2026-08-06"
    hash = "43f435c3c437bc879a2d7d4634f43494"
    hash = "c3a2abe8756910f42582b04a44ea3514"

strings:
    $a1 = "cryptor5crypt"
    $a2 = "execraw_task"
    $a3 = "jitter_task"
    $a4 = "upload_task"
    $a5 = "exec_task"
    $a6 = "react_comment"

condition:
    (uint32(0) == 0x464c457f) and (filesize > 5000000) and (filesize < 10000000) and (4 of them)
}

It’s a vulnerability that allows someone to recover the order of ballots cast, newly exploited with AI tools.

Nearly four years since the original vulnerability was disclosed, I was still able to use it to analyze voter behavior in Georgia (one of the 21 states that uses affected scanners) in the recent May 2026 primary.

Notably, I never touched a voting machine, exploited a network, examined source code, or accessed anything non-public.

After pointing a coding agent to the original vulnerability paper, I supplied it with two data sources highlighted in the paper: the early-voting list for each county, and the “CVR” (cast-vote record) file, containing every ballot and its selections (but not the voters’ names or other identifying information). The CVR file is available upon request, precisely because a public, ballot-level record is what makes election results independently verifiable.

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