SUMMARY: AI agents installed by employees inherit the permissions of the person running them, so a single unsanctioned agent can read every file its user can open. That turns shadow AI from an upload problem into an access problem. Finland's Traficom names excessive permissions and excessive autonomy as the core risks in its January 2026 guidance on AI agent cybersecurity. This blog explains how shadow AI agents change the threat model, why user-focused controls cannot contain them and how file-level access control on a default-deny basis, with tools like BestCrypt Data Shelter, enforces the boundary that policy alone cannot.
A year ago, shadow AI typically meant an employee pasting a customer email into a free ChatGPT account. The risk was real but contained. Whatever someone uploaded could end up in a model, but the rest of the organization’s data remained untouched.
AI agents change that picture. An agent installed on an employee’s laptop, or running inside an application they are signed into, inherits their permissions.
That means the agent can reach whatever they can reach, so access control now belongs in the shadow AI conversation.
In this blog, you can find out why AI agents make shadow AI harder to contain, what Traficom recommends for agent permissions and how default-deny access control keeps unapproved tools away from sensitive files.
Why Is Shadow AI Important to Address Now?
Shadow AI is important to address now because AI tools no longer wait for something to be copied and pasted. Instead, they act inside the user’s environment and carry the same permissions. Two shifts brought about this change:
Firstly, free-tier and personal AI tools are now built into everyday work. People draft, summarize and translate in a tab that stays open all day. That category of risk is well understood by now: data sent to these tools may be used for training and, once it is, it cannot be pulled back out.
The newer shift is AI agents and AI-connected applications that run locally or inside a user’s authorized environment. ChatGPT and Claude both ship agents that can take actions directly on the machine; code editors, browsers and productivity suites are doing the same. Most of these run without IT ever approving them, which is what makes them shadow AI agents. They are not malicious by default. But they’re built for automation, which involves launching other apps and opening whatever files a task requires. That breadth of access is not a misconfiguration. Agents cannot do their job without it.
If a developer’s agent has access to the source tree, it has access to all of it. If a sales rep’s assistant can see their inbox, it can see every customer record in there. Copying and pasting may be a weak control, but it still runs through a person. Someone decided which parts of a file to expose, and the responsibility for that decision sat with them. An agent removes that step. The exposure is no longer measured by what one person decides to paste. It’s measured by what an agent is free to read.
| Copy-paste shadow AI | Shadow AI agents | |
| What is exposed | The snippets a person pastes | Every file the user’s account can open |
| Who decides | The employee, one paste at a time | The agent, automatically |
| Human checkpoint | Weak but present | Removed |
| Typical scale | A few documents per day | The whole endpoint, continuously |
| Controls that work | Training, policy, approved tools | All of those, plus file-level access control |
What Does Traficom Say About AI Agent Permissions?
Traficom, the Finnish Transport and Communications Agency, published guidance on the cybersecurity of AI agents in January 2026. Its central point is that the biggest risk often lies in the rights an agent is given to systems, tools and data.
Three points stand out from the report.
- Excessive permissions and excessive autonomy are the core risks
- An agent’s rights and data access should be limited to what is strictly necessary
- The tools an agent is able to call should be restricted from the start
The OWASP reaches the same conclusion from the application side: excessive agency sits in its Top 10 risks for LLM applications, with excessive permissions and excessive autonomy named as root causes.
The principle is least privilege, which is what organizations already apply to people and service accounts. It can be manipulated by a prompt within a document or simply too thorough for its own good. Restricting what it can reach is the most reliable way of mitigating it.
What Does Access Control Change?
Access control moves enforcement from the person to the application. It governs which applications can touch which files and folders on the endpoint. An agent still inherits its user’s permissions, but it cannot use them through an app that has not been approved.
Traditional shadow AI controls focus on the person at the keyboard. Training, policy, business-grade subscriptions and clear lists of what can and cannot be uploaded are all necessary. None of them helps when the AI is operating through the user’s own environment.
If a folder containing customer records is not accessible to Chrome, an AI agent operating inside Chrome cannot pull from it. If only specific approved applications can read a project directory, an automation tool installed by an end user is blocked before it ever sees the contents.
So this changes the focus from what employees send AI to what AI is allowed to reach in the first place.
Does Access Control Replace Policy?
The short answer is no. A user that opens a sensitive file, copies the contents and pastes it into a browser AI tool is still a leak path. The restricting of files along can’t stop that final step. Access control sits alongside admin controls, not in place of them.
The full picture shows two layers working together:
| Policy controls | Technical controls | |
| What they govern | What users are allowed to do | What applications can open |
| Examples | Approved tool lists, training, data handling rules | File and folder access restrictions |
| Where they stop | The moment someone forgets or ignores them | A user who manually copies and pastes content |
Encryption works the same way. A drive can be encrypted, but if the password is written on a sticker next to the screen then the organization is still exposed.
What Are Shadow AI Management Best Practices?
Good shadow AI management combines visibility into what is already running with strict limits on what any AI tool can reach. In practice that means:
- Take an inventory of the AI tools already in use, including agents and AI-connected apps inside browsers and editors
- Approve a small set of business-grade tools with no-training clauses and clear data handling terms
- Classify data by sensitivity and mark the categories that should never leave the endpoint at all. This step depends on knowing where the data actually lives, including hidden working copies, archives and temp locations that rarely show up in manual inventories
- Apply access control at the file and folder level on a default-deny basis, so only named apps can touch sensitive data and everything else is automatically blocked
- Restrict agent permissions to only the tools, files and locations needed for the task
- Require human approval for critical or irreversible actions
- Monitor agent behavior for drift in scope or function
Most of these are not new principles. What’s new is applying them to a class of software that behaves like an over-permissioned employee!
How Can You Block AI Agents from Reading Sensitive Files?
The reliable method is app-level access control on a default-deny basis: every application is blocked from protected folders unless it has been explicitly approved. BestCrypt Data Shelter enforces that model on the endpoint. Only approved applications can reach a protected file. Everything else is blocked at the file-system level, whether it’s a browser, an AI agent or something an employee installed last week.
Blocking AI Tools by Name Doesn’t Hold
If one process is shut out, the AI can route the same request through another process or a second agent. The reverse is the only model that survives. Everything is denied by default and only a short list of trusted applications is allowed through. Anything outside that list, including software that did not exist when the policy was written, is refused without anyone having to anticipate it.
Access control depends on accurate discovery. Before a policy can block AI agents from reading a folder of personnel files, the organization has to know where those files are. BCWipe Search covers that step by scanning endpoints for sensitive and hidden data, so the access-control layer has something concrete to enforce against.
Policy still has to be written, and someone still has to decide what counts as sensitive data and explain the reasoning to staff. What the technical layer adds is enforcement, so the policy holds whether or not anyone is checking.
To learn more about BestCrypt Data Shelter, contact our Data Protection Specialist.
Frequently Asked Questions (FAQs)
Shadow AI agents are AI tools that can act on a computer, installed or enabled by employees without IT approval. Unlike a chatbot that only sees what a person pastes into it, an agent inherits the permissions of the user running it, so it can open files, launch applications and work across the endpoint.
Earlier shadow AI exposed only what an employee chose to paste into a tool, so a human decision sat in front of every leak. An AI agent removes that checkpoint and can read everything its user’s account can open, which turns one person’s productivity tool into organization-wide data exposure. OWASP tracks this as excessive agency, one of its Top 10 risks for LLM applications.
A default-deny policy blocks every application from reading protected files unless it has been explicitly approved. Applied to AI agents, it means new or unknown agents are refused automatically, including tools that did not exist when the policy was written. Blocking specific AI tools by name is weaker, because a request can be routed through another process. BestCrypt Data Shelter applies this model through folder-level protection policies.
No. File-level access control stops applications and AI agents from reading protected data, but it cannot stop a user who opens a file and manually pastes its contents into a browser tool. Organizations need administrative controls such as training and approved tool lists working alongside technical enforcement.
Access control policies protect specific files and folders, so they are only as strong as the organization’s knowledge of where sensitive data is stored. Data discovery tools such as BCWipe Search scan endpoints for sensitive and hidden files, including copies in temporary and backup locations, so access rules have something concrete to protect.
BestCrypt Data Shelter enforces application-level access control on the endpoint. Administrators define which applications are allowed to open protected folders, and everything else, including browsers and AI agents, is blocked at the file-system level on a default-deny basis.