ALEAPP / iLEAPP: Open-Source Mobile Artifacts Parsing for Android & iOS

ALEAPP / iLEAPP – Open-Source Mobile Artifact Parsers

Parse Android & iOS artifacts, generate interactive HTML reports, and accelerate mobile DFIR.

Why ALEAPP / iLEAPP?

ALEAPP (Android Logs Events And Protobuf Parser) and iLEAPP (iOS Logs, Events, And Plists Parser) are free, open-source DFIR tools widely used to extract and normalize artifacts from mobile device extractions. They support GUI & CLI, run on Windows, macOS, and Linux, and produce interactive HTML reports along with TSV and SQLite outputs for deeper analysis and timelines.

Highlights:
  • Hundreds of Android/iOS artifacts: calls, SMS/MMS, contacts, locations, app data, and more.
  • Interactive HTML reports for quick triage; TSV/SQLite for pivoting and timeline work.
  • Modular design—extend with Python artifact plugins/modules.
  • Active community and frequent updates.

Practical Workflow (Step-by-Step)

  1. Acquire data: Export a logical/FS/TAR/ZIP extraction from the device (via your preferred acquisition tool).
  2. Run ALEAPP / iLEAPP: Launch the GUI or CLI and point to the extraction folder/TAR/ZIP.
  3. Select modules: (Optional) filter artifact modules relevant to your case.
  4. Process & review: Open the generated index.html report and review artifacts by category.
  5. Deep-dive: Use TSV/SQLite outputs to pivot, join, and timeline events in your analysis tool of choice.
  6. Validate & report: Correlate across apps/logs and export case-ready findings.

Field Tips from DFIR Practice

  • Correlate artifacts: Cross-check app timestamps with system logs (power, network, notifications) to validate user activity.
  • Leverage SQLite/TSV: Load exported databases into your analysis stack (e.g., Python/SQL or timeline tools) for richer pivots.
  • Extend coverage: When you discover a new app artifact, write a minimal Python parser and drop it in the modules folder.
  • Chain-of-custody: Keep acquisition images read-only; export working copies for parsing.

Getting Started (Quick Links)

Use Cases

  • Triage at scale: Rapidly parse extractions to prioritize deep analysis.
  • App analysis: Recover chats, media, and account data from popular and niche apps.
  • Timeline building: Export SQLite/TSV to build cross-app timelines and correlate user activity.

© 2025 Forensicslarn | Tool of the Day #13 – ALEAPP / iLEAPP

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