Job market is crazy so i decided to hop on the hackattic.com challenge

Nkwochamaureen — Mon, 13 Apr 2026 01:59:49 +0000

# Redis RDB Binary Parser & Data Extractor

📌 Project Overview

This project is a high-performance binary parser built to interact with Redis RDB (Redis Database) snapshots. The goal was to programmatically fetch a raw, base64-encoded RDB dump from an API, "heal" a corrupted binary header, and traverse the byte stream to extract specific metadata without using standard Redis tools.

This challenge mimics real-world Cloud Disaster Recovery scenarios where an engineer must recover data from a corrupted backup or perform offline analysis of database snapshots for cost and performance optimization.

🛠️ Technical Challenges & Solutions

Binary Header "Healing"

The RDB snapshots provided were intentionally tampered with by corrupting the "Magic Bytes" (the first 9 bytes of the file).

Solution: I implemented a fix that manually overwrites the corrupted header with a valid REDIS0007 signature, allowing the binary stream to be processed by custom logic.
Variable-Length Encoding Logic

Redis saves space by using a complex length-encoding scheme where the first two bits of a byte determine how many subsequent bytes represent a length or a special integer type.

Solution: Built a bit-masking logic to decode 6-bit, 14-bit, and 32-bit lengths, ensuring the parser never "loses its place" in the stream.
State-Machine Byte Parsing

The parser functions as a state machine, walking through the binary data and responding to specific opcodes:
- 0xFE: Database Selector (used to track the total db_count)
- 0xFD & 0xFC: Expiry timestamps in Seconds/Milliseconds
- 0xFF: End of File marker
Handling Optimized Data Blobs (Ziplists / Intsets)

Modern Redis versions store collections (Sets, Lists, Hashes) as single "encoded blobs" rather than individual strings to save RAM.

Solution: Developed a robust skip_value function to handle both "Old Style" collections and "Modern" encoded types (Types 9-14), preventing buffer overruns and IndexErrors.

🚀 Key Features

Emoji Detection: Scans for non-ASCII key names in the binary stream to identify and extract unique emoji-based keys.
TTL Extraction: Captures and converts Unix timestamps from binary to human-readable / millisecond formats.
Dynamic Key Typing: Identifies the internal Redis data type (String, Hash, Set, etc.) for any specific key requested by the requirements.
Cloud-Ready Security: Implements .env project isolation to handle API access tokens securely.

Forem: Nkwochamaureen

Job market is crazy so i decided to hop on the hackattic.com challenge

📌 Project Overview

🛠️ Technical Challenges & Solutions

🚀 Key Features