New taxonomy reveals how prompt attacks compromise GenAI systems
DownloadOrganizations adopting generative AI face growing security challenges as adversarial prompt attacks expose vulnerabilities in language models. Evaluations show attack success rates over 50%, with some techniques reaching 88% effectiveness across models.
This white paper offers a taxonomy to understand and defend against prompt-based threats, covering:
• Three attack vectors: guardrail bypass, information leakage, and goal hijacking
• Techniques like prompt engineering, social engineering, and obfuscation
• Real-world scenarios showing how adversaries exploit AI systems
Learn strategies to detect and prevent these threats. Read the full white paper for securing your AI applications.
Download this White Paper


