The AWS API MCP Server is now available on AWS Marketplace

AWS announces the availability of the AWS API MCP Server on AWS Marketplace, enabling customers to deploy the Model Context Protocol (MCP) server to Amazon Bedrock AgentCore. The marketplace entry includes step-by-step configuration and deployment instructions for deploying the AWS API MCP Server as a managed service with built-in authentication and session isolation to Bedrock Agent Core Runtime. The AWS Marketplace deployment simplifies container management while providing enterprise-grade security, scalability, and session isolation through Amazon Bedrock AgentCore Runtime. Customers can deploy the AWS API MCP Server with configurable authentication methods (SigV4 or JWT), implement least-privilege IAM policies, and leverage AgentCore’s built-in logging and monitoring capabilities. The deployment lets customers configure IAM roles, authentication methods, and network settings according to their security requirements. The AWS API MCP Server can now be deployed from AWS Marketplace in all AWS Regions where Amazon Bedrock AgentCore is supported. Get started by visiting the AWS API MCP Server listing on AWS Marketplace or explore the deployment guide on AWS Labs GitHub repository. Learn more about Amazon Bedrock AgentCore in the AWS documentation.
Quelle: aws.amazon.com

Amazon Aurora now supports PostgreSQL 17.6, 16.10, 15.14, 14.19, and 13.22

Amazon Aurora PostgreSQL-Compatible Edition has added support for PostgreSQL versions 17.6, 16.10, 15.14, 14.19, and 13.22. The update includes the PostgreSQL community’s product improvements and bug fixes, and also includes Aurora-specific enhancements.
Dynamic Data Masking (DDM) (16.10 and 17.6 only) is a new database-level security feature that protects sensitive data like personally identifiable information by masking column values dynamically at query time based on role-based policies, without altering the actual stored data. This release also includes a shared plan cache, improved performance and recovery-time-objective (RTO) and improvement for Global Database switchovers. To use the new versions, create a new Aurora PostgreSQL-compatible database with just a few clicks in the Amazon RDS Management Console. You can also upgrade your existing database. Please review the Aurora documentation to learn more about upgrading. Refer to the Aurora version policy to help you to decide how often to upgrade and how to plan your upgrade process. These releases are available in all commercial AWS Regions and the AWS GovCloud (US) Regions. Amazon Aurora is designed for unparalleled high performance and availability at global scale with full MySQL and PostgreSQL compatibility. It provides built-in security, continuous backups, serverless compute, up to 15 read replicas, automated multi-Region replication, and integrations with other AWS services. To get started with Amazon Aurora, take a look at our getting started page.
Quelle: aws.amazon.com

Amazon Kinesis Video Streams now supports a new cost effective warm storage tier

AWS announces a new warm storage tier for Amazon Kinesis Video Streams (Amazon KVS), delivering cost-effective storage for extended media retention. The standard Amazon KVS storage tier, now designated as the hot tier, remains optimized for real-time data access and short-term storage. The new warm tier enables long-term media retention with sub-second access latency at reduced storage costs. The warm storage tier enables developers of home security and enterprise video monitoring solutions to cost-effectively stream data from devices, cameras, and mobile phones while maintaining extended retention periods for video analytics and regulatory compliance. Moreover, developers now have the flexibility to configure fragment sizes based on their specific requirements — selecting smaller fragments for lower latency use cases or larger fragments to reduce ingestion costs. Both hot and warm storage tiers integrate seamlessly with Amazon Rekognition Video and Amazon SageMaker, enabling continuous data processing to support the creation of computer vision and video analytics applications. Amazon Kinesis Video Streams with the new warm storage tier is available in all regions where Amazon Kinesis Video Streams is available, except the AWS GovCloud (US) Regions. To learn more, refer to the getting started guide.
Quelle: aws.amazon.com

Security that strengthens the ecosystem: Docker’s upstream approach to CVE-2025-12735

On November 24, 2025, Docker Hardened Images resolved CVE-2025-12735 in the Kibana project, which is the visualization and user interface layer for Elasticsearch. This CVE is a critical remote code execution vulnerability that scored 9.8 on the CVSS scale. While images from other hardened image vendors were still carrying the vulnerability, Docker’s security team and tooling not only patched the CVE  for Docker Hardened Images users, but also submitted the fix to the upstream LangChain.js project. Once that pull request merges, every application that depends on LangChain.js will benefit from a more secure foundation across the entire ecosystem.

We always default to upstream patching when possible because it protects everyone who depends on these libraries – not just Docker users. Upstream patches require effort. You have to submit a PR and get it approved by the project. That can mean back and forth with maintainers. Security teams are under intense time pressures. But when we fix expr-eval for LangChain.js, we’re protecting not just Kibana users but every application that depends on that library. That’s over one million weekly downloads that become more secure.

Another Nested Dependency, Another Ticking Time Bomb

CVE-2025-12735 originated in expr-eval, a JavaScript expression parser and evaluator library. The vulnerability allowed attackers to inject crafted variables into evaluate(), enabling untrusted code paths to execute logic the application never intended. Three layers deep into the dependency chain, there was a critical RCE vulnerability in unmaintained code. In practice, this gave attackers a pathway to execute malicious behavior within affected applications. The library hadn’t been updated in years. LangChain.js depends on expr-eval, which means any application or service built with LangChain.js inherits the vulnerability. This includes AI assistants, workflow tools, and LLM-powered applications widely deployed across the industry. Kibana was affected by the same dependency chain. 

This matters because LangChain.js has become a foundational component in modern application development. The library provides a framework for building applications powered by large language models, and it has been downloaded millions of times from npm. As of November 18, 2025, the npm package langchain (which includes LangChain.js) receives approximately 1,018,076 weekly downloads. Organizations use LangChain.js to build chatbots, document analysis systems, customer service platforms, and AI-powered search tools. When a vulnerability exists in LangChain.js or its dependencies, it potentially affects thousands of production applications across the technology industry.

This is exactly the attack surface that sophisticated adversaries target. The 2024 XZ Utils backdoor attempt demonstrated how attackers focus on dependencies precisely because they affect so many downstream projects. Old vulnerabilities remain a persistent challenge because organizations focus on direct dependencies while nested dependencies slip through the cracks.

Why We Must Fix at the Source, Fast

Many security and hardened image vendors scan for CVEs, flag them, and patch their own images. The vulnerability remains in the upstream project. The next build cycle reintroduces it. The problem persists for every other user of that dependency chain. This approach treats symptoms instead of causes. You patch your copy of Kibana. The next developer who builds from upstream gets the vulnerable version. Other container image providers may still ship the vulnerable dependency until their next update cycle. When the next CVE gets assigned to expr-eval, the cycle repeats.

Docker takes a different approach. When the Docker Security team identified CVE-2025-12735 in Kibana, we traced it back through the dependency chain to expr-eval. Rather than applying a surface-level patch, we replaced the unmaintained library with math-expression-evaluator, an actively maintained alternative that did not have the vulnerability. Then we contributed that fix upstream to LangChain.js: Pull Request #9391.

This approach delivers three outcomes:

Docker Hardened Images users got immediate protection. The updated Kibana image shipped without the vulnerable dependency. There was no waiting for upstream maintainers and no emergency patching required.

The entire LangChain.js ecosystem will benefit. Once the PR merged, every project using LangChain.js inherits the fix automatically. Web applications, data processing pipelines, AI tools, and analytics platforms all get safer because the fix lives where it belongs.

Future builds are secure by default. Docker doesn’t have to maintain downstream patches or worry about the vulnerability reappearing in the next release cycle. The fix lives in the upstream project where it belongs.

Docker Hardened Images responded faster than other  vendors. We identified the root cause, selected a maintained replacement, verified it worked correctly, and contributed the fix back to the upstream project. This is possible because Docker’s security architecture is designed for a high-speed workflow without sacrificing thoroughness or attention to detail. (We are also, as a team, strongly committed to contributing back to open source!) Continuous dependency analysis through Docker Scout identifies issues the moment they’re disclosed. Deep supply chain visibility shows not just what packages are in an image but the entire dependency chain. Direct upstream engagement means we can contribute fixes rather than wait for maintainers to respond to bug reports.

What This Means for Your Organization

If you’re running Kibana in production, CVE-2025-12735 posed a critical risk. Organizations using Docker Hardened Images received immediate protection with secure, minimal, production-ready container images built from source and backed by a fast SLA that ensures rapid remediation.. The updated image shipped with expr-eval replaced by a maintained alternative. No emergency patching was required and there was no downtime. Organizations using other container distributions may still be exposed. Check your Kibana images for the vulnerable expr-eval dependency. If you’re running upstream Kibana, monitor for the LangChain.js update that incorporates Docker’s fix.

But the implications extend beyond this single CVE. The nested dependency problem affects every modern application. Your development teams probably don’t know what libraries are three or four levels deep in your dependency trees. Your security scanners might not catch them. Your vendors might not fix them upstream.

Helping Open Source Projects Helps Us All

The container ecosystem depends on thousands of open source projects. Most are maintained by small teams, often volunteers, who juggle security alongside feature development, bug fixes, and user support. When vulnerabilities emerge, maintainers may lack resources for immediate response.

Commercial vendors who benefit from open source have a responsibility to contribute back. When Docker Security fixes vulnerabilities upstream, open source maintainers get security support at no cost. The entire community benefits from hardened dependencies. Docker builds trust with the projects that power modern infrastructure. Future vulnerabilities become easier to address as relationships deepen. Together, we are more secure.

Docker is not the only company to push patches upstream, but it is a core part of our DNA. We don’t just protect our own customers but strengthen the entire ecosystem. Fixes go upstream so everyone benefits. The focus is on eliminating vulnerabilities at their source rather than playing endless rounds of patch-and-scan.

Modern supply chain attacks move faster than traditional security response times. Docker Hardened Images and Docker Scout are designed to match that speed while strengthening the entire ecosystem through upstream contributions. When vulnerabilities emerge, our customers get immediate protection. When our fixes go upstream, everyone gets safer.

Learn more about how Docker Hardened Images deliver security that protects your organization and strengthens the ecosystem.
Quelle: https://blog.docker.com/feed/