What we still need to verify : 5 points in this profile are not yet confirmed against vendor documentation.
- Confirm the analysis engine: whether findings come from static analysis, a model, or both, and how fixes are generated and validated
- Confirm which CI/CD systems and source hosts are supported, the integrations list is currently empty
- Confirm the boundary between the free beta and paid plans
- Confirm whether scanning covers cross-platform frameworks such as React Native and Flutter, or native code only
- Confirm whether findings map to a published standard such as OWASP MASVS or the Mobile Top 10
Treat these points as unconfirmed. They are open items in the catalog's verification queue, and this note stays until each is checked against the vendor's documentation.
What it does
Nandee scans mobile application source code and reports vulnerabilities specific to the mobile platforms rather than generic web findings. The stated focus is the classes that dominate real mobile assessments: insecure local data storage, improper platform API usage, and insecure network communication. Android and iOS are both supported.
What distinguishes it from a conventional mobile scanner is that the output is meant to be a fix rather than a finding. The platform generates remediation suggestions written against the scanned codebase, so a developer receives a proposed code change instead of a rule identifier and a documentation link. That is a meaningful difference in mobile work specifically, where the population of developers who can act on a raw static analysis finding is smaller than on the server side, and where the remediation for something like a keychain or SharedPreferences misuse is usually a small, well-defined edit that a model can draft competently. Delivery is SaaS, with a free beta tier covering a single application and integration into build and release workflows.
Where it fits
This belongs at the pull request and pre-release stage, run against the mobile repository the way you would run any static scanner. The intended operator is the mobile developer rather than a security engineer, which matches the tool's emphasis on proposed fixes over triage workflow. It complements rather than replaces runtime hardening and manual mobile assessment, since source scanning does not observe what the shipped binary does on a compromised device.
Strengths
- Mobile-specific vulnerability classes rather than a general-purpose engine with a mobile rule pack bolted on.
- Fix generation targets the real bottleneck in mobile AppSec programs, which is developer remediation capacity rather than finding volume.
- Covers both platforms from one product, which small mobile teams usually have to assemble from separate tools.
- A free single-app tier makes evaluation cheap and removes the usual procurement barrier to trying it.
Limitations
- Early stage product with a short track record. Detection depth against established mobile scanners is unproven and worth measuring on your own codebase before relying on it.
- AI-generated fixes require human review. A suggested patch that looks correct and subtly is not is a worse outcome than an unfixed finding, so treat suggestions as drafts.
- Source-level analysis cannot see what a packaged binary does at runtime, so it does not cover the tampering, hooking and instrumentation risks that mobile apps face in the field.
- Integration coverage is not yet documented in detail, which matters if you need it to sit in a specific CI system.
Who it suits
A reasonable fit for small and mid-size mobile teams, particularly the Series A stage companies in fintech, health and consumer that ship on both platforms and have no dedicated mobile security engineer. The free tier makes it low-risk to trial. Less suitable for organizations that need a mature, benchmarked scanner with an established compliance and audit trail, or that require on-premise deployment.
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