Keygraph: the AI-native
GitHub Advanced Security replacement
GHAS is built directly into GitHub, which is both its greatest strength and its main constraint. Because it lives inside the platform, turning it on covers your GitHub repositories with essentially no integration work. The tradeoff is scope: anything outside GitHub's platforms, including the running application itself, falls outside what GHAS can see. Security shouldn't depend on which platform your code happens to live on, and a finding shouldn't ship as a hypothesis. Keygraph brings that same depth of detection to any source host and any environment, then goes further: it proves each real vulnerability by running a working exploit against it, and once a fix is in place, runs that exploit again to confirm the issue is genuinely closed.
Security that lives where your code lives, until it lives elsewhere.
Coverage that ships with the platform stops at the platform. Most companies' code doesn't: there are other source hosts, repos that arrive with an acquisition, and the application your customers actually run. Here is what each side can reach.
Inside GitHub's walls
Across everything you run
CodeQL and Copilot Autofix are excellent. They still don't run the attack.
CodeQL is genuinely strong: it reasons about data flow and catches taint and cross-procedure issues simpler scanners miss. Copilot Autofix suggests a patch right in the pull request. That is a fast, polished detect-and-suggest loop, and GitHub keeps extending it.
But none of it ever touches the running application. An alert is a strong lead, and a suggested patch is a plausible one; both still leave a human to establish what an attacker could actually do. Keygraph supplies that step as evidence: a working exploit that demonstrates the finding, and a re-run of the same exploit that demonstrates the fix.
Both find. Only one proves and closes the loop.
GHAS and Keygraph both find vulnerabilities through static analysis. The difference is everything after detection: proving the finding is really exploitable, driving the fix, and re-running the exploit to prove the fix held.
GHAS finds and can draft a fix PR; proving the vulnerability and verifying the fix held stay with your team. Keygraph runs all four stages end to end.
Static detection of likely vulnerabilities. GHAS scans GitHub repos with CodeQL, Dependabot, and secret scanning; Keygraph runs the same class of detection on any source host, plus IaC and container analysis.
Keygraph exploits the vulnerability against the running app and ships a reproducible PoC. A GHAS alert is a well-informed prediction about code that was never run, not a verified exploit.
Both can open a fix PR: Copilot Autofix drafts a contextual patch, and Keygraph writes one too. The difference is what comes next, and only Keygraph drives it to a verified close rather than leaving the check to you.
Keygraph re-runs the original exploit after the fix to confirm the vulnerability itself is gone, not just that the alert stopped firing, then rolls it into the system of record.
How Keygraph compares to GHAS
| Capability | Keygraph | GitHub Advanced Security |
|---|---|---|
| Static analysis | ||
| AI-native SASTReasoning at every node | ✓CPG plus LLM reasoning at every node | PartialCodeQL dataflow analysis; not LLM-based |
| SCA + reachabilityAdvisory to executable call chain | ✓proven-executable call chains; cuts 70 to 90% of noise | PartialDependabot alerts by version; reachability only in a Python beta |
| Secret scanningCatch leaked credentials | ✓40+ types + LLM context pass | ✓scanning + push protection (blocks the commit) |
| IaC / container scanningConfig-layer coverage | ✓included | Partialvia CodeQL / third-party Actions |
| Dynamic testing & exploitation | ||
| Pentest of the running appAttacks at machine scale | ✓autonomous agents, real browser | –DAST needs a third-party tool |
| Black-box testingExternal attacker view, zero knowledge | ✓zero-knowledge agents attack from outside, no code access | –static analysis only |
| Gray-box testingBlack-box plus provided context and steerability | ✓optional credentials, focus areas, business context, and OpenAPI specs steer the agents | – |
| Exploit validation / PoCProof, not theory | ✓every finding proven, reproducible | –alerts to triage |
| Business-logic testingIDOR, authz, tenant isolation | ✓IDOR, authz, tenant isolation | –only shallow static queries; no runtime exploit validation |
| Correlation & remediation | ||
| Static-dynamic correlationSource map directs the attack | ✓attacks with source knowledge | – |
| Verified-patch remediationFix, prove, labeled PR | ✓fix → dynamic re-test → labeled PR | PartialCopilot can open a draft fix; you verify it resolved the alert |
| Findings system of recordOne deduplicated record | ✓one canonical, deduplicated findings list with SLA tracking, bidirectional Jira | Partialsecurity overview and Jira sync; no cross-vendor dedup |
| Deployment & trust | ||
| Runs air-gappedEngine runs in your perimeter | ✓on-prem or self-hosted in your own infrastructure; source, scan results, and AI inference never leave your network | PartialEnterprise Server self-hosts, but AI features call GitHub's managed cloud (third-party models) |
| BYOK: model traffic stays yoursYour key, your gateway | ✓your own key, model, or AI gateway (Anthropic, AWS Bedrock, Google Vertex AI, or an Anthropic-compatible endpoint), including a self-hosted LiteLLM gateway, with usage tracking | –AI runs on GitHub's managed cloud; no BYO key or model |
| SSO / SCIM / RBAC / auditEnterprise access controls | ✓ | ✓ |
| Compliance evidenceAudit-ready reporting | ✓PCI, DORA, FedRAMP, …; SOC 2 Type II | Partialoverview + exportable alerts |
| Open source & pricing | ||
| Open sourceRead it before you buy | ✓Shannon, AGPL-3.0, 44k+ stars | PartialCodeQL queries are MIT; the CLI and engine are proprietary, and private or closed-source use needs a paid GitHub Code Security license |
| Pricing (public, sourced)What you actually pay | from $50 / developer / mo; Shannon free | $19 + $30 / active committer / mo |
Swipe to compare →
Compare security budgets, not seat prices.
A per-committer scanner license next to a platform seat is the wrong comparison. The real one is a single platform against a scanner plus the periodic pentest it still needs, plus the 364-day gap between them. GHAS is $19 per committer for Secret Protection and $30 for Code Security.
An "active committer" pushed to a GHAS-enabled repo in the last 90 days, deduplicated across the org. Pricing sources: GitHub Secret Protection $19 + Code Security $30 per active committer/month (github.com/security/plans, as of June 2026). A third-party web-application penetration test runs an industry range of $10,000 to $30,000 per engagement (TCM Security, Redfox Security, DeepStrike, 2026). Keygraph Pro from $50/developer/month, a floor price, computed here at the same headcount. Estimates for comparison only; actual costs vary by scope.
Four things a scanner leaves on the table
An alert is a hypothesis, not a verdict
GHAS output is an assessment of code that was never run: an alert means a vulnerability looks reachable, a fix means it might resolve it. Keygraph proves it with an exploit run against the live app and attaches the PoC, so a finding is a fact, not a prediction your team still has to triage.
Finding it is the start, not the finish
Copilot Autofix can draft a patch and re-scan, but that only confirms the pattern no longer matches, and it leaves you to verify the fix. Keygraph writes the fix and re-runs the original exploit to prove the vulnerability is actually gone, find → prove → fix → verify in one place, so the finding that goes in is the closure that comes out.
Risk that never shows up in static analysis
An IDOR, a broken authorization check, a tenant-isolation flaw: these are properties of the running application, and a static scanner has only shallow queries for them and never exploits them at runtime. Keygraph tests business logic against the live app, the layer a scanner cannot reach.
All your code, not one vendor's corner of it
Most enterprises run more than one source host: GitLab, Bitbucket, acquisitions, on-prem. GHAS secures GitHub, and as a separate product Azure DevOps, and nothing else, even when self-hosted. Keygraph is SCM-agnostic, so the same proof and the same loop cover all of them, inside your own perimeter.
Get more with Keygraph
Keygraph's agentic pentester attacks your running app in a real browser and ships only proven, reproducible exploits. Run it as often as you choose, on every release, nightly, or on demand; with BYOK there is no per-scan metering. GHAS scans every push but never pentests the running app, and the human pentest that does costs $10k to $30k a year and leaves a 364-day gap.
Learn moreKeygraph attacks the running app with full source knowledge and correlates both stages into one result per vulnerability. GHAS has no running-app testing to correlate its alerts against.
Learn moreKeygraph writes the fix and re-runs the original exploit to prove the vulnerability is actually gone, then opens a labeled PR. GHAS can open a draft Copilot fix and re-scan, but that only confirms the alert stopped firing, and it leaves you to verify the fix before you merge.
Learn moreKeygraph's engine is Shannon, AGPL-3.0 with 44k+ stars, so you can read exactly how it works. GHAS's CodeQL engine is proprietary; only its queries are open source.
Learn moreFAQ
Does Keygraph replace GitHub Advanced Security?
Does GitHub Advanced Security do penetration testing?
Is Copilot Autofix the same as Keygraph's remediation?
Where do Keygraph findings surface for developers?
What happens to findings Keygraph can't exploit?
Does my source code or model traffic leave my environment?
How is Keygraph priced compared to GHAS's per-committer model?
What is Shannon, and is it really free?
We're on Azure DevOps, does this change?
Is CodeQL open source?
Don't take our word for it,
try out Keygraph for yourself!
Run Keygraph against your own environment and judge the results: working exploits against your running app, and fixes proven closed.
Sources
Claims about GitHub Advanced Security on this page are drawn from the primary references below, verified June 8, 2026.
- GitHub Docs, About GitHub Advanced Security. https://docs.github.com/en/get-started/learning-about-github/about-github-advanced-security
- GitHub Changelog, Introducing GitHub Secret Protection and GitHub Code Security (per-active-committer pricing, $19 + $30), March 4, 2025. https://github.blog/changelog/2025-03-04-introducing-github-secret-protection-and-github-code-security/
- GitHub Docs, Billing for GitHub Advanced Security (active-committer definition). https://docs.github.com/en/billing/concepts/product-billing/github-advanced-security
- GitHub Changelog, Advanced Security for GitHub Team organizations, April 1, 2025. https://github.blog/changelog/2025-04-01-github-advanced-security-is-here-for-github-team-organizations/
- GitHub Docs, Responsible use of Copilot Autofix for code scanning. https://docs.github.com/en/code-security/responsible-use/responsible-use-autofix-code-scanning
- GitHub Docs, About Dependabot alerts. https://docs.github.com/en/code-security/dependabot/dependabot-alerts/about-dependabot-alerts
- Microsoft Learn, Billing for GitHub Advanced Security for Azure DevOps. https://learn.microsoft.com/en-us/azure/devops/repos/security/github-advanced-security-billing?view=azure-devops
- GitHub Docs, Hosting of AI models for GitHub Copilot. https://docs.github.com/en/copilot/reference/ai-models/model-hosting
- CodeQL repository README (queries MIT-licensed; CLI licensed separately; commercial license required for closed-source code). https://github.com/github/codeql
- CodeQL CLI binaries, license (the proprietary CodeQL Terms and Conditions). https://github.com/github/codeql-cli-binaries/blob/main/LICENSE.md
- GitHub Docs, About the CodeQL CLI (free on public repos; private repos require a GitHub Code Security license). https://docs.github.com/en/code-security/codeql-cli/getting-started-with-the-codeql-cli/about-the-codeql-cli
- GitHub Changelog, Dependabot alerts show vulnerable function calls (Python beta) (reachability limited to a Python beta). https://github.blog/changelog/2022-04-14-dependabot-alerts-show-vulnerable-function-calls-python-beta/
- CodeQL query help, Missing function level access control (CWE-862/285/284; shallow static access-control queries). https://codeql.github.com/codeql-query-help/csharp/cs-web-missing-function-level-access-control/
- GitHub Blog, Third-party code scanning tools, IaC and container scanning (IaC/container via CodeQL or third-party Actions). https://github.blog/2020-10-07-announcing-third-party-code-scanning-tools-infrastructure-as-code-and-container-scanning/
- GitHub Changelog, Security overview dashboards (security overview as the findings surface). https://github.blog/changelog/2024-07-19-security-overview-dashboards-secret-scanning-metrics-and-enablement-trends-reports-are-now-generally-available/
- GitHub Changelog, CSV exports for security alerts on the security overview dashboard (exportable alerts). https://github.blog/changelog/2024-08-06-csv-exports-for-security-alerts-on-the-organization-level-security-overview-dashboard/
- GitHub Docs, Configuring SAML single sign-on for your enterprise (SSO/SCIM/RBAC/audit). https://docs.github.com/en/enterprise-cloud@latest/admin/managing-iam/using-saml-for-enterprise-iam/configuring-saml-single-sign-on-for-your-enterprise
- GitHub Docs, Triaging code scanning alerts in pull requests (alerts land in the PR). https://docs.github.com/en/code-security/code-scanning/managing-code-scanning-alerts/triaging-code-scanning-alerts-in-pull-requests
- GitHub Blog, CodeQL zero to hero part 1, the fundamentals of static analysis (CodeQL flags potential issues; it does not run the attack). https://github.blog/developer-skills/github/codeql-zero-to-hero-part-1-the-fundamentals-of-static-analysis-for-vulnerability-research/
- CodeQL, semantic code analysis engine (mature dataflow analyzer with an extensible query library). https://codeql.github.com/
- GitHub, Security plans and pricing (Secret Protection $19 + Code Security $30 per active committer/month). https://github.com/security/plans
- GitHub, GHAS Jira integration (synchronize Code Scanning alerts to Jira issues). https://github.com/github/ghas-jira-integration
- Microsoft DevBlogs, GitHub Secret Protection and Code Security for Azure DevOps (legacy $49 bundle split into $19 + $30 for new customers). https://devblogs.microsoft.com/devops/github-secret-protection-and-github-code-security-for-azure-devops/
- DeepStrike, Penetration testing cost (separate third-party engagement, $10,000 to $30,000 range). https://deepstrike.io/blog/penetration-testing-cost