Skip to main content

Azure Cosmos DB - Security Overview


Azure Cosmos DB it is starting to become one of my favourite database for storing content. The integration with reporting and analytics services change the way how we integrate Azure Cosmos DB inside the application ecosystem.
In this post, we take a high-level overview of the security features that Azure Cosmos DB has at this moment in time. Each time when a new type of repository needs to be integrated or used inside a solution, the security requirements need to be validated.
Overview

  1. Access Layer: YES, RBAC, Users and Permissions, Master Keys, Resource Keys
  2. Transport Layer: YES, TLS 1.2
  3. Network Layer: YES, IP based filter for inbound traffic and VNET integration
  4. Application Layer: YES, using SDK and API
  5. Storage Layer: YES, data is encrypted

Access control
Network: IP firewall security layer. There is the ability to define policies to filter inbound traffic based on the IP. Once you define the list of approved IPs, requests from any other IPs is refused.
Authorization: There is the ability to use master or resource key to specify access to resources. The access level can be controlled up to document level. Behind the scene, the HMAC authorisation model is used.
Permission: Using the master key, permissions can be generated for RW/R/No access to a different level of an Azure Cosmos DB resources (functions (UDF), triggers, stored procedures, attachment, document, container, database). Permissions are attached to users.
Users: An Azure Cosmos DB database can be associated with one or multiple users. Each user can have specific permissions on the database resources.
RBAC (AD integration): Access to the database can be done using RBAC using existing users and roles that you already defined inside the AD.
Transport: All internal and external communication with Azure Cosmos DB is encrypted using TLS 1.2
Virtual Networks: There is the ability to specify what VNET Azure Cosmos DB can be accessed

Data protection
Local replication: Data is replicated inside the data center in multiple locations, offering an availability SLA of 99.99%.  
Regional failovers: Data can be automatical replicated in multiple Azure Regions around the globe, offering the capability to be protected in case of failover. Using multiple-regions, the read availability reaches 99.999%.
Backups: Automatical backups stored inside redundant storage are done at specific time intervals. All automatical backups are stored for 30 days and can be used to restore the data. Custom backup retention policies and triggers can be defined.
Data storage: Data is encrypted at REST. All data persistent inside Azure Cosmos DB is encrypted.
Geo-fencing: For specific regions around the world (China, US Government, Germany), the data governance is strictly controlled by local authorities or companies.
Attack protection: Azure security response team has a 5-step incident response process that ensures that any incidents are solved as fast as possible with a minimal impact.
Audit and monitoring: Activity logs and audit logging enables users to monitor activity and access to the data. Attacks or abnormal activities can be identified, and the full activity path can be obtained.
Security certifications: There is a long list of certifications and compliances that Azure Cosmos DB has, including SOCS ½ Type 2, PCI DSS Level 1, ISO 27001, HIPA, HITRUST, FedRamp High and so on.

Security tips and tricks
  • 1     Master keys can be regenerated anytime
  • 2.       Master keys cannot be used to granular access to document and containers
  • 3.       Resource keys are created when a user is granted access to specific resources
  • 4.       Resource keys maximum lifetime is 5 hours with a default value of 1 hour
  • 5.       Users are associated with Azure Cosmos DB databases
  • 6.       IP access control restriction changes can take up to 15 minutes to propagate
  • 7.       Column level encryption is available for Table API
  • 8.       There is no support for BYOK or CMK

Comments

Popular posts from this blog

Windows Docker Containers can make WIN32 API calls, use COM and ASP.NET WebForms

After the last post , I received two interesting questions related to Docker and Windows. People were interested if we do Win32 API calls from a Docker container and if there is support for COM. WIN32 Support To test calls to WIN32 API, let’s try to populate SYSTEM_INFO class. [StructLayout(LayoutKind.Sequential)] public struct SYSTEM_INFO { public uint dwOemId; public uint dwPageSize; public uint lpMinimumApplicationAddress; public uint lpMaximumApplicationAddress; public uint dwActiveProcessorMask; public uint dwNumberOfProcessors; public uint dwProcessorType; public uint dwAllocationGranularity; public uint dwProcessorLevel; public uint dwProcessorRevision; } ... [DllImport("kernel32")] static extern void GetSystemInfo(ref SYSTEM_INFO pSI); ... SYSTEM_INFO pSI = new SYSTEM_INFO(

Azure AD and AWS Cognito side-by-side

In the last few weeks, I was involved in multiple opportunities on Microsoft Azure and Amazon, where we had to analyse AWS Cognito, Azure AD and other solutions that are available on the market. I decided to consolidate in one post all features and differences that I identified for both of them that we should need to take into account. Take into account that Azure AD is an identity and access management services well integrated with Microsoft stack. In comparison, AWS Cognito is just a user sign-up, sign-in and access control and nothing more. The focus is not on the main features, is more on small things that can make a difference when you want to decide where we want to store and manage our users.  This information might be useful in the future when we need to decide where we want to keep and manage our users.  Feature Azure AD (B2C, B2C) AWS Cognito Access token lifetime Default 1h – the value is configurable 1h – cannot be modified

What to do when you hit the throughput limits of Azure Storage (Blobs)

In this post we will talk about how we can detect when we hit a throughput limit of Azure Storage and what we can do in that moment. Context If we take a look on Scalability Targets of Azure Storage ( https://azure.microsoft.com/en-us/documentation/articles/storage-scalability-targets/ ) we will observe that the limits are prety high. But, based on our business logic we can end up at this limits. If you create a system that is hitted by a high number of device, you can hit easily the total number of requests rate that can be done on a Storage Account. This limits on Azure is 20.000 IOPS (entities or messages per second) where (and this is very important) the size of the request is 1KB. Normally, if you make a load tests where 20.000 clients will hit different blobs storages from the same Azure Storage Account, this limits can be reached. How we can detect this problem? From client, we can detect that this limits was reached based on the HTTP error code that is returned by HTTP