Imported from jeremylongshore/tons-of-skills-marketplace (plugins/saas-packs/langfuse-pack/skills/langfuse-security-basics/SKILL.md). Install upstream with npx skills add jeremylongshore/tons-of-skills-marketplace --skill langfuse-security-basics. Copyright stays with the author (MIT).

Langfuse Security Basics

Overview

Security practices for Langfuse LLM observability: credential management, PII scrubbing before tracing, self-hosted hardening, data retention, and secret scanning.

Prerequisites

• Langfuse instance (cloud or self-hosted)
• API keys provisioned
• Understanding of data privacy requirements (GDPR, SOC2, HIPAA)

Instructions

Step 1: Credential Security

Langfuse uses two keys with different security profiles:

// Startup validation -- catch misconfigurations early
function validateLangfuseCredentials() {
  const publicKey = process.env.LANGFUSE_PUBLIC_KEY;
  const secretKey = process.env.LANGFUSE_SECRET_KEY;

  if (!publicKey || !secretKey) {
    throw new Error("LANGFUSE_PUBLIC_KEY and LANGFUSE_SECRET_KEY are required");
  }

  // Catch key swap (common mistake)
  if (secretKey.startsWith("pk-lf-")) {
    throw new Error("LANGFUSE_SECRET_KEY contains a public key (pk-lf-). Keys are swapped.");
  }

  if (publicKey.startsWith("sk-lf-")) {
    throw new Error("LANGFUSE_PUBLIC_KEY contains a secret key (sk-lf-). Keys are swapped.");
  }

  return { publicKey, secretKey };
}

// Use validated credentials
const { publicKey, secretKey } = validateLangfuseCredentials();

Key security rules:

• Public key (pk-lf-...): Identifies the project. Safe in client-side code.
• Secret key (sk-lf-...): Grants write access. Server-side only.
• Store in environment variables or secret manager -- never in source code.
• Rotate keys immediately if exposed in logs, git, or error reports.

Step 2: PII Scrubbing Before Tracing

Langfuse stores everything you send. Scrub PII from inputs and outputs before tracing.

// src/lib/pii-scrubber.ts

const PII_PATTERNS: Array<{ regex: RegExp; replacement: string }> = [
  { regex: /\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z]{2,}\b/gi, replacement: "[EMAIL]" },
  { regex: /\b\d{3}[-.]?\d{3}[-.]?\d{4}\b/g, replacement: "[PHONE]" },
  { regex: /\b\d{3}-\d{2}-\d{4}\b/g, replacement: "[SSN]" },
  { regex: /\b\d{4}[\s-]?\d{4}[\s-]?\d{4}[\s-]?\d{4}\b/g, replacement: "[CARD]" },
  { regex: /\b(?:sk|pk)-[a-zA-Z0-9_-]{20,}\b/g, replacement: "[API_KEY]" },
];

export function scrubPII(text: string): string {
  let scrubbed = text;
  for (const { regex, replacement } of PII_PATTERNS) {
    scrubbed = scrubbed.replace(regex, replacement);
  }
  return scrubbed;
}

export function scrubObject(obj: any): any {
  if (typeof obj === "string") return scrubPII(obj);
  if (Array.isArray(obj)) return obj.map(scrubObject);
  if (typeof obj === "object" && obj !== null) {
    const result: Record<string, any> = {};
    for (const [key, value] of Object.entries(obj)) {
      result[key] = scrubObject(value);
    }
    return result;
  }
  return obj;
}

// Usage with tracing
import { observe, updateActiveObservation } from "@langfuse/tracing";
import { scrubPII, scrubObject } from "./lib/pii-scrubber";

const tracedChat = observe(async (userMessage: string) => {
  // Scrub input before tracing
  updateActiveObservation({ input: scrubPII(userMessage) });

  // Send original to LLM (unscrubbed)
  const response = await callLLM(userMessage);

  // Scrub output before tracing
  updateActiveObservation({ output: scrubPII(response) });
  return response;
});

Step 3: Self-Hosted Hardening

# docker-compose.yml -- production-hardened
services:
  langfuse:
    image: langfuse/langfuse:latest
    environment:
      # Disable open registration
      - AUTH_DISABLE_SIGNUP=true
      # Enforce SSO for your domain
      - AUTH_DOMAINS_WITH_SSO_ENFORCEMENT=company.com
      # Least-privilege default role
      - LANGFUSE_DEFAULT_PROJECT_ROLE=VIEWER
      # Encrypt data at rest
      - ENCRYPTION_KEY=${ENCRYPTION_KEY}
      # Data retention (days)
      - LANGFUSE_RETENTION_DAYS=90
      # Database
      - DATABASE_URL=${DATABASE_URL}
      - NEXTAUTH_SECRET=${NEXTAUTH_SECRET}
      - SALT=${SALT}

Step 4: Git Secret Scanning

Prevent Langfuse keys from being committed:

# .gitignore
.env
.env.local
.env.production

# .github/workflows/secret-scan.yml
name: Secret Scan
on: [push, pull_request]
jobs:
  scan:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Check for Langfuse keys
        run: |
          if grep -rn "sk-lf-[a-zA-Z0-9]" --include="*.ts" --include="*.js" --include="*.py" .; then
            echo "ERROR: Secret key found in source code!"
            exit 1
          fi

Step 5: Scoped API Keys and Least Privilege

// Create separate API keys per service/environment
// In Langfuse dashboard: Settings > API Keys

// Backend API service -- full write access
// LANGFUSE_SECRET_KEY=sk-lf-backend-...

// Analytics worker -- read-only access
// Use Langfuse API with read-only key
// LANGFUSE_SECRET_KEY=sk-lf-readonly-...

// CI/CD pipeline -- scoped to test project
// LANGFUSE_SECRET_KEY=sk-lf-ci-test-...
// LANGFUSE_PUBLIC_KEY=pk-lf-ci-test-...

Security Checklist

Error Handling

Output

Produce a security checklist with an accountable owner for each control: credential storage and rotation, trace-data minimization, retention, access roles, self-hosting hardening, and CI secret scanning. The deliverable should identify whether each control is verified in the deployment environment rather than merely present in source code.

Examples

For a production deployment, keep the Langfuse write credential in the platform's secret store, inject it only into the service that emits traces, and use a separate restricted credential for CI verification. Before enabling a new trace field, test it with representative data and confirm that identifiers and free-form text are scrubbed or omitted according to the retention policy.

Resources

• Langfuse Data Security
• Self-Hosting Configuration
• Headless Initialization