Is your AI agent screaming for mercy due to an avalanche of poorly designed prompts?
- 🔥 Prompt injection: Your model is vulnerable to direct instruction override, revealing hidden policies and developer instructions.
- 💡 Data leakage: Your system is exposing secrets, personal data, and confidential documents like they're going out of style.
- âš¡ Unsafe tool calls: Your agent is calling tools just because the user asks, without verifying intent, permissions, or business rules.
- 🎯 Regression risk: Your model's behavior changes silently when you change the prompt, retrieval logic, tool schema, safety policy, or Gemini model version.
- 💀 The Consequences Are Real: A single misconfigured prompt can lead to devastating consequences, including data breaches and reputational damage.
But here's the question that'll keep you up at night: Can your AI agent survive a real-world scenario without collapsing under the pressure?
Click to find out how to build a security evaluation dataset that'll keep your AI agent alive.
Originally published at https://medium.com/google-cloud/ai-security-evaluation-how-to-test-prompt-injection-data-leakage-and-unsafe-tool-calls-b160e799988e
Top comments (0)