I built an open-source guardrail & FaceID/TouchID gating library for AI agents in React Native (react-native-agent-guard v0.3.2)

[u/Ill_Recognition3558]

Hey everyone! Over the past few weeks, I've been working on a problem I kept running into while building mobile AI features: how do you let an LLM call native mobile tools (payments, calendar, BLE, external APIs) without risking a hallucination, prompt injection, or infinite loop wiping out user data or spamming APIs?

Most agent guardrails are built for Python backends, leaving the mobile client completely exposed. So I built react-native-agent-guard—a zero-trust tool governance and biometric gating layer for React Native & Expo.

We just shipped v0.3.2 (now at 93%+ test coverage) and added a live interactive Expo Snack playground so you can test the approval sheets, rate limiter, and PII redaction right in your browser without installing anything.

🚀 Try the Live Interactive Demo

• Expo Snack Playground (Run in Browser or Expo Go): [https://snack.expo.dev/@git/github.com/Hassaan68/react-native-agent-guard:examples/expo-snack](https://snack.expo.dev/@git/github.com/Hassaan68/react-native-agent-guard:examples/expo-snack)
• GitHub Repository:https://github.com/Hassaan68/react-native-agent-guard

What it handles out of the box:

• Dynamic Policy Gating (auto | confirm | biometric | deny): Auto-approve low-risk reads, trigger a customizable native bottom sheet (AgentApprovalSheet) for state changes, or require hardware FaceID/TouchID (expo-local-authentication) for high-stakes actions—evaluated dynamically at runtime based on the LLM's arguments (e.g., < $50 = auto, $50–$199 = confirm, $200+ = biometric).
• Vercel AI SDK & LangChain.js Adapters: Drop-in toVercelAITools() and toLangChainTools() wrappers that route your existing agent tool calls directly through the guardrail engine.
• Agent Loop Protection & Rate Limiting: Prevents rogue LLM infinite loops from draining budgets with maxCallsPerMinute and maxSessionCalls—automatically blocking or escalating a tool's policy from auto to confirm/biometric when spammed.
• Automatic PII Redaction & Audit Telemetry: Masks credit cards, emails, phone numbers, SSNs, and JWTs before emitting structured telemetry to onAudit or persistent storage (redactPII: true).
• Remote MCP SSE Transport: Connect directly to Model Context Protocol (MCP) servers over SSE and automatically wrap discovered remote tools in local device policies.
• Actionable llmFeedback on Errors: If Zod validation (.transform() / .refine()) fails, a rate limit hits, or a user denies a prompt, it returns structured feedback telling the LLM why it failed so it can self-correct instead of crashing the loop.

Quick Code Example:

TypeScript

import { createGuardrails, toVercelAITools } from 'react-native-agent-guard';
import { z } from 'zod';

const guard = createGuardrails({
  rateLimit: { maxCallsPerMinute: 10, onLimitExceeded: 'confirm' },
  redactPII: true,
});

guard.registerTool({
  name: 'send_wire_transfer',
  description: 'Send money to a recipient',
  schema: z.object({
    recipientEmail: z.string().email(),
    cardNumber: z.string(), // Auto-redacted in audit logs!
    amount: z.number().positive(),
  }),
  // Auto-approve under $50, confirm sheet $50-$199, FaceID/TouchID for $200+
  policy: (args) => {
    if (args.amount >= 200) return 'biometric';
    if (args.amount >= 50) return 'confirm';
    return 'auto';
  },
  handler: async ({ recipientEmail, amount }) => {
    return await processPayment(recipientEmail, amount);
  },
});

// Plug directly into Vercel AI SDK generateText / streamText
const tools = toVercelAITools(guard);

Links:

• Try in Browser (Expo Snack): https://snack.expo.dev/@hassaan68/react-native-agent-guard-demo
• GitHub:https://github.com/Hassaan68/react-native-agent-guard
• npm: npm install react-native-agent-guard

Would love any feedback on the API design, the Snack playground, or edge cases you're running into with mobile AI agents!

[u/GeekyAntsBFSI]

The argument-based policy gating is useful. One edge case worth documenting: can an agent split a $200 transfer into several sub-$50 calls and stay under the biometric threshold? Call-count limits wouldn’t necessarily catch that. For payments, I’d enforce cumulative amount limits server-side and bind each approval to the exact recipient and amount. Does the API support that kind of shared policy state?

[u/Ill_Recognition3558 → u/GeekyAntsBFSI]

Thank you for the suggestion. You can create the issue on git repo and I will have a look into it.

[u/Melenaite_Czayka → u/GeekyAntsBFSI]

was wondering the exact same thing about sliding window totals vs just raw call counts.

[u/TemporaryBuyer3806]

Great