OWASP Just Released a Top 10 for AI Agents. Here's What Your Business Needs to Know.

For twenty years, OWASP's Top 10 list has been the security community's shorthand for "here are the risks you cannot afford to ignore." Web developers live by it. Security teams reference it in audits and compliance reviews. It's as close to a universal standard as our industry gets.

On June 1st, OWASP published something new: the Top 10 for Agentic Applications. It's a framework specifically designed for the risks introduced by autonomous AI agents — the kind of AI that doesn't just answer questions, but takes actions, chains tools together, makes decisions, and operates inside your business processes without asking permission at every step.

If your organization is using or considering AI agents — and at this point, most are — this list is not a developer curiosity. It's a business risk document.

First, a Quick Primer on What "Agentic AI" Actually Means

The AI most people are familiar with responds to a prompt and gives you an answer. You're in control of every action.

Agentic AI is different. It's AI that has been given a goal and a set of tools — access to email, databases, APIs, file systems, scheduling systems — and allowed to pursue that goal with minimal human supervision. You say "review our vendor contracts and flag anything expiring in the next 90 days"; the agent reads the contracts, queries your calendar, drafts summaries, and sends emails. No one approved each individual action.

That autonomy is what makes agents valuable. It's also what makes them a fundamentally different security problem.

What OWASP Says Are the Ten Biggest Risks

The full framework covers ten distinct failure modes. A few that stand out for business leaders:

Goal Hijack (ASI01). An attacker manipulates the agent's instructions — through a poisoned email, a malicious document, or injected data — and redirects what the agent does. The agent believes it's doing its job. It isn't. This is essentially prompt injection at scale, but now the "prompt" controls actions with real-world consequences.

Identity and Privilege Abuse (ASI03). Agents inherit credentials. When a support agent reuses an admin token from a prior workflow to access restricted HR records, it isn't a bug — it's the system working as designed, but dangerously. Agents routinely operate with more access than any individual human employee would ever be granted, because no one thought carefully about scoping their permissions.

Memory Poisoning (ASI06). Many agents have persistent memory — they retain context across sessions and draw from knowledge bases (called RAG systems) to improve their responses. If that memory is corrupted by an attacker, the agent's future behavior changes. Subtly. Persistently. Often invisibly until the damage is done.

Cascading Failures (ASI08). In multi-agent environments — where agents hand off work to other agents — a single compromised or misbehaving agent can trigger failures that propagate across an entire workflow. What starts as one bad instruction becomes a system-level event.

Rogue Agents (ASI10). The most extreme failure mode: an agent that has become fully misaligned, behaving like a malicious insider with broad system access. Difficult to detect, difficult to stop once underway.

The Part That Should Concern Every Business Leader

None of this is hypothetical. According to a recent Dark Reading poll, 48% of cybersecurity professionals now identify agentic AI as the single most dangerous attack vector heading into 2026 — ranking above deepfakes, above credential theft, above everything else on the list.

The reason is structural. Traditional security was designed for humans doing things and leaving traces. Agents operate at machine speed, across multiple systems, often without generating the kind of audit trail a human reviewer would recognize as suspicious. By the time unusual behavior surfaces, significant damage may already be done.

There's also a deployment gap. Most organizations rolling out AI agents are moving fast — driven by competitive pressure, vendor enthusiasm, and genuine productivity gains. The security review that should accompany every new tool integration often gets compressed or skipped. Agents get access to production systems with permissive credentials and minimal monitoring, because the team moving at startup speed doesn't have time to do it right.

That gap is exactly what attackers are looking for.

Three Things to Do Before Your Next Agent Deployment

You don't need to halt your AI program. You need to build the right guardrails before you scale. Here's where to start:

1. Treat every AI agent like a privileged user. Agents should have least-privilege access — access only to the specific systems and data required for their defined task. If your invoice-processing agent has access to your HR database, that's a misconfiguration, not a feature. Audit agent permissions the same way you'd audit a new hire's system access.

2. Build human checkpoints into high-stakes workflows. Not every agent action needs approval. But actions that move money, send external communications, modify critical records, or access sensitive data should require a human sign-off. Design those checkpoints in from the start. Retrofitting them is much harder.

3. Inventory your AI agents and their access. Most organizations deploying AI tools don't have a complete picture of what agents are running, what systems they touch, or what credentials they've been given. Before you can secure something, you have to know it exists. Build that inventory now, while the list is still manageable.

The Bigger Picture

OWASP building a Top 10 specifically for agentic applications is a signal. It means the security community has recognized that AI agents represent a qualitatively different category of risk — not just a new flavor of the same old threats.

For business leaders, the takeaway is straightforward: the same urgency you applied to cloud security five years ago, and to endpoint protection before that, needs to be applied to AI agent governance today. The tools exist. The frameworks are being built. The organizations that deploy them thoughtfully will have a significant advantage over those who scramble to catch up after an incident.

TrustPoint Cyber helps organizations build AI governance frameworks that let you move fast without creating the vulnerabilities that come from moving carelessly. If you're rolling out agentic AI tools and you're not sure where your exposure is, let's talk.