AI agent security: risks and protection

5 AI Agent Risks

1. Prompt injection — attacker manipulates behavior through input data
2. Data leaks — LLM may reveal confidential information from prompts
3. Hallucinations — agent generates plausible but false information
4. Unauthorized actions — agent acts beyond permissions
5. Provider dependency — OpenAI/Anthropic API may be unavailable

How AppStar Protects

• Sandboxing — agent has minimum necessary permissions
• Human-in-the-loop — critical actions (payments, deletion) require confirmation
• Input validation — prompt injection filtering
• Audit trail — complete logging of all agent actions
• Fallback — switching to backup LLM on failures
• Local LLMs — for personal data (Llama, Mistral)

AppStar Security

Specialized AI system pentesting: testing for prompt injection, data leaks, attack resilience.