SQLite Truncated Database Recovery

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This skill provides comprehensive guidance for restoring data from SQLite databases suffering from binary truncation, incomplete writes, or filesystem errors. It helps users analyze raw file structures using hex dumps to identify specific corruption patterns, such as missing headers or partial pages, and provides systematic Python-based implementation patterns for parsing SQLite's internal page structures. By focusing on low-level technical details like varint encoding and big-endian serial types, it enables successful data extraction even when standard command-line utilities report malformed disk images.

Características Principales

• Systematic verification strategies to validate the integrity of recovered records
• 16 GitHub stars
• Implementation patterns for varint decoding and big-endian integer handling
• Mapping of serial types to data formats for strings, integers, and BLOBs
• Strategies to identify corruption patterns like missing headers and partial pages
• Guidance for manual binary parsing of SQLite page structures and cell layouts

Casos de Uso

• Extracting records from a file that was truncated and lacks a standard SQLite file header
• Manually reconstructing table data when the built-in SQLite .recover command fails
• Restoring critical data from a database that returns 'database disk image is malformed' errors