Averlon + GitHub Advanced Security: Turning Code Scanning Into Safer, Faster Fixes

Most teams rely on GitHub Advanced Security to uncover code vulnerabilities and identify leaked credentials early in the development process. It is one of the most widely adopted platforms for catching issues before they leave the repository. The challenge however is rarely detection. It is everything that comes after.

Static analysis generates high volumes of findings. Secret scanning catches credentials early but still demands immediate action. Developers want clarity on what truly matters. Security teams want confidence that fixes are safe and complete. Engineering leaders want security that fits into existing workflows without slowing their roadmap.

Modern application security demands smarter automation. That's why we're excited to share our new integration with GitHub Advanced Security, the comprehensive security platform trusted by enterprises worldwide.

GitHub Advanced Security identifies vulnerabilities in your code through CodeQL analysis and detects exposed secrets before they reach production. Averlon builds on that foundation by using agentic AI to determine which findings represent real risk, why they matter in your specific environment, and automatically implements safe remediations to eliminate exposure faster.

This integration helps teams ship secure code faster, maintain development velocity, and turn static analysis overload into meaningful, automated action that reduces real risk.

Why GitHub Advanced Security and Averlon: A Better Way to Fix Code Vulnerabilities

Security and engineering teams want the same outcome. They want secure applications without slowing development. GitHub Advanced Security does a great job of finding issues in code. The real challenge for most organizations is understanding which issues matter and getting them fixed quickly and safely.

Recent 2025 data shows how wide this gap has become. GitGuardian detected 23,770,171 leaked secrets in public GitHub commits in 2024, a 25 percent increase year over year. Seventy percent of the secrets leaked in 2022 are still valid today, which shows how long exposed credentials remain usable when not remediated quickly. Breaches that involve stolen or compromised credentials take an average of 292 days to identify and remediate. At the same time, Edgescan reports that high and critical application vulnerabilities take an average of 74.3 days to fix, which highlights how slow code remediation remains for many teams.

Together, these data points show how detection has far outpaced remediation. Teams generate more findings than they can address, code vulnerabilities remain open for long periods, and leaked secrets linger far longer than most organizations expect.

This is where the integration matters. GitHub Advanced Security identifies issues early in the development lifecycle. Averlon adds the context and automation needed to move those findings to safe resolution. Together they reduce open risk by validating exploitability, generating safe code fixes, rotating leaked secrets, and giving teams a faster path from detection to remediation.

With the integration in place, security and engineering teams can:

• Understand which code vulnerabilities are actually exploitable and need immediate attention
• Automatically generate and validate safe code fixes for common vulnerability patterns
• Instantly rotate exposed secrets and update dependent systems
• Connect each finding to the right team with full remediation context

How This Integration Works

GitHub Advanced Security stays the source of truth for code and secret findings. Averlon becomes the layer that moves those findings to resolution.

1. Advanced Security scans your code continuously. CodeQL analyzes every commit for security vulnerabilities while Secret Scanning detects exposed credentials across your repositories.
2. Averlon enriches findings with runtime context. Each vulnerability is evaluated against your actual deployment environment, API usage patterns, and authentication flows to determine real exploitability.
3. Agentic AI drives automated fixes. Averlon generates safe, tested remediations for common vulnerability patterns, from SQL injection fixes to proper input validation, and creates pull requests with full context.
4. Secrets are automatically rotated. When credentials are exposed, Averlon orchestrates immediate rotation, updates dependent services, and validates the remediation across your environment.
5. Risk reduction happens in real-time. While permanent fixes are being implemented, Averlon can deploy immediate mitigations like WAF rules or API rate limits to contain exposure.

The result is faster remediation, with many vulnerabilities fixed automatically before they reach production.

What Teams Gain

This integration is built for organizations that want:

• Smaller backlogs of unaddressed code issues
• Automatic response to leaked credentials
• Faster pull requests with validated fixes
• Less manual coordination between security and engineering
• A consistent, predictable remediation workflow across repositories

Most security programs are not struggling because they lack visibility. They are struggling because they lack the contextual insights and capacity to act on that visibility quickly. Averlon and GitHub Advanced Security together close that gap in a way that keeps security aligned to developer velocity.

Ready to See It in Action

The integration is available now for teams already using GitHub Advanced Security.

If you want to see how Averlon converts findings into fast, safe remediations, we’re happy to walk through it with your team.

Request a walkthrough: https://averlon.ai/demo