Copa: An Image Vulnerability Patching Tool
Securing container images is paramount, especially with the widespread adoption of containerization technologies like Docker and Kubernetes. Microsoft has recognized the need for robust image security solutions and has introduced Copa, an open-source tool designed to keep container images secure and address vulnerabilities swiftly. Learn about Copa in this blog.The History of Microsoft Azure
Learn about the history of Microsoft Azure a leading giant in the cloud service industry which offers rich services on platform as a service (PaaS), software as a service (Saas) and infrastructure as a service (IaaS). This will take us back to the moments on how this powerful and sophisticated service began, revealing the resilience and vision of the Microsoft company as a brand, the present stages and how to partake of the cake Microsoft has provided for businesses and developers.Vulnerability Assessment on Azure Container Registry with Microsoft Defender and Docker Hub
Azure Container Registry: Microsoft Defender for Containers and Docker Scout. Rather than comparing these tools, I want to highlight how they complement each other to enhance container security on ACR. Containers revolutionize the way applications are deployed, providing a consistent and efficient way to package code and dependencies. However, with this convenience comes the critical need for robust security measures. In this post, we'll explore why container security is essential, focusing on preventing malicious code, avoiding vulnerabilities, and managing configuration and deployment risks.Boosting Code Security with GHAS Code Scanning in Azure DevOps & GitHub
Code scanning, a pipeline-based tool available in GitHub Advanced Security, is designed to detect code vulnerabilities and bugs within the source code of ADO (Azure DevOps) repositories. Utilizing CodeQL as a static analysis tool, it performs query analysis and variant analysis. When vulnerabilities are found, it generates security alerts. CodeQL CodeQL is a powerful static analysis tool used for showing vulnerabilities and bugs in source code. It enables developers to write custom queries that analyze codebases, searching for specific patterns and potential security issues. By converting code into a database format, CodeQL allows for sophisticated, database-like queries to detect flaws. CodeQL in Action 1. Preparing the Code Create a CodeQL Database: Extract and structure the code into a database for analysis. 2. Running CodeQL Queries Execute Queries: Run predefined or custom queries against the database to find potential issues. 3. Interpreting the Query Results Review Findings: Analyze the results to find, prioritize, and address vulnerabilities and code quality issues. Reference: - About the CodeQL CLI - GitHub Docs Sample Code Scanning Azure DevOps Pipeline Once the GitHub Advanced security is configured for the ADO Repo we can then create and run a dedicated Code scanning pipeline to detect vulnerability & generate query results & alerts. Below is a generic sample Code scanning pipeline Prerequisites: - GitHub Token (GitHub token): Required Pipeline Variable for authenticated operations with GitHub. CodeQL Results File Path (codeql_results_file): Predefined in the pipeline YAML variable to specify where the analysis results are stored. SARIF SAST Scans Tab extension: Need to install it from Azure DevOps Marketplace to view query results # Author: Debjyoti # This pipeline uses default CodeQL queries for code scanning trigger: none pool: vmImage: 'windows-latest' variables: codeql_results_file: '$(Build.ArtifactStagingDirectory)/results.sarif' steps: - task: AdvancedSecurity-Codeql-Init@1 displayName: 'Initialize CodeQL' inputs: languages: 'python' loglevel: '2' env: GITHUB_TOKEN: $(githubtoken) - task: AdvancedSecurity-Codeql-Autobuild@1 displayName: 'AutoBuild' - task: AdvancedSecurity-Codeql-Analyze@1 displayName: 'Perform CodeQL Analysis' inputs: outputFile: '$(codeql_results_file)' - task: PublishBuildArtifacts@1 displayName: 'Publish CodeQL Results' inputs: pathToPublish: '$(codeql_results_file)' artifactName: 'CodeQLResults' For further insights and detailed guides, please refer to the following articles: https://learn.microsoft.com/azure/devops/repos/security/configure-github-advanced-security-features?view=azure-devops&tabs=yaml https://learn.microsoft.com/azure/devops/repos/security/github-advanced-security-code-scanning?view=azure-devops Default setup of Code Scanning in GitHub Repository Requirements for Using Default Setup GitHub Actions: Must be enabled. Recommendations Enable default setup if there is any chance of including at least one CodeQL-supported language in the future. Default setup will not run or use GitHub Actions minutes if no CodeQL-supported languages are present. If CodeQL-supported languages are added, default setup will automatically begin scanning and using minutes. Customizing Default Setup Start with default setup. Evaluate code scanning performance. Customize if needed to better meet security needs. Configuring Default Setup for a Repository Automatic Analysis: All CodeQL-supported languages will be analyzed. Successful Analysis: Languages analyzed successfully will be retained. Unsuccessful Analysis: Languages not analyzed successfully will be deselected. Failure Handling: If all analyses fail, default setup stays enabled but inactive until a supported language is added, or setup is manually reconfigured. Steps to Enable Default Setup Navigate to Repository: Go to the main page of the repository. Access Settings: Click on "Settings" under the repository name. If "Settings" is not visible, select the dropdown menu and click "Settings". Security Settings: In the "Security" section of the sidebar, click "Code security and analysis". 4. Setup Code Scanning: In the "Code scanning" section, select "Set up" and click "Default". Review Configuration: A dialog will summarize the automatically created code scanning configuration. Optionally, select a query suite in the "Query suites" section. Extended query suite runs additional, lower severity and precision queries. Enable CodeQL: Review settings and click "Enable CodeQL" to trigger a workflow. View Configuration: After enablement, view the configuration by selecting the relevant choice. CodeQL Analysis Run: Once CodeQL is set up, it will run on the repository to check for vulnerabilities in the supported language code. You can view more information by clicking on the "View last scan" option. View Security Alerts: It will run its default built-in queries on the repository code for the supported language (in this case, Python) and will generate alerts for any detected vulnerabilities. Reference Link for more insights - https://docs.github.com/en/code-security/code-scanning/enabling-code-scanning/configuring-default-setup-for-code-scanning https://docs.github.com/en/code-security/code-scanning/managing-your-code-scanning-configuration/python-built-in-queries Benefits of Running Code QL for Developers Responsibilities and Burdens Initial Setup and Learning Curve: Requires time to set up and learn how to use effectively. Maintenance of Queries: Custom queries may need updates as the codebase evolves. False Positives: May generate false positives that need to be reviewed and addressed. Integration Effort: Integrating Code QL into existing CI/CD pipelines can require significant effort.Revolutionizing Road Safety: Power Platform AI-Powered Vehicle Identification & Verification System
Explore our groundbreaking project leveraging AI Builder and Microsoft technologies for vehicle and driver identification. Enhance road safety, prevent theft, and streamline verification processes with our innovative system. Join us in exploring the potential of AI in traffic management.Azure DevOps for Beginners: How to Set Up Your Account, Organization, and Repository
Microsoft Learn Student Ambassador and developer in Power Platform and Dynamics 365 Customer Engagement, Rachel Irabor, shares how to create a new organization and repository in Azure DevOps. This step-by-step guide will walk you through the process of setting up an Azure DevOps account and creating a new organization, project, and repository. Follow this guide and start building your own projects in Azure DevOps.
