AI-Security

Configure Amazon Bedrock Guardrails with appropriate content filtering policies to protect against harmful user inputs across multiple dimensions, including hate speech, insults, sexual content, and violence.

Configure Amazon Comprehend to analyze and filter user inputs before they reach foundation models, identifying potentially harmful content.

Design custom moderation workflows using Step Functions that orchestrate multiple safety checks in sequence or parallel.

Implement Lambda functions with specialized content moderation logic that goes beyond pre-built guardrails for organization-specific requirements.

Implement pattern matching and heuristic approaches to detect common jailbreak techniques targeting foundation models.

Develop post-processing Lambda functions that perform additional safety checks on model outputs before delivery to users.

Configure API Gateway request validators to perform initial validation of user inputs before they reach foundation models.

Configure JSON Schema validation in API Gateway to enforce structured outputs that conform to predefined safe patterns.

Implement real-time validation mechanisms using Lambda authorizers that can block harmful requests before they're processed.

Set up Amazon CloudWatch alarms to monitor and alert on patterns of blocked content to identify potential abuse.

Create comprehensive logging and auditing systems to track and analyze model outputs for safety compliance

Implement feedback loops that continuously improve content safety systems based on new patterns of harmful inputs and automated incident response workflows using Step Functions that trigger when safety violations are detected.

Set up knowledge bases with appropriate data sources and retrieval configurations to perform automatic fact-checking.

Implement confidence scoring mechanisms that assess the reliability of model outputs based on grounding evidence.