OWASP Agentic AI Threat T5: How One AI Lie Can Corrupt Everything
Explore OWASP Agentic AI Threat T5: Cascading Hallucination Attacks. Learn how false AI outputs spread and how to stop hallucinated data from poisoning your systems.
All About Testing
OWASP Agentic AI Threat T4: Resource Overload – How Attackers Drain AI Systems
Resource Overload is a critical OWASP Agentic AI threat where attackers intentionally overload an AI agent’s compute, memory, or bandwidth resources—causing degraded performance or system crashes. This blog explains how the threat works, real-world examples, and defenses you can implement.
OWASP Agentic AI Threat T3: Privilege Compromise – When AI Permissions Go Wrong
Privilege Compromise is a top threat in OWASP’s Agentic AI list. It occurs when attackers exploit weak access controls or over-permissive AI agents to gain unauthorized actions or data access. Here’s how privilege compromise works, real-world examples, and how to defend against it.
OWASP Agentic AI Threat T2: Tool Misuse Explained with Examples
Understand OWASP Agentic AI Threat T2: Tool Misuse. Learn how attackers manipulate AI tools, real-world misuse cases, and strategies to prevent these AI security risks.
OWASP Agentic AI Threat T1: Memory Poisoning – How Attackers Corrupt AI’s Memory
Memory Poisoning is one of the most dangerous risks in OWASP’s Agentic AI Top 15. Attackers can inject false or malicious data into an AI’s memory, leading to harmful and persistent decisions. This blog explains memory poisoning with simple examples and effective defenses.
OWASP Agentic AI Top 15 Threats – Complete Guide to AI Security Risks
Agentic AI systems are becoming smarter and more powerful—but they’re also introducing a new wave of security threats. OWASP has identified 15 critical risks that developers and security teams need to understand to protect these AI-driven systems. Here’s a beginner-friendly breakdown of each threat and why it matters.
OWASP LLM10:2025 – Unbounded Consumption: When AI Overloads Systems
Unbounded consumption happens when LLMs overload systems with endless generation, calls, or recursion. OWASP LLM10:2025 urges developers to apply throttling, budgets, and execution limits to prevent runaway behavior.
OWASP LLM09:2025 – Misinformation: When AI Spreads Falsehoods with Confidence
LLMs can confidently generate false information—misleading users and damaging trust. OWASP LLM09:2025 highlights why AI misinformation is dangerous and how developers can reduce hallucinations and bias.
