GitHub Copilot Coding Agent Now Ships with Automatic Security Scanning—Here’s What Changed

TL;DR GitHub Copilot coding agent now automatically analyzes new code it generates using GitHub’s security and quality validation tools . When Copilot writes new code, it analyzes it for potential security vulnerabilities using CodeQL, checks any newly-introduced dependencies against the GitHub Advisory Database, and uses secret scanning to detect sensitive information such as API keys and tokens . Three major updates landed Oct 28–29: Linear issue assignment support , enhanced code review blending LLM detections with deterministic tools like ESLint and CodeQL , and GitHub Code Quality in public preview . For .NET and Azure teams, this means less manual security churn and faster feedback loops.

The Security Shift: Agents That Police Themselves

Until now, delegating code generation to an AI agent felt like a leap of faith. With this release, new code generated by Copilot coding agent is automatically analyzed by GitHub’s security and quality validation tools . That’s not a nice-to-have—it’s a game-changer for enterprise .NET shops.

Here’s what happens under the hood:

- CodeQL scans for potential security vulnerabilities, the GitHub Advisory Database checks newly-introduced dependencies, and secret scanning detects sensitive information such as API keys and tokens - If the security validation or code review tools find any problems, Copilot attempts to resolve them before finishing the pull request and summarizing the actions taken in the pull request summary Why this matters: Automated security and quality validations for Copilot coding agent don’t require a GitHub Advanced Security license or any additional configuration—these security tools are seamlessly included with your normal Copilot coding agent usage .

Three New Capabilities Rolling Out Now

1. Linear Integration (Public Preview)

You can now assign issues in Linear to Copilot coding agent, our asynchronous, autonomous background agent. When you assign a Linear issue to Copilot, it will analyze the issue contents and open a draft pull request .

For .NET teams using Linear: This closes the tool-switching loop. No more jumping between Linear and GitHub. Copilot works independently in its own ephemeral development environment, powered by GitHub Actions, where it can explore your code, make changes, run automated tests and linters, and more .

2. Smarter Code Review (Public Preview)

Copilot code review now blends LLM detections and tool calling with deterministic tools like ESLint and CodeQL, delivering smarter reviews and a seamless handoff to the Copilot coding agent for fixes .

The key innovation: CCR now leverages agentic tool calling to actively gather full project context, including code, directory structure, and references. This enables CCR to understand how your changes fit within the broader project architecture .

Practical win: You can now hand off suggested changes directly to the Copilot coding agent. Mention @copilot in your pull request, and CCR will automatically apply the suggested fixes in a stacked pull request, ready for you to review and merge .

3. GitHub Code Quality (Public Preview)

GitHub Code Quality is now available in public preview. It turns every pull request into an opportunity to improve . CodeQL-based quality rules detect maintainability and reliability issues in Java, C#, Python, JavaScript, Go, and Ruby . For .NET devs, this means your C# code gets real-time quality scoring alongside security checks.

Integration with Azure and .NET Ecosystem

The first stable release of the Azure AI Foundry library for .NET provides comprehensive access to Azure AI Foundry Project resources. This release introduces important API improvements with consistent AIProject prefixing for key models, simplified client access through direct properties on AIProjectClient, and new convenience CreateOrUpdate methods for index management .

If you’re building agents in .NET, Microsoft Agent Framework enables developers to build AI agents with minimal code requirements. The company demonstrated this simplicity with examples showing functional agents created in fewer than twenty lines of code .

What to Watch

A robot confidently reviewing code while a human nervously watches over its shoulder, both staring at a pull request. The robot has a checkmark badge on its chest. Alt text: "Copilot's new security scanner: now with 100% more confidence and 0% more coffee breaks."

The automation is accelerating. 80% of new developers on GitHub use Copilot in their first week , and more than 1.1 million public repositories now use an LLM SDK with 693,867 of these projects created in just the past 12 months alone .

For teams shipping on GitHub, Azure, and .NET:

Cost: No extra licensing for the security scanning.
Latency: Agents work asynchronously; feedback comes via Linear or GitHub notifications.
Integration: Use the GitHub Marketplace to install the Linear integration; no API keys needed if you’re already on GitHub Enterprise.

Getting Started

Enable Copilot coding agent for your repo (available on all paid Copilot plans).
Try Linear integration via the GitHub Marketplace.
Opt into Code Quality in your repository settings (free during preview; scans use GitHub Actions minutes).
For .NET projects: Pair with Microsoft Agent Framework, which is Microsoft’s preview framework for building AI agents in .NET. Think of it as the next evolution beyond simple chatbots. It’s built on patterns we already know and love as .NET developers: dependency injection, middleware, telemetry—all integrated with Microsoft.Extensions.AI .

GitHub Copilot Coding Agent Now Ships with Automatic Security Scanning—Here's What Changed