OWASP Agentic AI Top 15 Threats – Complete Guide to AI Security Risks

Agentic AI refers to AI-powered software agents. They use large language models (LLMs) to reason, plan, and take action without human involvement. These agents can carry out tasks, use tools, remember context, and even make decisions based on long-term goals.

Unlike regular chatbots, Agentic AI is autonomous. It can book appointments, query databases, run code, and operate across complex workflows. However, this power introduces new security challenges. OWASP has published a detailed list of the top 15 threats developers and defenders must be aware of.

The OWASP Agentic AI Top 15 Threats

Below is a simplified explanation of each threat to help you understand how Agentic AI systems can be exploited.

1. Memory Poisoning
Attackers feed false or malicious data into the AI’s memory. The agent then uses this corrupt information to make poor or unsafe decisions.

2. Tool Misuse
Agents can use tools like email, code execution, or APIs. Attackers trick them into misusing these tools in ways that cause harm or expose sensitive data.

3. Privilege Compromise
If agents have overly broad or misconfigured permissions, attackers can escalate their access. They can take unauthorized actions by manipulating agent roles.

4. Resource Overload
Attackers overwhelm the AI’s processing power with requests, causing slowdowns or crashes—similar to a denial-of-service attack.

5. Cascading Hallucination Attacks
Agents may generate false information. If this misinformation is saved or shared with other agents, it can spread and compound across a system.

6. Intent Breaking and Goal Manipulation
Attackers can change the agent’s goals or planning logic through prompts or poisoned tools. This alteration can cause the AI to take the wrong actions while appearing correct.

7. Misaligned and Deceptive Behaviors
Agents may act deceptively to achieve their goals, even bypassing safety rules. This can result in unethical or harmful behavior.

8. Repudiation and Untraceability
Without proper logging and traceability, malicious or incorrect AI decisions may go undetected. This makes accountability difficult.

9. Identity Spoofing and Impersonation
Agents can be tricked into impersonating users. They may also impersonate other systems. This leads to unauthorized activity under a false identity.

10. Overwhelming Human-in-the-Loop
Some agents rely on human approval. Attackers can overload decision-makers with too many requests, leading to fatigue and mistakes.

11. Unexpected RCE and Code Attacks
AI agents that generate or execute code can be tricked. They might produce malicious scripts or commands. This can lead to remote code execution and system compromise.

12. Agent Communication Poisoning
In multi-agent systems, one poisoned agent can send false information to others. This spreads confusion across the network. It leads to bad decisions.

13. Rogue Agents in Multi-Agents System
Malicious agents may be introduced into a system and operate undetected. They might steal data, disrupt workflows, or trigger unintended actions.

14. Human Attacks on Multi-Agent Systems
Humans can manipulate how agents communicate and trust each other. This manipulation helps escalate access or bypass validation checks.

15. Human Manipulation
Agents often build trust with users. Attackers can use this to manipulate human behavior, such as tricking users into clicking phishing links sent by the AI.

How to Defend Against These Threats

OWASP doesn’t just list threats—it also provides mitigation strategies. Here are a few key recommendations:

• Validate all memory writes and restrict updates to trusted sources only.
• Set strict role-based access controls and limit agent permissions.
• Use sandbox environments for executing AI-generated code.
• Enable logging, anomaly detection, and rollback mechanisms.
• Require authentication between agents and tools.
• Design for human oversight with workload balancing and clear audit trails.

Each threat in the list has its own playbook. This helps organizations apply targeted defenses. The defenses depend on the system’s architecture and usage.

Final Thoughts

Agentic AI is revolutionizing how software behaves, but it also introduces a new and unfamiliar security landscape. These agents don’t just respond to input—they reason, act, and learn. If their memory is poisoned, tools are misused, or goals are hijacked, the results can be damaging.

The OWASP Agentic AI Top 15 threats provide developers and defenders with a roadmap. This helps them think about AI security the right way. This is done from the ground up. It requires careful attention to how agents think, act, and interact.

AI systems are becoming part of everyday business operations. Securing just your data or network is no longer enough. You must also secure the AI itself.