replit-data-handling
Implements secure data handling, redaction, and privacy compliance patterns for Replit storage services.
Install
mkdir -p .claude/skills/replit-data-handling && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/7582" && unzip -o skill.zip -d .claude/skills/replit-data-handling && rm skill.zipInstalls to .claude/skills/replit-data-handling
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Implement secure data handling on Replit: PostgreSQL, KV Database, ObjectKey capabilities
- →Implement secure PostgreSQL connection patterns using parameterized queries
- →Configure Key-Value database for session management and caching with TTL
- →Manage file uploads and storage using Replit Object Storage
- →Redact sensitive fields from logs and application responses
- →Validate user input using Zod schemas
How it works
The skill provides patterns for interacting with Replit's storage systems while enforcing security through parameterized SQL queries, field redaction in logs, and schema-based input validation. It guides developers to use specific APIs like @replit/database and @replit/object-storage for data persistence.
Inputs & outputs
When to use replit-data-handling
- →Implementing PII redaction logic
- →Configuring data retention policies
- →Securing PostgreSQL connection patterns
- →Ensuring GDPR/CCPA compliance in Replit-hosted apps
About this skill
Replit Data Handling
Overview
Manage application data securely across Replit's three storage systems: PostgreSQL (relational), Key-Value Database (simple cache/state), and Object Storage (files/blobs). Covers connection patterns, security, data validation, and choosing the right storage for each use case.
Prerequisites
- Replit account with Workspace access
- PostgreSQL provisioned in Database pane (for SQL use cases)
- Understanding of Replit Secrets for credentials
Storage Decision Matrix
| Need | Storage | API | Limits |
|---|---|---|---|
| Structured data, queries | PostgreSQL | pg npm / psycopg2 | Plan-dependent |
| Simple key-value, cache | Replit KV Database | @replit/database / replit.db | 50 MiB, 5K keys |
| Files, images, backups | Object Storage | @replit/object-storage | Plan-dependent |
Instructions
Step 1: PostgreSQL — Secure Connection
// src/services/database.ts
import { Pool, PoolConfig } from 'pg';
function createPool(): Pool {
if (!process.env.DATABASE_URL) {
throw new Error('DATABASE_URL not set. Create a database in the Database pane.');
}
const config: PoolConfig = {
connectionString: process.env.DATABASE_URL,
ssl: { rejectUnauthorized: false }, // Required for Replit PostgreSQL
max: 10,
idleTimeoutMillis: 30000,
connectionTimeoutMillis: 5000,
};
const pool = new Pool(config);
// Log errors without exposing connection string
pool.on('error', (err) => {
console.error('Database pool error:', err.message);
// Never: console.error(err) — may contain credentials
});
return pool;
}
export const pool = createPool();
// Parameterized queries ONLY — never string concatenation
export async function findUser(userId: string) {
// GOOD: parameterized
const result = await pool.query(
'SELECT id, username, created_at FROM users WHERE id = $1',
[userId]
);
return result.rows[0];
// BAD: SQL injection risk
// pool.query(`SELECT * FROM users WHERE id = '${userId}'`)
}
Dev vs Production databases:
Replit auto-provisions separate databases:
- Development: used when running in Workspace ("Run" button)
- Production: used when accessed via deployment URL
View in Database pane:
- Development tab: test data, iterate freely
- Production tab: live customer data, handle with care
Both use the same DATABASE_URL — Replit routes automatically.
Step 2: Key-Value Database — Session & Cache
Node.js:
// src/services/cache.ts
import Database from '@replit/database';
const db = new Database();
// Cache with TTL using KV
export async function cacheGet<T>(key: string): Promise<T | null> {
const entry = await db.get(key) as { value: T; expiresAt: number } | null;
if (!entry) return null;
if (Date.now() > entry.expiresAt) {
await db.delete(key);
return null;
}
return entry.value;
}
export async function cacheSet<T>(key: string, value: T, ttlMs: number): Promise<void> {
await db.set(key, { value, expiresAt: Date.now() + ttlMs });
}
// Session storage
export async function setSession(sessionId: string, data: any): Promise<void> {
await db.set(`session:${sessionId}`, {
...data,
createdAt: Date.now(),
});
}
export async function getSession(sessionId: string): Promise<any> {
return db.get(`session:${sessionId}`);
}
// Clean up expired sessions
export async function cleanSessions(): Promise<number> {
const keys = await db.list('session:');
let cleaned = 0;
const oneDay = 24 * 60 * 60 * 1000;
for (const key of keys) {
const session = await db.get(key) as any;
if (session && Date.now() - session.createdAt > oneDay) {
await db.delete(key);
cleaned++;
}
}
return cleaned;
}
// Limits reminder: 50 MiB total, 5,000 keys, 1 KB/key, 5 MiB/value
Python:
from replit import db
import json, time
# Dict-like API
db["settings"] = {"theme": "dark", "lang": "en"}
settings = db["settings"]
# List keys by prefix
user_keys = db.prefix("user:")
# Delete
del db["old_key"]
# Cache pattern with TTL
def cache_set(key: str, value, ttl_seconds: int):
db[f"cache:{key}"] = {
"value": value,
"expires_at": time.time() + ttl_seconds
}
def cache_get(key: str):
entry = db.get(f"cache:{key}")
if not entry or time.time() > entry["expires_at"]:
return None
return entry["value"]
Step 3: Object Storage — File Uploads
Node.js:
// src/services/files.ts
import { Client } from '@replit/object-storage';
import express from 'express';
const storage = new Client();
const router = express.Router();
// File upload endpoint
router.post('/upload', express.raw({ limit: '10mb', type: '*/*' }), async (req, res) => {
const userId = req.headers['x-replit-user-id'] as string;
if (!userId) return res.status(401).json({ error: 'Login required' });
const filename = req.headers['x-filename'] as string || `file-${Date.now()}`;
const path = `uploads/${userId}/${filename}`;
await storage.uploadFromBytes(path, req.body);
res.json({ path, size: req.body.length });
});
// File download
router.get('/files/:userId/:filename', async (req, res) => {
const path = `uploads/${req.params.userId}/${req.params.filename}`;
try {
const { value } = await storage.downloadAsBytes(path);
res.send(Buffer.from(value));
} catch {
res.status(404).json({ error: 'File not found' });
}
});
// List user files
router.get('/files/:userId', async (req, res) => {
const objects = await storage.list({ prefix: `uploads/${req.params.userId}/` });
res.json(objects.map(o => ({ name: o.name })));
});
export default router;
Python:
from replit.object_storage import Client
storage = Client()
# Upload
storage.upload_from_text("reports/daily.json", json.dumps(report))
storage.upload_from_filename("backups/db.sql", "/tmp/dump.sql")
# Download
content = storage.download_as_text("reports/daily.json")
storage.download_to_filename("backups/db.sql", "/tmp/restore.sql")
# Check existence
if storage.exists("reports/daily.json"):
storage.delete("reports/daily.json")
Step 4: Data Sanitization
// src/middleware/sanitize.ts
import { z } from 'zod';
// Validate all input with Zod schemas
const UserInputSchema = z.object({
name: z.string().min(1).max(100).trim(),
email: z.string().email().toLowerCase(),
message: z.string().max(5000).trim(),
});
export function validateInput<T>(schema: z.ZodType<T>, data: unknown) {
const result = schema.safeParse(data);
if (!result.success) {
return { valid: false as const, errors: result.error.flatten().fieldErrors };
}
return { valid: true as const, data: result.data };
}
// Strip sensitive fields from responses
export function sanitizeUser(user: any) {
const { password_hash, email, phone, ...safe } = user;
return safe;
}
// Safe logging — redact sensitive fields
export function safeLog(message: string, data?: any) {
if (!data) return console.log(message);
const redacted = JSON.parse(JSON.stringify(data, (key, value) => {
if (['password', 'token', 'secret', 'api_key', 'ssn'].includes(key.toLowerCase())) {
return '[REDACTED]';
}
return value;
}));
console.log(message, redacted);
}
Step 5: Error Response Safety
// Never expose internal details in production
app.use((err: Error, req: any, res: any, next: any) => {
safeLog('Error:', { message: err.message, path: req.path });
const isProduction = process.env.NODE_ENV === 'production';
res.status(500).json({
error: isProduction ? 'Internal server error' : err.message,
...(isProduction ? {} : { stack: err.stack }),
});
});
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| DATABASE_URL undefined | PostgreSQL not created | Provision in Database pane |
KV Max storage exceeded | Over 50 MiB | Migrate to PostgreSQL or Object Storage |
| Object Storage 403 | Bucket not provisioned | Create in Object Storage pane |
| SQL injection | String concatenation | Use parameterized queries ($1, $2) |
| PII in logs | Full object logging | Use safeLog() with field redaction |
Resources
Next Steps
For team access control, see replit-enterprise-rbac.
When not to use it
- →Storing more than 50 MiB in the KV database
- →Using string concatenation for SQL queries
- →Logging raw objects containing passwords or tokens
Prerequisites
Limitations
- →KV database is limited to 50 MiB and 5,000 keys
- →KV database values are limited to 5 MiB per value
How it compares
Unlike manual implementation, this skill provides standardized security wrappers and storage-specific connection patterns to prevent common vulnerabilities like SQL injection and PII leakage.
Compared to similar skills
replit-data-handling side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| replit-data-handling (this skill) | 1 | 26d | Review | Intermediate |
| supabase-rls-policy-generator | 11 | 9mo | No flags | Advanced |
| sqlmap-database-penetration-testing | 4 | 6mo | Review | Advanced |
| data-safety-auditor | 3 | 7mo | No flags | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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