Enhance the Security of DeepSeek Model Deployments Using Protect AI and Amazon Bedrock
By Shashi Raina, Sr. Partner Solutions Architect – AWS
By Qiong Zhang, Partner Solutions Architect – AWS
By Vedant Ari Jain, Principal AI/ML Solutions Architect – Protect AI
By Zoe Hellenmeyer, Head of Tech Alliances – Protect AI
Understanding the Security Challenges of Generative AI
As businesses begin to incorporate generative AI into their operations, new opportunities arise alongside security concerns. Common problems include prompt injection attacks, model poisoning, and data extraction vulnerabilities. Open-source AI models are particularly prone to risks like data leaks and targeted attacks. To harness AI technologies effectively, it’s crucial for organizations to assess these risks and mitigate them proactively.
The Rapid Growth of AI Models
In the year 2023, a remarkable 149 foundation models were introduced, more than double the count from the previous year. Each new model offers unique functionalities in reasoning, generating text, and automating decisions. However, many users adopt these models without fully grasping the security implications. For instance, the launch of DeepSeek-R1, another open-source reasoning model, serves as a wake-up call regarding generative AI security. Despite its impressive capabilities, vulnerabilities such as prompt injection and jailbreaking have been identified, stressing the importance of thorough security assessments prior to use.
Protecting AI Workflows with Amazon Bedrock and Protect AI
Companies often find it challenging to evaluate AI model security, which can lead to delays in innovation and production. Firms face risks like compliance failures and reputational damage when proper security measures are overlooked. Amazon Bedrock is designed to address these issues by offering a fully managed service that provides access to high-performing foundation models through a single API. It gives businesses the tools necessary to create secure, innovative AI applications.
On the other hand, Protect AI functions as a security platform dedicated to AI systems. It assists organizations in identifying, monitoring, and addressing AI-related security risks. Its two main tools integrate effectively into AI workflows: Guardian, which scans and validates machine learning models, and Recon, which performs automated security assessments for generative AI systems. This combination helps ensure security across the AI application lifecycle—right from the initial model selection to deployment.
How Guardian and Recon Enhance Security in AI Models
With Protect AI’s Guardian tool, users can validate open-source DeepSeek models before implementing them through Amazon Bedrock. By employing Recon, organizations can automate red-teaming efforts, which guides the configuration of essential security measures when building generative AI applications.
Using Guardian to Scan for Vulnerabilities
It’s vital to confirm the safety of the DeepSeek model you’re using. Guardian serves as a model scanning tool that assesses the integrity and security of the AI model files. It helps detect threats like backdoors and runtime issues, especially when users upload custom models through Custom Model Import (CMI) in Amazon Bedrock. By scanning models with Guardian, organizations can make informed decisions when selecting AI systems.
Identifying Vulnerabilities with Recon
Once the models are scanned and deemed safe, organizations can use Recon to investigate potential runtime vulnerabilities. This tool simulates real-world adversarial attacks to identify vulnerabilities and assists users in configuring necessary security measures through Amazon Bedrock Guardrails. Features such as content filters and controls for preventing prompt injection and jailbreaking are part of this security process.
Continuous Monitoring for Ongoing Security
Maintaining security measures does not stop after deployment. Recon’s capabilities extend to creating a library of known attacks and continuously updating these threats. Regularly scanning model endpoints enables businesses to ensure their security protocols are functioning correctly. If new vulnerabilities are found, Recon generates reports highlighting the issues, allowing businesses to adapt their security strategies proactively.
Advantages of Integrating Protect AI with Amazon Bedrock
Efficient AI Security Workflows: Organizations can easily integrate Guardian and Recon within AWS environments without needing additional development.
Fast Deployment: The speed of scanning and automated assessments allows for quick yet secure AI deployments, ensuring that businesses can innovate without delays.
Proactive Vulnerability Management: Early detection and remediation of vulnerabilities help reduce compliance and reputation risks significantly.
Consistent AI Governance: Protect AI’s solutions comply with industry frameworks, ensuring a robust adherence to security standards.
With the growing importance of generative AI in the corporate landscape, securing these systems effectively is essential for successful deployment. The tools offered by Protect AI, when combined with Amazon Bedrock, provide businesses with the comprehensive security measures necessary to safeguard their AI innovations.
