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sqlite3, Python pandas)# Quick SQL check (if dump is SQL)
sqlite3 truecaller.db "SELECT COUNT(*) FROM contacts;"
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- [b]~47M[/b] records (varies by version)
- [b]Core fields:[/b]
- `phone_number` (primary key, hashed/cleartext?)
- `name` (user-reported, often inaccurate)
- `country_code` (e.g., "US", "IN")
- `last_seen` (timestamp of activity)
- `trust_score` (TrueCaller’s internal rating, 0–100)
- `metadata` (device type, carrier, etc.)
- [b]Bonus:[/b] Some dumps include:
- `email` (if linked)
- `social_media` (if scraped)
- `geolocation` (IP-based, not always precise)
.sql or .db)-- Quick count check (replace 'truecaller' with your DB name)
SELECT COUNT(*) FROM contacts;
-- Dump all numbers to CSV (SQLite example)
.mode csv
.headers on
.output truecaller_numbers.csv
SELECT phone_number, name, country_code FROM contacts;
import pandas as pd
# Load CSV (adjust delimiter if needed)
df = pd.read_csv('truecaller_dump.csv', delimiter=';')
# Filter by country (e.g., US numbers)
us_numbers = df[df['country_code'] == 'US'][['phone_number', 'name']]
us_numbers.to_csv('us_numbers.csv', index=False)
import re
with open('dump.txt', 'r') as f:
data = f.read()
# Extract phone numbers (adjust pattern for your dump)
numbers = re.findall(r'(\+\d{1,3}[-\s]?\d{3}[-\s]?\d{3}[-\s]?\d{4})', data)
print(f"Found {len(numbers)} numbers.")
md5sum or sha256sum on the dump to ensure no corruption.bash
sha256sum truecaller_dump.sql
name → NULL).Lorem ipsum dolor sit amet, consectetur adipiscing elit. Curabitur egestas ex id lacus porttitor congue. Nam tristique massa quis eleifend ornare. Sed mattis est at ipsum.