AI features
Mobile Security’s static checks run with no AI. Adding an AI provider turns on a set of higher-signal, natural-language actions on top of a scan.
Run a scan first (AI actions work from a scanned project’s findings), then:
- Deep scan — the AI reviews the app context (pubspec, AndroidManifest, Info.plist, and truncated Dart source) for high-signal issues the regex checks miss: insecure data flow, auth/session logic, injection, unsafe platform channels, crypto misuse, WebView-bridge abuse, IDOR, and more. Its findings are merged into the record and count toward the grade.
- Explain a finding — plain-language why it’s a risk, a concrete minimal fix, and how to verify it, for any single finding.
- Propose a patch — a concrete fix for one finding as a unified
diff(or exact before/after code), grounded in the file and line context. - Threat model — a concise STRIDE threat model (assets, attack surface, a STRIDE table, and a fix-first list) built from the scan’s failing findings.
- Executive summary — an executive risk briefing: overall posture, the top 3 risks with business impact, and a prioritized fix-first order for the week.
All of these call your configured provider directly; nothing is sent to a Batta/Mobile-DevTools server. See Privacy & storage.