Configuring security groups for DeepSeek-R1 models on AWS involves several best practices to ensure secure and efficient deployment. Here are some detailed guidelines:
1. Create Separate Security Groups**
Create a separate security group for each set of resources with different connectivity requirements. For example, if you're deploying DeepSeek-R1 models using Amazon SageMaker, create a distinct security group for the SageMaker endpoints and another for any associated databases or services like RDS[2][4].2. Restrict Inbound and Outbound Traffic**
Ensure that your security groups restrict inbound and outbound traffic to only what is necessary for your application. Avoid allowing all inbound access to some or all ports, as this can make your network vulnerable to malicious attacks[4]. For instance, if your DeepSeek-R1 model only needs to communicate with a specific database, restrict the inbound rules to allow traffic only from that database's security group.3. Avoid Using Default Security Groups**
Default security groups often have open inbound and outbound traffic, which can pose a significant security risk. Instead, create custom security groups with specific rules tailored to your application's needs[4][8].4. Use IAM Roles for Access Control**
Implement IAM roles to manage who can access and invoke the DeepSeek-R1 model. This ensures fine-grained access control and helps prevent unauthorized access to sensitive resources[5][7].5. Deploy within a Private VPC**
Deploy your DeepSeek-R1 models within a private Virtual Private Cloud (VPC) to enhance security. This setup allows you to control network access more effectively and reduce exposure to the public internet[1][7].6. Implement Guardrails for Safety and Compliance**
Use tools like Amazon Bedrock Guardrails to implement safety and compliance measures. These guardrails help prevent prompt attacks, filter harmful content, and ensure that your AI applications adhere to industry regulations[3].7. Monitor and Log Network Traffic**
Enable VPC flow logs to monitor network traffic between your resources. This helps in detecting any unauthorized access attempts and aids in compliance auditing[4].8. Regularly Review and Update Security Groups**
Regularly review your security groups to ensure they remain aligned with your application's evolving needs. Remove any unused security groups and update rules as necessary to maintain optimal security[4].By following these best practices, you can securely deploy DeepSeek-R1 models on AWS while maintaining robust security controls and compliance with industry standards.
Citations:
[1] https://aws.amazon.com/blogs/machine-learning/optimize-hosting-deepseek-r1-distilled-models-with-hugging-face-tgi-on-amazon-sagemaker-ai/
[2] https://repost.aws/questions/QUBp50iDPqSju0TINNsO8-fw/best-practice-security-group-architecture
[3] https://aws.amazon.com/blogs/machine-learning/protect-your-deepseek-model-deployments-with-amazon-bedrock-guardrails/
[4] https://www.jit.io/blog/best-practices-for-aws-security-groups
[5] https://crossasyst.com/blog/deepseek-r1-on-aws-bedrock/
[6] https://www.youtube.com/watch?v=MlvdpDJn59E
[7] https://aws.amazon.com/blogs/machine-learning/deploy-deepseek-r1-distilled-models-on-amazon-sagemaker-using-a-large-model-inference-container/
[8] https://renovacloud.com/en/26-aws-security-best-practices-to-adopt-in-production-part-2/