Top 5 GitHub CodeQL alternatives

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CodeQL is a semantic code analysis engine. It turns your code into a database and runs queries against it to trace how data flows through the application, and it powers GitHub code scanning. You can use the standard query suites or extend them with your own queries.

GitHub sells CodeQL to private repositories as part of GitHub Code Security, which also adds Copilot Autofix suggestions and an AI scan of pull requests, generally available since October 2026. An AI scan of whole repositories is in public preview. Secret scanning is sold separately as GitHub Secret Protection, and Dependabot alerts are available on every repository.

For public repositories, CodeQL code scanning, Copilot Autofix, secret scanning and push protection are free. For private repositories, Code Security costs $30 per active committer a month, on top of GitHub Team or Enterprise seats.

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CodeQL does a lot well, but teams usually start looking elsewhere for one of three reasons.

1. Queries find only what they describe. CodeQL's dataflow analysis is strong on injection and file-handling flaws, but a query cannot tell whether one team should be able to read another team's data, or whether a user should be allowed to take an action. In our benchmark on an open-source TypeScript application, 1 of the 6 findings CodeQL reported was a real vulnerability, a low-severity issue (full comparison↗).

2. Private repositories add per-committer fees. Code Security costs $30 and Secret Protection $19 per active committer a month, as add-ons to GitHub Team at $4 per user or to Enterprise. For a team of 10 on Team with Code Security, that comes to $340 a month. AI Scan and agentic autofix use metered AI credits, and GitHub does not publish the credit cost of a scan.

3. It stays inside the code and inside GitHub. CodeQL and Code Security analyse source code. They do not run black-box or white-box pentests, prove findings against your running application or keep monitoring it. Findings sync to GitHub Issues only, with no Jira or Linear integration, and self-hosting requires GitHub Enterprise Server with Code Security.

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Here is how the leading alternatives compare, starting with the one we build.

#1 AISafe Labs

AISafe Labs is an application security platform that uses AI agents to test your code and your running application the way an attacker would. It runs code audits, black-box and white-box pentests, pull request reviews and continuous monitoring from one place, and its free plan includes a full SAST suite.

Where CodeQL runs queries against a database of your code, AISafe Labs agents build a model of your codebase and trace user input from where it enters to where it reaches a sensitive operation, with no query suites to pick or extend. That lets them find the flaws that depend on how your application is meant to behave, such as broken access control between teams and business-logic errors. A separate triage pass then confirms each finding, merges duplicates that share a root cause and shows its reasoning. Our AISafe Labs vs GitHub CodeQL comparison↗ runs both on the same codebase, if you want to see them side by side.

Key features

• Code Audit: AI agents review the whole repository and report evidence-backed findings with exact code locations, the path user input takes, and remediation guidance.
• Code Scan, free: SAST, AI SAST, dependency scanning, secrets detection, licence risk and IaC scanning on the free Basic plan, with no card required.
• Black-box and white-box pentests: agents probe your live application over HTTP and in a browser, and white-box tests combine source access with live confirmation, so findings come with evidence you can replay.
• Pull request security review: every pull request is reviewed for security defects, using what earlier audits learned about the project.
• Endpoint monitoring: AISafe re-runs the proof of each fixed finding against your live application on a schedule and alerts you when a fix regresses.
• Fix verification (beta): check a patched source revision against the original finding before you deploy it.
• Built for coding agents: findings, remediation guidance and fix verification are available through the AISafe API, so your own coding agent can read a finding, write the patch and start the verification itself.
• Fits your workflow: export findings to Jira or Linear, get alerts in Slack or Teams, and run AISafe on your own infrastructure if you need to.

Why AISafe Labs stands out as a GitHub CodeQL alternative

• There are no queries to write. AI agents read your entire application, and they find the access-control gaps, authentication and session flaws, token leaks, SSRF and race conditions that sit outside CodeQL's query suites.
• It tests the running application. CodeQL analyses source code only. AISafe Labs pentests confirm issues against your live application, so your team spends its time fixing instead of triaging.
• It covers the whole cycle. AISafe Labs gives remediation guidance, checks the fix and keeps watching for regressions, and it sends findings to Jira or Linear as well as working with your coding agent.

Pricing

The Basic plan is free and includes the full SAST suite. Pro starts at $40 a month and includes the same number of credits, which pay for code audits, pentests and continuous work; the price of a code audit depends on the size of the codebase and is shown before you start.

Ideal for: Teams that want more than a scanner: engineering and security teams that need to find logic and access-control flaws, test the running application, and close the loop from finding to verified fix, without moving to an enterprise contract.

#2 Semgrep

Semgrep is a static analysis tool that matches code against rules you can read and write. The Community Edition is free and open source and runs locally, and the Semgrep AppSec Platform adds cross-file analysis, dependency and secrets scanning, and AI triage and fixes.

Key features

• Rules written in a syntax that looks like the code they match
• Community Edition runs locally and in CI at no cost
• Semgrep Supply Chain for dependencies and Semgrep Secrets for credentials
• AI triage and AI Autofix pull requests on the platform
• Pull request comments and Jira Cloud sync
• A free platform edition for up to 10 contributors and 10 private repositories

Ideal for: Security teams that want transparent rules they can tune and extend, and are prepared to write and maintain custom rules for their own code.

#3 Snyk

Snyk is a developer security platform best known for dependency scanning. Snyk Open Source covers third-party packages, Snyk Code scans your own source code with its DeepCode AI engine, and the platform also covers containers and infrastructure as code, with DAST and AI pentesting on Enterprise plans.

Key features

• Snyk Open Source for known vulnerabilities in dependencies
• Snyk Code SAST, with pull request checks
• Container and IaC scanning
• Agent Fix patches for code issues
• API and web DAST and Evo AI pentesting on Enterprise
• A free plan with 5 projects and 100 Snyk Code tests a month

Ideal for: Teams that want one developer platform covering dependencies, containers and IaC as well as code, with fast feedback in the IDE and in CI.

#4 SonarQube

SonarQube is a code quality and code security platform built on rule-based static analysis. It is offered as SonarQube Cloud, paid self-hosted Server editions and a free self-hosted Community Build.

Key features

• Quality gates that block merges on reliability, maintainability and security issues
• Taint analysis for common injection flaws
• Secrets and IaC scanning
• AI CodeFix suggestions on paid plans
• Billing by lines of code, with no charge per scan
• Self-hosted Server editions and a free Community Build

Ideal for: Engineering organisations that care about code quality and technical debt as much as security, and want one quality gate across many repositories.

#5 Aikido

Aikido is an all-in-one application security platform that covers code, dependencies, cloud and runtime from one dashboard. It adds AI Code Analysis, where agents audit selected repositories, and AI pentests, both billed in credits.

Key features

• SAST, AI SAST, dependency, secrets and IaC scanning on the free plan
• AutoFix pull requests, with 10 a month on the free plan
• Cloud posture management for AWS, GCP and Azure
• Zen, an in-app firewall that blocks attacks at runtime
• AI Code Analysis and AI pentests, paid in credits
• Jira and Linear sync from the Basic plan

Ideal for: Teams that want one vendor for code, cloud and runtime security, with pentests available on demand.

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The right choice depends on what you need your security tooling to catch and how your team works. When you compare options, check:

• Which vulnerabilities matter most. If access control, authentication and business logic are your biggest risks, look for a tool that reasons about your application rather than one that only runs queries or rules.
• How much noise you can absorb. Ask each vendor how findings are validated, and run a trial on your own code to see how many are real.
• Whether you need to test the running application. Static analysis and live testing find different problems. Decide whether you need pentests, and which plan includes them.
• Where your work happens. If your team tracks work in Jira or Linear, or uses more than one source code host, check how findings reach the people who fix them.
• What it costs as you grow. Compare billing models: per committer, per contributor, per line of code or per credit, and which add-ons you need for private repositories.

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GitHub CodeQL is a strong choice for query-based scanning built into GitHub, and it is free for open-source projects. As your application grows, AISafe Labs helps you go further: AI agents that find the logic and access-control flaws queries miss, pentests that prove them on your live application, and fix verification that closes the loop.

You can start on the free Basic plan, which includes the full SAST suite, and run your first code audit in minutes. Start for free↗ or see the full AISafe Labs vs GitHub CodeQL comparison↗.