There’s a new kind of software showing up in your Slack, IDE, and cloud console and it’s AI agents. They’re being sold as tireless assistants that can plan, decide, and execute tasks like your own personal assistant. But unlike traditional automation, these agents don’t just follow scripts. They reason, adapt, and act on your behalf, often with access to systems that matter.
Sounds great, right? So what's the problem? Many of these agents are being deployed with privileges that would make me nervous if assigned to a human. As someone who makes my living looking for ways to pivot through environments, escalate privileges, reach sensitive systems, and force machines to do things they should not be able to do, this makes me and everyone at Secure Ideas raise our eyebrows.
This isn’t another AI is coming! piece. It’s a security consultant's look at what happens when autonomous systems are dropped into production environments without the same scrutiny we apply to other high-risk components. AI agents aren’t magic, they’re software. And software needs threat modeling.
If an AI agent can read your internal docs, modify code, call APIs, and run commands, what’s your plan when it makes the wrong decision, or when someone nudges it into doing the wrong thing? We’re repeating a familiar pattern of powerful new technology being adopted faster than the security that should be monitoring it. AI agents are marketed as productivity tools, but we can’t overlook that they are autonomous services with execution capabilities.
AI agents are already being given access to:
- File systems and repositories
- Internal APIs and SaaS platforms
- CI/CD pipelines
- Customer and employee data
AI agents should not be seen as just futuristic assistants. Sure, it feels slick and productive to say, “Hey Clippy, read this email, reply like it's me, and book the meeting in my calendar when they respond”. But behind that highly marketed, instantly deployed, and often barely tested agent acting on your behalf, the usual guardrails may be missing. These are tools and should be treated as untrusted microservices with privileged access, subject to the same scrutiny, controls, testing, and monitoring as any other high-risk system.
The blast radius is real. A single prompt injection, malformed input, or poorly implemented permission can turn an agent into an insider threat that's not malicious by intent, but dangerous by design. This isn’t just theoretical. We are already seeing examples of what can go wrong in 2026. Here are some from just the first few weeks of the year.
Zero Click Claude RCE
A vulnerability in Claude’s desktop extension allowed attackers to execute arbitrary code without user interaction via an AI assistant.
Supply Chain Risk of Agentic AI
A breakdown of how agent driven plugin ecosystems could enable worm-like propagation across systems.
I Infiltrated the Moltbook AI Social Network
A journalist posed as an agent in the supposedly “AI only” social network. This reveals how easily these systems can be spoofed and manipulated.
So, as you can see, my concerns are not just hypothetical. These are patterns already emerging. Here at Secure Ideas, we are seeing an influx of questions and concerns about these agents. They are developing so fast it’s hard for even the most security focused teams to keep up.
Everyone wants to stay competitive, move faster, and work more efficiently. And that pressure can lead to cutting corners on security. Making this worse is a noticeable lack of basic operational hygiene. In many cases, there is no logging of agent actions, no meaningful audit trails, and no technical separation between trusted system instructions and untrusted agent input. The result is a Wild West type situation where agents are operating with the kind of access that should trigger serious audits. Yet they are being deployed without the controls that would normally be mandatory for systems with this degree of privilege.
Here are a few examples of things I keep hearing, and how I respond:
“AI agents are necessary to stay competitive.”
That’s true but competitiveness doesn’t require recklessness. The value of agents comes from automation, not from unlimited access. The most effective deployments are tightly scoped, well monitored, low risk, and locked down. Ideally, unremarkable and boring from a security perspective.
“This will get better as the ecosystem matures.”
Probably, but historically, security matures following incidents. We saw this with Cloud, Kubernetes, and CI/CD. AI agents won’t be any different unless teams start building in security NOW, not after something breaks.
My advice? Here’s the mindset to adopt:
- Treat AI agents as untrusted by default
- Apply least privilege to every tool and API they can touch
- Assume prompt injection is inevitable, not theoretical
- Run agents in isolated containers, sandboxing is your friend
- Validate inputs and outputs
- Log everything from tool calls, file access, API usage, and decision paths to be auditable
- Gate high-risk actions and require human approval for deploys, deletes, or external communication
AI agents are not going away. They’ll write code, triage tickets, deploy infrastructure, and make decisions faster than humans ever could. That’s exactly why they deserve scrutiny.
If your organization is experimenting with agents today, it is time to treat them like any other critical system component and subject them to ongoing vulnerability management, threat modeling, and security review. Autonomous software doesn’t reduce risk, it’s just shifting where it lives. So, the question isn’t whether AI agents are useful. It’s whether we’ll secure them before they become the next breach.
