By launching social engineering attacks at scale and automating exploit discovery at machine speed, AI has compressed the time to shore up defenses.
Malware also gets an AI boost today, able to morph in real time and deflect standard security controls. While these are serious security concerns, there’s yet another issue companies must prepare to mitigate: Overprivileged AI tools that may wreak havoc.
A disaster waiting to happen
Here’s a fairly typical scenario: An impatient employee asks for approval to use an AI tool. The request gets overlooked, but does not deter him. He opens a free public AI chatbot account and in a step that will later haunt the organization, links it to the shared corporate cloud drive for convenience. He then instructs the AI to “organize” his files.
The AI tool has broad access to the entire corporate repository, including read, write, and delete. The AI not only “organizes” the user’s files, but also reorganizes files across the entire network. It moves and deletes files it thinks are duplicates. Ongoing projects it assumes are completed become archived. It restructures shared team folders based on its own logic. In short, it perpetuates chaos: the company spends days and weeks recovering, reversing changes, and restoring directory structures.
This didn't happen out of malice, but because an employee wanted to do his job better.
Why do these incidents happen?
Our minds have been conditioned to think software will do what it’s told, following a set of hard-coded rules. But AI agents are different. They interpret our defined objectives and then decide how to fulfill them by any means possible, charting their own course based on information they can access. Agents can also respond differently every time the context changes. This flexibility makes them useful, but flexibility combined with too much open access can cause disruption.
Problems may not materialize if the AI gets restricted permission, such as limited to only reading files. The real problem occurs when the agent gets wide latitude to write, send, or delete files without first determining whether the agent needs such broad permission. For example, SQL database admin tools that can only read data are not a problem, but an AI agent with broad access can autonomously alter data, move files, trigger workflows, and send communications. Any damage are directly proportional to what the agents can touch.
Excessive permissioning and knee-jerk deployment without governance can result in a sprawling AI ecosystem where nobody has a clue about which tools are running, what data users (or attackers) can access, or where that data goes afterward.
What security leaders need to know
- Permissions can weaken AI resilience: External threat actors present risk, but even riskier are the wide access permissions routinely granted AI tools. Almost all employees (96%) do not fully use their granted access, but AI agents are different. When an AI inherits the same standing permissions given to a worker, it can operate continuously at machine speed, testing the access it’s been allowed.
- Prompt training alone doesn’t cut it: While security awareness training around safe AI use makes sense, training that covers proper prompt writing isn’t the fix to look for. Teach employees to phrase requests in a manner that doesn’t overshare information. But this won’t fix such a systemic issue. Better to implement behavioral tracking to check for unusual patterns in AI behavior, along with stronger identity and access management.
- Closely monitor AI agents: A traditional IT review asks whether a piece of software functions properly. But such reviews are not enough for autonomous agents. A good AI governance framework must continuously ask what a particular agent can access and what it’s doing with that access right now. Security teams must shift from periodic compliance checks to continuous, runtime monitoring of active agent behavior. This starts with using AI discovery tools to identify exactly which AI tools are in use across the organization, from LLMs and agentic features built into everyday apps, to fully autonomous agents. From there, least-privilege access controls and data loss prevention can help lock them down.
An IBM survey found that 77% of organizations admit AI adoption has outpaced their governance capabilities. AI deployment now moves faster than defensive strategies can keep up and this pace will only increase. Organizations that best navigate AI will restrict agent permissions to only what's necessary, making least-privilege access a core tenet of their cybersecurity framework.
Michelle Drolet, founder and CEO, Towerwall
