Two readings on one pull request: GitHub AI Scan's own reading for the languages CodeQL doesn't cover, and Aevral adding its security reading of the same change through its PR review, live on install.
| Row | GitHub AI Scan | Aevral |
|---|---|---|
| Question it answers | Does this change introduce a vulnerability in a language CodeQL doesn't scan? | Who has access to what, and does this change widen it? |
| Stated job | AI-based scanning for vulnerabilities, including broken access control, in PHP, Shell/Bash, Terraform, Dockerfiles, JSP, and Blazor pull requests, per GitHub's documentation | Security reading of the PR diff: access control, business logic, injection, XSS, SSRF, path traversal, LLM integration |
| Where it runs | Code scanning check on the pull request; private repositories need GitHub Advanced Security, per GitHub's documentation | GitHub Check and inline comments, live on install; scans run from the console on a chosen SHA |
| Unit of work | A finding on the Conversation and Files changed tabs, labelled AI, with an optional suggested autofix, per GitHub's documentation | Up to five findings per review, grounded on the added lines; scan findings come as leads with evidence |
| Complementary? | Yes | Yes |
AI Scan runs on a pull request once code scanning and the repository's AI Scan setting are enabled, finding vulnerabilities on the pull request diff across nine categories, including broken access control, string injection, weak cryptography, and SSRF, in languages CodeQL's built-in analysis does not cover today, per GitHub's documentation.
Findings are advisory: they do not fail the code scanning check and cannot block a merge through a ruleset, and AI Scan does not run on pull requests from forks or pull requests opened by Dependabot.
The framing is addition, not replacement: AI Scan's own reading for the languages CodeQL doesn't cover, and Aevral adding its security reading of the same pull requests with Aevral's PR review, live on install.
Aevral also reads the repository snapshot at rest, for authorization, IDOR, and business-logic access control only. This page makes no claim about results on your code.
AI Scan
GitHub AI Scan is GitHub's own AI-based scanning engine, layered onto code scanning and generally available since 15 October 2026.
It finds vulnerabilities, including broken access control, in pull requests for languages and frameworks CodeQL's built-in analysis does not cover today: PHP, Shell/Bash, Terraform (HCL), Dockerfiles, JSP for Java, and Blazor for C#, per GitHub's documentation.
Aevral
Security review, handled. PR review, live on install, looks for access control, business logic, SQL and command injection, XSS, SSRF, path traversal, unsafe deserialization, token and session flaws, and LLM-integration risks on the diff. Paid PR plans are live in the console. The whole-repo scan is live and self-serve, and reads authorization, IDOR, and business-logic access control only. A finding is a lead with evidence, and a human decides. No patches are auto-applied.
This change simplifies an invoice-lookup method that used to load the invoice only after confirming it belonged to the caller's organization. The refactor collapses two lines into one call, and the ownership scope goes with them.
public function show($id){ $invoice = Invoice::where('organization_id', Auth::user()->organization_id)->findOrFail($id); $invoice = Invoice::findOrFail($id); return view('invoices.show', ['invoice' => $invoice]);}InvoiceController::show loads the invoice by id alone after the refactor; the organization_id scope that used to gate the query is gone, so a signed-in user can read another organization's invoice by changing the id in the URL.
Aevral is built to read a changed lookup for the ownership question first: whose row is this, and did the check that used to confirm it survive the change.
Keep AI Scan for the languages CodeQL doesn't cover; run Aevral for its own access-control and business-logic reading of the same pull requests, live on install.
No. AI Scan does its stated job and keeps doing it. Aevral runs alongside it with its own reading: its PR review, live on install, looks for access control, business logic, injection, XSS, SSRF, path traversal, and LLM-integration security on the pull requests it reviews, and its whole-repo scan reads access control and business logic across the repository at rest.
No. This page states each product's job and shows one worked example of Aevral's own reading. Results on your code depend on your code; evaluations belong to you.
Aevral is self-serve: install the GitHub App and log in to the console. The waitlist form is a launch-updates channel; joining does not reserve a price, access, or a contract.
More comparisons
The shorter version, at a glance: GitHub AI Scan and Aevral on the works-alongside page.
Primary sources: GitHub Docs: AI-powered security detections; GitHub Changelog: AI Scan for pull requests, generally available; Aevral PR security review; Aevral whole-repo scan.
Install the GitHub App and PR review starts on. Sign in with GitHub to connect it, then press Scan for the repository you already have.
For professional use. By installing, you confirm you can act for the account or organization that owns it, and you accept the Terms and DPA on its behalf.