Ensuring Security in Generative AI: The Collaboration Between AWS and Datadog

A Comprehensive Approach to Protecting Amazon Bedrock Deployments

Enhancing AI Security with Datadog Cloud Security

Addressing Misconfigurations and Regulatory Compliance in AI Systems

The Future of AI Adoption: A Partnership Built on Security

Leveraging Datadog for Seamless Monitoring of Amazon Bedrock Resources

Safeguarding AI Infrastructure Against Emerging Threats

Navigating Security Risks in Cloud AI Environments with Datadog

Conclusion: Building a Secure AI Ecosystem Together

Securing AI with Confidence: Integrating Amazon Bedrock and Datadog

Co-written by Nick Frichette and Vijay George from Datadog

In the ever-evolving landscape of technology, the adoption of generative AI is rapidly gaining momentum. Organizations are increasingly gravitating towards Amazon Bedrock for their AI initiatives, leading to a pressing need for robust security measures. As highlighted in the AWS Generative AI Adoption Index, 45% of surveyed IT decision-makers identified generative AI tools as their top budget priority in 2025. As businesses delve into AI, ensuring data protection against misconfigurations and unauthorized model access is critical.

Understanding AI Security Needs

With AI adoption comes the responsibility of managing its risks. These risks can’t be viewed in isolation; they must be contextualized alongside identity exposures, misconfigurations, and other vulnerabilities. This is where the combination of Amazon Bedrock and Datadog’s comprehensive security monitoring can empower organizations to innovate while maintaining stringent security controls.

Built-In Security of Amazon Bedrock

Amazon Bedrock stands as a bastion of enterprise-grade security, encompassing several essential features:

• Data Privacy: Your input, prompts, and outputs remain confidential and are not shared with model providers.
• Encryption: Data is encrypted both in transit using TLS 1.2 or above and at rest with AWS Key Management Service (AWS KMS).
• Access Controls: Tightly governed by AWS Identity and Access Management (IAM), allowing for granular authorization.

Moreover, Amazon Bedrock aligns with key industry standards such as ISO, SOC, HIPAA, GDPR, and FedRAMP High, making it a viable choice for regulated industries.

Datadog’s Security Monitoring

Building upon these robust security features, Datadog’s integration with AWS offers a holistic view of potential risks within AI infrastructure. Datadog Cloud Security uses agentless and agent-based scanning to pinpoint vulnerabilities and misconfigurations.

Exciting new capabilities are being rolled out within Datadog Cloud Security to detect and remediate Amazon Bedrock misconfigurations proactively. This feature not only enhances compliance but enables organizations to seamlessly incorporate AI security into their broader cloud security strategy.

Bridging the Gap: AWS and Datadog Partnership

The collaboration between AWS and Datadog seeks to create an ecosystem where customers can securely operate their cloud infrastructure. This partnership’s recent extension to Amazon Bedrock is a natural progression, driven by customer demand and robust security needs. Datadog’s long-standing integration capabilities facilitate rapid development of security monitoring tailored for Amazon Bedrock.

The Emerging Threat Landscape

As generative AI is embraced, the threat landscape evolves. In Q4 2024, Datadog Security Research noted a surge in malicious interest targeting cloud AI environments. Integrating AWS’s powerful AI capabilities with Datadog’s security expertise allows organizations to accelerate AI adoption while upholding robust security measures.

How Datadog Secures Amazon Bedrock

Upon adding the AWS integration to your Datadog account and enabling Datadog Cloud Security, your AWS environment undergoes continuous monitoring. Datadog identifies misconfigurations, identity risks, and compliance violations.

For instance, an essential detection involves ensuring Amazon Bedrock custom models do not source data from publicly writable S3 buckets. Misconfiguration here can expose sensitive data or allow data poisoning attacks, where malicious actors compromise the training dataset of your AI models.

Real-Time Detection and Remediation

Datadog provides real-time risk assessments and remediation guidance. If a misconfigured S3 bucket is identified, Datadog generates detailed steps to rectify the issue, enhancing compliance and protecting sensitive information.

Conclusion: Unlocking Safe AI Adoption

As generative AI becomes entrenched across various sectors, organizations must be vigilant in managing associated risks. With Datadog Cloud Security, organizations gain the clarity and context needed to navigate these challenges confidently.

To further bolster your AI security, explore Datadog’s agentic AI features, including the innovative Bits AI Security Analyst. This automated tool simplifies threat triage, allowing teams to focus on critical threat-hunting activities.

For businesses eager to secure their AI environments, contacting Datadog to learn more about Amazon Bedrock integration could be the first step toward a safer and more compliant future.

Get Started

If you’re ready to enhance your AI security posture, consider a 14-day free trial of Datadog Cloud Security. It’s the right time to harness powerful AI capabilities while ensuring their secure implementation.