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Architecture comparison

Choose the output model before the library

These projects overlap in a few checks, but they are built for different jobs: raw evidence, focused integrity helpers, runtime protection, or general device information.

Short answer

  • Choose React Native Device Risk Signals when you want a broad, typed, machine-readable raw event and your own backend policy.
  • Choose JailMonkey when a smaller focused API for common root, jailbreak, hook and mock-location checks matches your requirements.
  • Evaluate freeRASP when you need a runtime application self-protection product and its alert or response model.
  • Choose react-native-device-info for broad device and application metadata that is not primarily a risk telemetry contract.

Architecture-level comparison

ProjectPrimary jobOutput styleBest fit
React Native Device Risk SignalsTransparent device and runtime risk observationsOne typed event with independent success, skipped, timeout, and error outcomesTeams building their own ingestion, calibration, privacy controls, and backend policy
JailMonkeyFocused root, jailbreak and related environment checksIndividual helper results oriented around common detection questionsApplications needing a compact integrity-check surface
freeRASPRuntime application self-protectionThreat detection and notification or response integrationApplications evaluating an RASP lifecycle rather than only storing raw observations
react-native-device-infoGeneral device and application informationMany independent getters and hooksProduct features, compatibility checks, diagnostics, and general metadata
This is an architecture comparison, not a claim that one project detects every technique better. Detection catalogs and platform behavior change over time. Verify current upstream documentation and test the exact versions you plan to ship.

Questions to ask before choosing

  1. Do you need raw field-level evidence or a higher-level detection event?
  2. Must the package avoid all network traffic and vendor services?
  3. Do you need one backend event schema across Android and iOS?
  4. Which sensitive fields and permissions can your declared purpose justify?
  5. Will you calibrate physical-device behavior and own downstream policy?
  6. Do you need platform attestation in addition to local observations?

Combining libraries safely

It can be reasonable to use a general device metadata library, platform attestation, and a raw observation SDK together. Keep provenance explicit: store the source library, version, collection time, platform, verification status, and failure state for each value. Avoid copying everything into one ambiguous trusted-device object.

Do not collect duplicate sensitive fields without a documented purpose. Do not add persistent identifiers merely to join data across tools. The SDK does not calculate a risk score or make a blocking decision.

Review method and freshness

Last reviewed 2026-07-29 against the public project documentation linked above. This page compares documented product models, not unpublished implementations, bypass resistance, support quality, or commercial guarantees. Open an issue if a description is stale or materially incomplete.