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Area of Science:

  • Digital Forensics
  • Computer Science
  • Information Security

Background:

  • The COVID-19 pandemic accelerated the adoption of remote collaboration tools like Microsoft Teams.
  • Microsoft Teams utilizes IndexedDB for client-side data storage, presenting a novel area for digital forensic investigation.
  • Understanding data artifacts in Microsoft Teams is crucial for modern digital investigations.

Purpose of the Study:

  • To investigate the digital forensic artifacts generated by Microsoft Teams within its IndexedDB storage.
  • To assess the feasibility of extracting valuable forensic data from Microsoft Teams IndexedDB.
  • To evaluate the security implications of artifact accessibility.

Main Methods:

  • A quasi-experimental design (pretest-posttest) was employed to generate Microsoft Teams artifacts in IndexedDB.
  • Artifact extraction was performed without requiring user credentials.
  • Data analysis involved signature pattern processing, database queries, and time-frame analysis.

Main Results:

  • Significant digital forensic artifacts were successfully extracted from Microsoft Teams IndexedDB.
  • Complete contents of private chat messages and voicemails were recovered.
  • Artifact extraction occurred without user credentials, highlighting potential security vulnerabilities.

Conclusions:

  • Microsoft Teams IndexedDB storage is a valuable and largely untapped source for digital forensic investigations.
  • The extracted artifacts, including chat messages and voicemails, provide crucial evidence for investigators.
  • Efficient time-frame analysis enhances the utility of these artifacts in forensic investigations.