Introduction

AI agents and associated tooling are becoming increasingly common in corporate infrastructure. Agents can perform a range of actions with the user’s privileges, such as accessing data, running commands, and interacting with external services. This creates new security risks, especially when these tools are used without the security team’s oversight or well-designed policies.

Detecting, tracking, and controlling AI agents is becoming one of the most pressing tasks for security teams today. We closely follow technological developments and continuously update our solutions to respond to new threats in a timely manner amid a rapidly changing technology landscape. This post describes new expertise built into Kaspersky products that helps counter the threats posed by the proliferation of AI agents. We approach this problem from several angles.

First, you need to thoroughly understand the threat you are dealing with. To this end, we added profiles to the Kaspersky Threat Intelligence Portal that describe various AI agents and how attackers exploit them. At their core, AI agents are programs (processes) that run in the operating system on endpoints and can also launch other processes. This means that Endpoint Detection and Response solutions are among the key endpoint controls for this threat. These solutions detect the presence and launch of AI agents, track their activity, and identify potentially dangerous behavior. When needed, they also take action, such as stopping a suspicious process, blocking the activity, or isolating the host, to reduce the likelihood of an incident escalating. For this purpose, we developed specially adapted detection rules.

You can use Kaspersky Endpoint Security, now also available as Kaspersky Next, to control and restrict the launch of AI agents. This solution uses two components to detect AI agents and control how they are used. Application Control categorizes the application processes launched on endpoints, and Web Control manages access to specific categories of web resources for users on endpoints.

Finally, even harmless AI agents can contain malicious instructions (skills), such as those downloaded from unsafe external sources. Kaspersky Scan Engine analyzes installed applications to detect these threats and also checks LLM files for malicious code. Let’s take a closer look at these solutions and technologies.

Popular AI applications and services in organizations

Tools from Anthropic and OpenAI take the top spots in the September 2026 ranking of AI agents by popularity among Kaspersky users. This list is based on telemetry from Kaspersky solutions. It shows the number of users who had the relevant AI vendors’ products installed at the time of the study.

The data shows that agentic systems, especially AI agents for software development, are the most popular AI applications. The TOP 10 also includes an application for running large language models locally (LM Studio) and a voice note-taking app (Wispr Flow).

According to open sources, these are the most widely used AI services in 2026:

While analyzing the most popular and widely used apps, our experts also noticed a sharp rise in vulnerable versions of AI-related software and services. From 2025 to date, more than 2500 vulnerabilities have been published:

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

* Data for previous quarters was updated and may differ slightly from previously published data.

Application Control and Web Control

To enforce the organization’s security policy for AI agents and other AI applications on the corporate network, Kaspersky products offer application control based on KL categories. These categories classify installed software and give you granular control over which approved applications can run in the organization.

Application Control analyzes the processes launched on endpoints, tracking which AI agents are running in corporate systems at any given moment, on which hosts, and under which accounts. Application Control also shows how long a given program has been in use.

This makes it easier for the Kaspersky Security Center (KSC) administrator to control applications. Administrators can use KL categories to allow or block AI agents inside the company for specific groups of employees.

Here is what this functionality looks like to KSC administrators:

KL categories available when configuring Application Control

For details on how to configure Application Control in KSC, follow this link.

In Kaspersky Endpoint Security (KES), Application Control can operate in two modes:

• Denylist. In this mode, Application Control lets users run any applications except those blocked by Application Control rules. This is the default mode.
• Allowlist. In this mode, Application Control blocks users from running any applications except those explicitly allowed by Application Control rules.

Below are the steps to configure Application Control to block AI tools.

Configuring Application Control for the AI Tools category in KES

With this setup, when a user tries to launch an AI agent, they get a notification and the agent doesn’t start.

KES notification about an attempt to launch an AI agent

For more on how to configure Application Control in KES, follow this link. Our public portal also lets you explore information on KL categories and the applications that fall under them, in particular details on how AI agents are categorized and how popular they are.

AI Tools KL category

The View applications drop-down list shows products for a specific vendor.

Similarly, Web Control lets you manage user access to web resources. If a user tries to open a denylisted website, KES blocks access and shows a warning.

KES notification about an attempt to access a prohibited web resource

When configuring access, the administrator can block websites that provide AI as a service.

Website categories

For more on configuring Web Control, follow this link. The help portal also provides information on website categories that can be assigned to resources to configure access control.

Kaspersky Endpoint Detection and Response

To an EDR solution, an AI agent is a regular process. It has its own executable, a tree of child processes, and network communications, all of which need to be monitored for suspicious activity. An attacker can use an AI agent as an automation tool. An AI agent installed as a legitimate user tool can also be leveraged in a ClickFix attack, where it executes a malicious instruction received from an untrusted source, such as a document, web page, or email. That said, unsafe actions by an agent do not always indicate an attack. There may be no malicious intent in the chain at all. An incident can result from what looks like an ordinary instruction from a user who doesn’t fully understand the consequences of having it executed. The mere fact that an agent was launched does not reveal whether it is being used in an attack. That is why Kaspersky EDR (KEDR) uses both conventional behavioral rules and rules written and adapted to detect AI tools. The latter identify risky agent actions and settings, and help determine which AI tool was involved in suspicious activity.

Conventional KEDR rules detect the vast majority of familiar malicious techniques, including when performed by an AI agent. A suspicious PowerShell launch, persistence via Task Scheduler, or an attempt to steal credentials leaves clear, identifiable traces. These traces look the same no matter what initiated the actions. The rules analyze launch parameters, process relationships, affected files, network activity, and other telemetry events.

For example, in a recent Armored Likho campaign, we found signs that AI had been used to create loader and dropper samples, which were later compiled with NSIS (Nullsoft Scriptable Install System). The key telltale artifacts were icons in the scripts and excessive comments on every function, which is uncharacteristic of human-written code. In addition, the group continues to generate new modules for its BusySnake Stealer and BusySnake RAT samples. For example, the attackers used AI to develop a module that runs multiple checks for virtual environment artifacts and calculates a score. Depending on the score, the sample either runs or exits with code 0. Even though the initial access samples, payloads, and their modules were AI-generated, the commands they execute via rundll32 and PowerShell are detected by the shell_creation_by_rundll32 and suspicious_powershell_cmd_or_script_spawning rules.

So, for detecting an attack like this, it is not important who wrote the loader, the payload, or its modules: they are given away by the commands they execute, process relationships, and other traces of activity in the system. AI can be involved both in preparing the code and in carrying out the attack directly on the device.

In the latter case, the attacker uses the agent to carry out their tasks and lets it choose and run the required commands within the privileges it has. For effective protection, it is critical to link suspicious actions back to the AI tool and the conditions under which it operates. In KEDR, several specialized rules handle this task.

We have created separate rules for popular AI agents, ai_agent_*_access_to_sensitive_file_**, where * is the tool name and ** is the operating system. They generate alerts when an agent accesses files that contain credentials, tokens, or keys.

ai_agent_opencode_access_to_sensitive_file_win Tap to previewTap to hide

The ai_agent_dangerous_execution_mode rule detects agents launched with auto-approval of all actions (so-called YOLO mode) or with the sandbox disabled. These settings do not indicate an attack on their own, but they let the agent perform dangerous actions without user confirmation.

ai_agent_dangerous_execution_mode Tap to previewTap to hide

The suspicious_mcp_server_artifact rule triggers when MCP server scripts are created or modified in hidden, temporary, or cache directories. Attackers can place an MCP server in these locations to quietly connect it to the agent: through the MCP server, they can pass instructions to the agent, call third-party tools, and access the user’s data.

suspicious_mcp_server_artifact Tap to previewTap to hide

The llm_api_access_by_unusual_apps rule generates an alert when an application on Windows, Linux, or macOS connects to the API of a known external LLM service, unless this activity falls under predefined exclusions. This helps spot model access by applications that do not normally behave this way.

llm_api_access_by_unusual_apps Tap to previewTap to hide

Some Kaspersky EDR rules tag events for investigation but do not generate alerts. For example, the ai_agent_**_execution rules flag launches of known agents on Windows, Linux, and macOS. The local_ai_model_artifact rule records the creation or modification of AI model files in typical application, runtime, and cache directories. These events reveal AI tools on the device, including tools that run on local models and never call an external API.

local_ai_model_artifact Tap to previewTap to hide

Kaspersky Threat Intelligence Portal

AI agent profiles

The Kaspersky Threat Intelligence Portal offers a large number of software profiles, including profiles of AI agents. You can sort them by the ai_ prefix:

AI agent profiles on Kaspersky TIP

The profile of an AI agent such as Claude Desktop includes a detailed description of the software, the privilege level required to run it, supported platforms, and threat actor groups known to use it. It also lists tactics and techniques mapped to the MITRE ATT&CK framework, with descriptions of the procedures the tool can be used for.

Claude profile on Kaspersky TIP

The description also lists ways to detect the software through standard system auditing mechanisms:

• Windows: events from standard audit logs and Sysmon events
• Linux: syscall audit events and Sysmon events
• Network auditing: a set of protocols and the traffic generated by the software

The detection section lists the main artifacts the software leaves in the system: command lines, possible launch parameters, names of the services and scheduled tasks it creates, and the key network artifacts.

Detection section in the Claude profile

Hunt Hub

In December 2025, the Kaspersky Threat Intelligence Portal added Hunt Hub (HH), a repository of detection rules. This is a unique Kaspersky project, and we developed it in response to growing market demand.

This functionality is available in the Threat Landscape section of the portal. It gives analysts access to detection rules: their descriptions and their mapping to MITRE ATT&CK tactics and techniques, as well as to the associated cybercriminal groups.

In the Hunt Hub section, customers can explore the detection logic of EDR, NDR, and NGFW products, including the logic for detecting AI agents.

Rules in the Hunt Hub repository

The rule card provides:

• Detailed description
• Rule’s severity level, confidence level, and alert format
• Detection tips
• Description of possible false positives
• Platforms the rule can run on
• Tactics, techniques, and sub-techniques covered by the rule
• Groups that use the technique covered by the rule
• Detection logic that shows what exactly triggers the rule

Detection rule card in Hunt Hub

Kaspersky Scan Engine

Skills are a key component of the AI agent ecosystem. They’re prewritten sets of natural-language instructions that extend agent functionality. We previously covered the risks that malicious skills pose to agent users. A skill can require the usage of additional programs and services, come with helper scripts (for example, written in Python), or contain a malicious command embedded right in the instruction text. This means that adding skills to an originally harmless AI agent opens up several new ways for malicious code to enter the system. To prevent this, any skills obtained from external sources must be scanned. Kaspersky Scan Engine is well suited for this task. This is a cyberthreat detection and response solution that seamlessly integrates with various applications. It can detect malicious code in agent skills, associated scripts, and in files generated by running agents.

Detection of a malicious agent skill in Kaspersky Scan Engine

Detection of an LLM with malicious code in Kaspersky Scan Engine

Conclusion

AI agents are rapidly making their way into corporate environments: they help employees work faster and take on a wide range of tasks, but they also open up new opportunities for attackers. To take advantage of this technology without compromising security, organizations need to build multi-layered protection and minimize risks. A range of Kaspersky solutions can help with this:

• Kaspersky TIP keeps you up to date on current scenarios in which attackers use AI agents, and its Hunt Hub section provides rules for detecting suspicious AI agent activity.
• Kaspersky EDR detects AI agents in the infrastructure and monitors their activity on endpoints. If it detects potentially dangerous actions, the product can log the event, notify the SOC, and take response actions, such as stopping the process or isolating the host.
• Application Control in Kaspersky products can fully restrict the use of AI agents within the company by using application categorization. The Web Control component can restrict access to AIaaS web resources.
• Kaspersky Scan Engine can be integrated into various company processes to detect malicious code in any files, including AI agent skills and LLMs.

When companies combine the tools described above in a comprehensive approach, they can adopt AI agents in an informed way: with an understanding of the associated risks and effective means of minimizing them.

Reddit users found that by using a specific Google search query, it was possible to find Claude conversations that users had shared.

This exposed sensitive material, including crypto wallet keys, names, addresses, work notes, and even erotic or otherwise policy-violating chats. Fortune says Anthropic appears to have fixed the Google indexing issue, but the shared links themselves were still live for people who already had them.

The exposure was tied to Claude’s Share feature, which creates a public web link to a snapshot of a conversation rather than leaving it inside a user’s private account. Reddit users found a search query that surfaced many of these shared chats, plus Claude Artifacts (interactive documents, apps, and other content created by Claude) in Google results. Wired reports that this is still true for Bing.

The main risk is that people use chatbots to think through work, health, legal, or personal matters without realizing that a shared link can behave like ordinary public web content.

This isn’t unique to Claude. We’ve previously seen Grok chats show up in Google search results, and Meta AI conversations can also become public by design. We have also written about the share option in ChatGPT that was swiftly removed after users unintentionally made thousands of conversations searchable.

Anthropic says Claude chats are private by default, and only conversations users explicitly chose to share were affected. But the incident is a reminder that a “share” button on an AI chat can be more like publishing than messaging, especially if search engines can discover the resulting URL.

How to stay safe

The easy way out here is not to share your AI chatbot conversations with anyone, because you could end up reaching more people than you intended.

That’s because it’s harder to stop pages from being indexed than you might expect. And you don’t have those controls aren’t in your hands. The AI provider should take care of that.

But there are a few things you can do:

• Don’t share Personally Identifiable Information (PII) with a chatbot, so that if a conversation is ever exposed it can’t be easily linked back to you.
• To review or stop sharing conversations in Claude, go to Settings > Privacy > Shared chats.
• If you’re using an AI service from a social media company, such as Meta AI, Grok, or Gemini), remember that your conversations could be tied to your account—which might contain a lot of personal information.
• When using AI, make sure you understand how to keep your conversations private. Many services offer temporary or incognito chats that aren’t saved to your history, but they aren’t a guarantee against bugs, leaks, or data breaches. Only use the share feature when you’re comfortable with anyone potentially seeing that conversation.
• Read the privacy policy so you understand how your conversations are stored and shared. If it’s too long, you can always ask an AI to summarise the important points.

Let’s face it, an incognito window can only do so much. 
 
Breaches, dark web trading, credit fraud. Malwarebytes Identity Theft Protection monitors for all of it, alerts you fast, and comes with identity theft insurance. 

Researchers found that cybercriminals are using sponsored search results and shared Claude chats to lure victims into a typical ClickFix attack to install malware on macOS devices.

ClickFix is a social engineering method that tricks users into infecting their own device with malware. Users are instructed to run specific commands that will download malware, usually an infostealer.

The researchers found that when users search for terms like “Claude Mac download,” they may see sponsored Google results that appear to go to the legitimate claude.ai domain.

In reality, the ads resolve to real Claude shared chats, set up to look like official “Claude Code on Mac” or Apple Support guides. Independent research by BleepingComputer found another chat serving the same purpose. The chat instructs victims to open Terminal and paste a base64‑encoded command, which pulls a loader shell script from attacker‑controlled infrastructure and runs it in memory.

The script then profiles the system, pulls down a second-stage payload and runs it through osascript, macOS’s built-in scripting engine. This gives the attacker remote code execution (RCE) without ever dropping a traditional application or binary.

This results in a MacSync‑style payload that harvests browser credentials, cookies, Keychain contents, and crypto wallet data, bundles it, and sends all that information over HTTP to attacker servers.

How to stay safe

Users running macOS Tahoe 26.4 and later will see warnings about possible ClickFix attacks, but other users still have to rely on common sense.

With ClickFix running rampant and inventing new methods all the time, it’s important to stay aware, cautious, and protected.

• Slow down. Don’t rush to follow instructions on a webpage or prompt, especially if it asks you to run commands on your device or copy and paste code. Attackers rely on urgency to bypass your critical thinking, so be cautious of pages urging immediate action. Sophisticated ClickFix pages add countdowns, user counters, or other pressure tactics to make you act quickly.
• Avoid running commands or scripts from untrusted sources. Never run code or commands copied from websites, emails, or messages unless you trust the source and understand what the action does.
• Verify instructions independently. If a website tells you to execute a command or perform a technical action, check through official documentation or contact support before proceeding.
• Limit copy and paste for commands. Manually typing commands instead of copy and paste can reduce the risk of unknowingly running malicious payloads hidden in copied text.
• Secure your devices. Use an up-to-date, real-time anti-malware solution with web protection. Malwarebytes blocks connections to unsafe sites like these.
  
• Educate yourself on evolving attack techniques. Understanding that attacks may come from unexpected places helps maintain vigilance. Keep reading our blog!
• Stay away from sponsored ads in search results. Anyone can buy them and make them look legitimate.

Pro tip: The free Malwarebytes Browser Guard extension warns you when a website tries to copy something to your clipboard.

Stop threats before they can do any harm.

Malwarebytes Browser Guard blocks phishing pages and malicious sites automatically. Free, one click to install. Add it to your browser →

Last week on Malwarebytes Labs:

• 3 easy-to-miss cybersecurity risks for small businesses
• Actively exploited cPanel bug exposes millions of websites to takeover
• More PayPal emails hijacked to deliver tech support scams
• Hackers stole hundreds of thousands of Roblox accounts: Here’s what to do
• Researchers built a chatbot that only knows the world before 1931
• Microsoft won’t patch PhantomRPC: Feature or bug?
• Scam-checking just got a lot easier: Malwarebytes is now in Claude
• Fake CAPTCHA scam turns a quick click into a costly phone bill
• Chinese engineer stole US military and NASA software for years

Stay safe!

“One of the best cybersecurity suites on the planet.” 

According to CNET. Read their review →

Security researcher Alexander Hanff wrote an article titled Anthropic secretly installs spyware when you install Claude Desktop.

Claims like that are bound to create two sides, so we searched for an official rebuttal by Anthropic. But we couldn’t find one. It would surprise me very much if they’d be unaware of the claim, since there’s been some noise about it.

Users on Mastodon, Reddit, and LinkedIn are confirming the researcher’s findings and discussing the subject, so it’s hard to imagine Anthropic missed it.

Let’s look at the claims first.

While looking into another matter, the researcher discovered a Native Messaging host manifest on his Mac that he did not knowingly install. On Chrome and other Chromium-based browsers, extensions can exchange messages with native applications if they register a native messaging host that can communicate with the extension. 

By testing on a clean machine, Hanff discovered that Installing Claude Desktop for macOS drops a Native Messaging host manifest into multiple Chromium profiles (Chrome, Edge, Brave, Arc, Vivaldi, Opera, Chromium), even including for browsers that are not actually installed yet.

The Native Messaging host manifest tells a Chromium‑based browser which local executable to invoke when an extension calls a native host, and those hosts run outside the browser sandbox with current users  permissions. Hanff therefore describes this as a “backdoor.” The manifest pre‑authorizes three Chrome extension IDs, so any extension with those IDs can call the helper via connectNative, giving it access to browser automation features.

Another objection is that Claude makes simple deletion futile since the manifest will be recreated the next time the user launches Claude Desktop.

It’s important here to point out that his article is about Claude Desktop, the Electron-based macOS application with bundle identifier com.anthropic.claudefordesktop, distributed as Claude.app. It is not about Claude Code, Anthropic’s command line developer tool. Claude Code is autonomous (“agentic”), allowing you to hand over a task, and it handles the planning and execution until done. So, for Claude Code, it would absolutely make sense to enable communication with browsers, provided they are present on the target system.

So, we have an application that writes into other apps’ profile/support directories (the browsers’ configuration area) and can act as the user, with capabilities like using the logged‑in browser session, DOM inspection, data extraction, form filling, and session recording. This expands the attack surface of every machine this manifest is dropped on, without asking for consent. 

Anthropic’s own launch blog on “Claude for Chrome,” which discusses Anthropic’s internal red‑team experiments, explicitly mentions prompt injection as a key risk and reports attack success rates of 23.6% (no mitigations) and 11.2% (with mitigations). Hanff cites this to argue that a pre‑positioned bridge is a non‑trivial risk.

How bad is it?

Native Messaging is a standard Chromium mechanism. Nothing here is an unknown or exotic technique per se. Chrome’s own documentation explains that Native Messaging hosts run at user privilege and are invoked by browser extensions through a manifest file. And as the researcher pointed out, the bridge does nothing. But it could potentially be abused.

I don’t think it’s fair to say that Claude Desktop installs spyware, but it does open a system up by expanding the attack surface.

Anthropic already had a separate, documented Native Messaging manifest for Claude Code that users sometimes manually copied into other Chromium browsers; the new behavior is that Claude Desktop now drops a Claude‑Desktop‑related manifest into multiple browser paths automatically.

It requires a combination of extension and host. Only combined with a matching browser extension, this bridge enables the user-like capabilities we listed earlier.

What we don’t know yet

Anthropic hasn’t published a detailed technical privacy spec for the Claude Desktop–browser bridge, so we don’t know exactly what data flows when the Chrome integration is used, beyond the general capabilities described in their documentation (session access, DOM reading, etc.).

The detailed analysis and most replication so far are on macOS. We’re in the dark about behavior on Windows and Linux, and the same is true across different browser install paths. That behavior has also not been comprehensively documented in public write‑ups.

I did reach out to Anthropic asking for a response. If and when we get an official response from Anthropic, I’ll add it here, so stay tuned.

Conclusion

Anthropic likely wanted “Claude in Chrome”‑style capabilities across Chromium‑based browsers, but that doesn’t excuse doing it silently and preinstalling the manifest into profile directories for multiple browsers, including ones that are not yet installed.

There are better ways to implement changes like these, and users should at least be made aware of them so they can weigh the advantages against the potential risks.

Stop threats before they can do any harm.

Malwarebytes Browser Guard blocks phishing pages and malicious sites automatically. Free, one click to install. Add it to your browser →