email-forensics

Email header analysis for phishing investigations involves parsing mailbox files to inspect routing paths, authentication results, and metadata, which detects spoofing attempts and extracts structured forensic artifacts and investigative reports.

Yes, parsing PST and OST files reconstructs email timelines by extracting messages and folder structures from these formats, building searchable timelines that map communication sequences for forensic investigations.

Detecting email spoofing and business email compromise is best achieved by analyzing mailbox artifacts and authentication headers, identifying impersonation patterns and phishing signals across extracted email data to surface anomalies.

Email forensics supports MBOX, EML, and MSG formats, extracting messages and analyzing attachments across these file types to extract Indicators of Compromise and uncover evidence for security incidents.

Yes, analyzing mailbox data requires Python 3.9+, alongside optional libraries like libpst, python-msg, and mailbox, which parse specific formats to output structured forensic artifacts and searchable timelines.

Extracting Indicators of Compromise from email attachments requires parsing mailbox data to analyze associated files and metadata, surfacing artifacts needed for investigating phishing campaigns and security incidents.