Who Is Auditing the AI? A Practical Guide to AI Governance, ISO 42001, and Agentic AI Security
Discover why AI auditing is becoming critical, how ISO 42001 is changing AI governance, and what organizations must do to secure Agentic AI systems
Tagged: Prompt Injection
How to Use Garak to Test Prompt Injection Vulnerabilities in LLM Applications
Prompt Injection is one of the most critical security risks in modern AI systems. This blog explains how Garak, an open-source AI vulnerability scanning framework, can be used to test LLM applications against Prompt Injection attacks, jailbreaks, prompt leakage, and adversarial manipulation through practical AI red teaming techniques.
Why AI Security Testing is Different From Traditional Security Testing
AI systems introduce risks that traditional security testing cannot fully address. Unlike conventional software, AI models can be manipulated through prompts, leak sensitive data, generate unsafe outputs, or behave unpredictably. This blog explains why AI security testing requires specialized approaches covering applications, models, infrastructure, data, and overall AI trustworthiness.
OWASP LLM08:2025 – Vector and Embedding Weaknesses: The Hidden AI Backdoors
Vector and embedding weaknesses in LLMs create dangerous backdoors that hide inside AI’s internal understanding of language. Learn how OWASP LLM08:2025 exposes this hidden risk—and what to do about it.
OWASP LLM07:2025 – System Prompt Leakage and How It Exposes the Brain of Your AI
OWASP LLM07:2025 highlights a growing AI vulnerability—system prompt leakage. Learn how attackers extract internal instructions from chatbots and how to stop it before it leads to deeper exploits.
OWASP LLM Top 10: The Biggest Security Risks in AI You Can’t Ignore
The OWASP Top 10 for LLM Applications 2025 outlines the most critical security threats facing AI tools. From prompt injection to plugin abuse, learn how to secure your chatbot, agent, or LLM integration today.
Your AI Plugin Might Be a Backdoor: The Hidden Risk of LLM Integrations
As LLMs connect to tools and APIs, insecure plugin design becomes a critical threat. Learn how careless integrations can turn your AI assistant into a backdoor—and how to stop it.
When AI Talks Too Much: Preventing Data Leaks from LLMs
LLMs can leak sensitive data with just the right prompt. Learn how output handling flaws expose private info—and how to stop your chatbot from oversharing by accident.
