OpenClaw, which was previously known as Clawdbot and Moltbot, is today one of the most successful and fast‑growing ecosystems for AI agents, recognized worldwide. The project quickly became popular with users because of its flexibility and ability to solve fairly complex tasks that previously required a lot of time for automation and execution. A dedicated marketplace appeared quickly after the project started gaining traction, where developers and users began publishing tools for working with it. Currently, employees all over the world use OpenClaw to automate their tasks, often unaware of risks this practice introduces to them and their employers.

In this article we will examine several security aspects of OpenClaw, look at how attackers can target this system, which vulnerabilities are already known, and how to protect against all of the listed issues.

OpenClaw skills

The project’s success was ensured by the fact that the agent accepts natural language instructions, does not require knowledge of programming languages, and allows the use of skills, which expand its capabilities. The overall architecture of OpenClaw can be seen below:

As shown in the scheme, the system is designed to be used along with agent skills. These skills can reside locally on a system where the agent is installed or can be obtained from external sources. At the time of writing this article, a dedicated hub named ClawHub is used for sharing skills among users.

One of the key features of OpenClaw skills is that they are easy to create and do not require coding. A skill is in essence a set of commands written in natural language, although it can contain code. Currently, there is a general description of the skill format: it is usually a text file named SKILL.md, although more complex variants can exist. The primary requirement for these files is that they use plain‑text formats. To illustrate what this looks like, here is a fragment of a skill:

The application areas for the OpenClaw skills are quite broad and can include everyday tasks such as checking email, performing routine operations and calculations on a computer, as well as more complex pipelines that handle testing, research, or software development. For most actions, the agent requires access to the operating system’s file system, as well as to the tokens and keys of the systems it will interact with. All necessary data are usually provided by users either through environment variables or in plain‑text files located alongside the agent.

Since many skills enable automation of work processes, employees worldwide actively use them. This fact, combined with the widespread adoption of the system and the overall popularity of artificial‑intelligence technologies, has attracted attackers to the project.

OpenClaw vulnerabilities

In less than two years, around 530 vulnerabilities have been discovered both in OpenClaw itself and in the underlying technologies. That said, the publication of OpenClaw vulnerabilities in the CVE database began only in February 2026. Below is a breakdown of these vulnerabilities by severity.

As shown in the chart, the number of high-severity vulnerabilities is quite large. Most of these vulnerabilities fundamentally involve issues with storing sensitive data and operating with excessively high privileges. Each of them can be exploited to hijack the agent or inject commands that it will execute.

Malicious skills

Besides exploiting vulnerabilities and deceiving users, there are more specific attack vectors against OpenClaw, namely, the skills.

Research logically draws a parallel between supply‑chain attacks and the distribution of malicious skills. However, unlike usual supply-chain attacks, creating malicious skills is trivial because there is no longer a need to develop custom malware.Despite this, until February 7, 2026, no skills underwent even a basic security check, which allowed malicious skills to appear immediately. Our scan of the skill hub in April, identified 24 accounts that were distributing more than 600 malicious skills. Overall, open‑source intelligence indicates that over 1,100 malicious accounts have been created since January.

Following the investigations and a lengthy effort to clean the skill repository of malicious entries, it was announced that files would undergo preliminary scanning with VirusTotal (VT) and NVIDIA’s SkillSpector. On the one hand, this is a more responsible approach to publishing skills; on the other, because OpenClaw is primarily an agent that executes a set of instructions, detecting malicious activity moves to a different level. Now it is necessary not only to analyze a file for dangerous commands that should be blocked, but also to examine all possible malicious behaviors that could be triggered by a harmful instruction within a skill. An example of a malicious command in natural language:

An example of a malicious command using a part of a bash command:

The example in the image and similar malicious skills are detected by Kaspersky products as HEUR:Trojan.ANSI.MalClaw.gen.

In addition, Kaspersky products monitor malicious OpenClaw skill activity on the system. Below are detection statistics from our systems that identified malicious OpenClaw client behavior. The data for June cover the first half of the month.

As shown in the chart, even despite the measures taken to counter the publication of malicious skills, attacks continue. Therefore, it is important to employ layered protection that isolates the OpenClaw agent from critical data and infrastructure systems. We also recommend checking all skills that enter the organization’s perimeter. For this purpose, Kaspersky Scan Engine is suitable. This solution is designed to protect web applications, proxy servers, network attached storage and mail gateways. It can be integrated into almost any application, is easy to deploy and manage.

Additionally, monitor network accesses used by the agent. For this purpose, the project already provides a sandboxing subsystem and various wrappers for working with APIs and services. Last but not least, develop a comprehensive AI policy and make sure your employees never use third-party tools that are not explicitly allowed to use.