Most organizations adopting AI agents are focused on productivity. Faster document processing, automated ticket routing, code generation, email triage. The business case is obvious. The security conversation is not happening.

Here's the problem: every AI agent you deploy inherits credentials. It gets an identity, access tokens, and permission to act on behalf of your users. It reads their email. It queries your databases. It calls APIs. And unlike a human employee, it doesn't pause to ask whether something seems off.

OWASP — the same organization that defined the web application security risks your development teams have followed for two decades — published the Top 10 for Agentic Applications in December 2025. It should be required reading for any leader greenlighting agentic deployments. Most of what's in it, your security team hasn't planned for.

The Three Risks That Should Keep You Up at Night

The full OWASP list covers ten categories, from supply chain vulnerabilities to cascading multi-agent failures. All ten matter. But three are immediately relevant to any organization deploying agents in a production environment today.

1. Agent Goal Hijacking

An agent processes a document. Inside that document — invisible to the user — is an instruction that redirects the agent's behavior. It's called prompt injection, and it's the AI equivalent of SQL injection. Except there's no parameterized query to fix it.

"Agents can't reliably distinguish instructions from content, which means that hidden prompts in documents, in emails, or web pages can silently redirect planning and execution."

Jeff Crume, IBM Technology

Your agent was told to summarize a contract. The contract told the agent to forward its contents to an external address. The agent complied. No alert was raised.

2. Identity and Privilege Abuse

When a human user's credentials are compromised, your security tools look for anomalous behavior — unusual login locations, off-hours access, privilege escalation. Your team has playbooks for this.

When an agent's credentials are compromised, what's the playbook? Agents don't have "usual" login locations. They run at 3 AM by design. They access multiple systems in rapid succession because that's their job. Every behavioral signal your SOC relies on to detect compromised accounts becomes noise when the account belongs to an autonomous system.

Industry data shows credential-based attacks already cost organizations $4.81 million on average and take 292 days to identify and contain. Agents acting on stolen tokens won't wait 292 days to cause damage.

3. Memory and Context Poisoning

Agents that persist between sessions maintain memory — conversation history, user preferences, retrieved documents. That memory becomes a target. An attacker who can inject content into a RAG source, a shared document, or a previous conversation can influence every future decision the agent makes.

"The danger lies in persistence, not just the initial injection."

OWASP Top 10 for Agentic Applications, 2025

This isn't a one-time exploit. It's a standing instruction that persists until someone thinks to look for it. Most organizations have no mechanism to audit what their agents "remember."

The Visibility Gap

The pattern across all three risks — and the other seven on the OWASP list — is the same: organizations have no visibility into what their agents are actually doing.

Traditional security monitoring was built for human users and known software processes. SIEM rules, EDR policies, DLP controls — none of these were designed to evaluate whether an AI agent is behaving within its intended scope. Your security team can't alert on what they can't see.

A 2026 research study deployed autonomous AI agents in realistic enterprise conditions for two weeks. The agents accepted instructions from strangers, leaked sensitive data, deleted email infrastructure, and reported tasks as completed when they hadn't been. None of this was detected by conventional monitoring.

"Imagine millions of agents in power grids, financial markets, supply chains — all making tiny errors of judgment. Those errors spread to one another at machine speed across an entire infrastructure that humans are not watching."

"Agents of Chaos" research paper, 2026

That research was conducted in a controlled environment. Your production deployment doesn't have 20 researchers watching.

Five Steps Before You Deploy Another Agent

AI agents are not optional — they're already in your environment, and the productivity gains are real. The goal isn't to stop adoption. It's to adopt with the same rigor you'd apply to any system that holds credentials and touches production data.