Keygraph vs GitHub Advanced Security
Rather than predicting whether a vulnerability is exploitable, Keygraph proves it by running a working exploit against the application, no matter where the code lives: GitHub, GitLab, Bitbucket, or your own infrastructure.
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 the same class of static detection to any source host and any environment, then adds the step scanners cannot perform: vulnerability validation. It confirms each real vulnerability by executing a working exploit against the running application, and after a fix lands, re-executes the same exploit to verify the issue is genuinely closed.
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.
GHAS
GitHub-native
Excellent within its own platform (a separate product covers Azure DevOps). Code on any other host is out of reach, and so is risk that only appears at runtime.
Keygraph
org-wide
Any source host, any environment, plus the live system itself. One platform covers all of it, in Keygraph's cloud or inside your own network.
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 a plausible guess; both still leave a human to work out what an attacker could actually do. Keygraph supplies that answer as evidence: a working exploit that demonstrates the finding, and a re-run of the same exploit that demonstrates the fix.
GHAS and Keygraph both identify vulnerabilities through static analysis. The difference is everything after identification: validating that a finding is exploitable, driving remediation, and re-running the exploit to confirm the fix held. Scanning stops at identification; penetration testing is the validation step.
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.
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.
| Capability | Keygraph | GitHub Advanced Security |
|---|---|---|
| Static analysis | ||
| Agentic SASTReasoning at every node | ✓CPG plus LLM reasoning at every node | PartialCodeQL dataflow analysis, plus an AI scan for code CodeQL does not cover (AI security detections on pull requests, public preview since July 2026; needs a Copilot license) |
| SCA + reachabilityAdvisory to executable call chain | ✓proven-executable call chains; cuts 70 to 90% of noise | PartialDependabot alerts by version; no reachability analysis in current Dependabot documentation |
| Secret scanningCatch leaked credentials | ✓40+ types + LLM context pass | ✓scanning + push protection (blocks the commit) |
| 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 pentest 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 Autofix drafts a fix; agentic autofix (preview) re-runs the scan to confirm the alert clears; no runtime re-test |
| 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; Keygraph never receives your source or scan results; inference goes straight to the model endpoint you configure, so a full air-gap needs a local model endpoint | 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, OpenAI, xAI, AWS Bedrock, an OpenAI- or Anthropic-compatible gateway such as a self-hosted LiteLLM, or a local model via Ollama, vLLM, or LM Studio), with usage tracking | ✕code scanning AI (Autofix, AI detections) runs on GitHub-hosted models; Copilot's enterprise BYOK covers Chat, CLI, and IDEs, not code scanning |
| 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, 48k+ 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 →
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 September 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.
Prediction vs proof
GHAS output is an assessment of code that was never run: an alert means a vulnerability looks reachable; a fix means it might resolve the issue. 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.
Detection, then closure
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.
The running app
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.
Not only on GitHub
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, in Keygraph's cloud or inside your own perimeter.
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; hiring humans to do that costs $10k to $30k a year and leaves the rest of the year untested.
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 moreThe Keygraph platform is built on Shannon, our open-source AI pentester (AGPL-3.0, 48k+ stars), so you can read its code and run it on your own app before you buy. GHAS's CodeQL engine is proprietary; only its queries are open source.
Learn moreClaims about GitHub Advanced Security on this page are drawn from the primary references below, verified September 18, 2026.
Run the Keygraph platform against your own environment and judge the evidence: working exploits against your running application, and fixes verified closed by re-running the same exploit.