AI applications introduce unique security challenges that traditional application security doesn't address. Prompt injection, data poisoning, and model manipulation require new defensive strategies.
Top AI Security Threats
Prompt Injection
Attackers craft inputs that override the model's instructions, potentially extracting sensitive data or causing harmful outputs.
Data Poisoning
Manipulating training data to introduce biases or backdoors into models.
Model Inversion
Reverse-engineering model outputs to extract training data, potentially exposing sensitive information.
Defense Strategies
Input validation and sanitization — Filter and validate all user inputs before they reach the model
Output filtering — Scan model outputs for sensitive data, harmful content, and policy violations
Rate limiting — Prevent abuse through request throttling
Audit logging — Log all model interactions for security review
Red team testing — Regularly test your AI systems with adversarial inputs
Security should be built into your AI applications from day one. Contact Iedeo for a security review of your AI systems.