I was shocked by how much system access OpenClaw requires. Not because the technology is impressive – it is – but because many users do not fully realise what they are granting when they connect an AI agent to their system. Tools like OpenClaw are designed to increase efficiency. They can read files, execute tasks, interact with applications, and in some cases control large parts of a computer environment. This level of access is often necessary for automation to work properly. However, it also creates a new kind of risk: control is slowly shifted away from humans, sometimes without clear oversight.
For private users, this may feel uncomfortable. For companies, it is a serious governance issue. When an AI agent operates in the background, decisions about permissions, monitoring, and responsibility become critical. The question is no longer whether the technology works, but who remains accountable when something goes wrong. This article looks at where the real cybersecurity risks begin when AI agents gain deep system access – and why organisations should take a closer look before trusting automation blindly.
1. What kind of access do AI agents really need?
To work effectively, AI agents usually need more than simple user permissions. Tools like OpenClaw are designed to interact deeply with a system. This often includes access to files, folders, applications, and background processes. In some setups, the agent can also execute commands, manage workflows, or connect different tools automatically.
From a technical perspective, this level of access makes sense. Automation only works if the system can “see” what is happening and act without constant human input. Reading documents, moving files, or controlling applications are common requirements. Without these permissions, the AI agent would be slow, limited, or unreliable.
The problem starts when this access becomes too broad or poorly defined. Many users grant permissions once during setup and rarely look at them again. Over time, the AI agent may gain access to more data and functions than originally intended. This does not happen because of malicious intent, but because convenience often comes first.
What makes this situation difficult is that most of these processes run silently in the background. There are no warning messages, no visible alerts, and often no clear overview of what the AI agent can currently access. The system still works as expected, which creates a false sense of safety. In other words, the risk does not come from the technology itself, but from the gap between what the AI agent is allowed to do and what users actively monitor. This gap is where control slowly begins to fade.
2. Where control starts to fade
Control does not disappear all at once. It fades slowly and often without anyone noticing. This usually happens after the initial setup, when an AI agent is already working reliably and delivering results. Because everything seems to function well, there is little reason to look closer. AI agents like OpenClaw often run in the background. Tasks are executed automatically, files are accessed silently, and processes continue without human interaction. Over time, users stop actively thinking about what the agent is doing and which permissions it still has. The focus shifts to output, not oversight.
Another issue is visibility. Many systems do not provide a clear, simple overview of current access rights and ongoing actions. Logs may exist, but they are rarely checked. Alerts are often missing or too technical to be useful for non-experts. As a result, control is technically present, but practically absent.
This creates an illusion of safety. Because no problems are visible, users assume there are no problems. Automation becomes trusted by default, not because it is well monitored, but because it is quiet. The AI agent does exactly what it was designed to do — just without continuous human supervision. At this point, control has not been lost in a dramatic way. It has been delegated and then forgotten. This is where real cybersecurity risks begin, not through active misuse, but through passive neglect.
3. Why this is a bigger problem for companies
For companies, the loss of control caused by AI agents is far more serious than for private users. When an AI agent operates inside a business environment, it does not only access personal files, but also internal data, customer information, credentials, and business-critical systems.
In many organisations, access rights are linked to roles, responsibilities, and compliance rules. When an AI agent receives broad system permissions, these structures can be bypassed without intention. The agent does not understand business context, legal obligations, or regulatory boundaries. It only follows technical instructions.
This creates a governance problem. If an AI agent publishes content, installs software, accesses cloud services, or interacts with password managers, the question of responsibility becomes unclear. Who is accountable if something goes wrong? The employee who installed the tool, the management who approved it, or the vendor who developed it?
Another risk is visibility. Companies often assume that security tools, antivirus software, or access policies will automatically prevent misuse. However, if an AI agent is granted access to these systems themselves, traditional protection layers lose their effectiveness. Security controls exist, but they are no longer independent.
From a business perspective, this affects more than IT security. It touches compliance, data protection, reputation, and trust. A single uncontrolled system can expose sensitive information, disrupt workflows, or create legal consequences. The damage is rarely immediate, but it can be long-lasting.
This is why AI agents are not just a technical topic for companies. They are a leadership issue. Decisions about system access, automation, and oversight must be made consciously. Without clear boundaries and responsibility, efficiency gains can quickly turn into serious business risks.
According to the German technology magazine c’t Magazin, OpenClaw creates a significant security risk due to the level of system access it requires.
4. Common misconceptions about AI control
One of the biggest problems with AI agents is not the technology itself, but the assumptions people make about it. Many risks start with ideas that sound reasonable at first, but do not hold up in practice. A common belief is: “The tool comes from a trusted source, so it must be safe.” In reality, trust in a vendor does not replace technical control. Even well-intentioned tools like OpenClaw can create risks when they require broad system access. Trust without verification is not a security strategy.
Another misconception is: “It only automates small tasks.” AI agents often start with simple actions, but their capabilities grow quickly. Over time, they may gain access to more systems, more data, and more functions than originally planned. What begins as assistance can turn into independent operation.
Some users also believe: “We can always turn it off if something goes wrong.” This underestimates how deeply an AI agent can be integrated into a system. If it has access to cloud accounts, password managers, or core services, stopping it is not always simple. The effects may already have spread across multiple platforms.
Finally, there is the assumption: “Security tools will protect us anyway.”
This is dangerous. If an AI agent has access to security software or administrative privileges, traditional protection layers may no longer work as intended. Security tools are effective only when they remain independent and monitored.
These misconceptions create a false sense of control. The technology feels manageable, familiar, and helpful, while the real risks remain hidden. Understanding these assumptions is a key step toward using AI agents responsibly and securely.
You can see similar patterns in other areas of AI-driven software. AI-powered browsers, for example, often require deep access to user data, browsing behaviour, and cloud services. The risks are not always obvious at first glance. A closer look at this topic can be found here: The Hidden Dangers of AI Browsers – What You Should Know
According to other leading AI experts, Openclaw can be a cybersecurity and privacy nightmare
5. What organisations should think about before using AI agents
Before introducing an AI agent into a company environment, organisations should slow down and ask a few fundamental questions. This is not about blocking innovation, but about understanding responsibility and risk. The first question is scope. What exactly does the AI agent need to access in order to do its job? Many tools request full system access by default, even if only a small part is actually required. Companies should clearly define boundaries and avoid giving broad permissions “just in case”.
The second point is oversight. Automation does not mean absence of control. Companies should know how actions are logged, who can review them, and how unusual behaviour is detected. If an AI agent works silently in the background, regular visibility becomes essential. Another important aspect is ownership. Someone must be responsible for the AI agent. Not “IT in general”, but a clearly defined role. This includes decisions about installation, updates, permissions, and shutdown procedures. Without ownership, accountability disappears.
Companies should also think about separation. Core systems, password managers, cloud services, and security tools should not all be accessible through a single automated agent. When too much is connected, a single failure can affect the entire organisation. Finally, there is the human factor. Employees need to understand what the AI agent does and what it should not do. AI should support decision-making, not replace it. Clear rules about approval, publishing, and system changes help prevent unwanted actions.
Using AI agents responsibly means treating them as powerful tools, not digital employees with unlimited trust. The goal is not maximum automation, but controlled automation — with humans remaining in charge.
The risks discussed here do not exist in isolation. As AI tools gain deeper access to systems, they also expand the attack surface for malicious actors. This is already visible in how cybercriminals actively use artificial intelligence to target businesses. A deeper look at this development can be found here:
How Hackers Use Artificial Intelligence Against Businesses — and How You Can Protect Yours
Conclusion: OpenClaw access as a cybersecurity risk
The debate over OpenClaw highlights a major challenge that goes far beyond one specific tool. When an AI agent needs deep access to a system, cybersecurity risks stop being theoretical—they become a daily reality. The real problem isn’t the technology itself, but the lack of control.
Granting AI access to operating systems, cloud services, and password managers creates a dangerous situation. It becomes difficult to monitor what is happening, and it is often unclear who is responsible if something goes wrong. Even if there is no bad intention, this level of access can create hidden security gaps.
For businesses, adopting AI should be seen as a security and governance decision, not just a way to work faster. Before using powerful AI agents, companies must ask two questions:
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Which permissions are actually necessary?
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Who is held accountable for the AI’s actions?
OpenClaw reminds us that convenience should never be more important than control. As AI tools become more advanced every year, being cautious is not a weakness—it is a smart strategic advantage.
