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2.5 KiB
2.5 KiB
API Reference: Outlook PST Email Forensics
pypff (libpff Python bindings)
Installation
pip install libpff-python
Opening a PST File
import pypff
pst = pypff.file()
pst.open("mailbox.pst")
root = pst.get_root_folder()
Navigating Folders
for i in range(root.number_of_sub_folders):
folder = root.get_sub_folder(i)
print(f"{folder.name}: {folder.number_of_sub_messages} messages")
Extracting Messages
msg = folder.get_sub_message(0)
print(msg.subject)
print(msg.sender_name)
print(msg.delivery_time)
print(msg.transport_headers)
print(msg.plain_text_body)
print(msg.html_body)
Extracting Attachments
for i in range(msg.number_of_attachments):
att = msg.get_attachment(i)
print(f"Name: {att.name}, Size: {att.size}")
data = att.read_buffer(att.size)
pffexport (CLI)
Syntax
pffexport mailbox.pst # Export all to current dir
pffexport -m all mailbox.pst # Export all message types
pffexport -t target_dir mailbox.pst # Export to target directory
pffexport -f text mailbox.pst # Export as text format
Output Structure
Export/
Inbox/
Message001/
Message.txt
Attachment001.pdf
Sent Items/
Deleted Items/
readpst (libpst)
Syntax
readpst -o output_dir mailbox.pst # Extract to dir
readpst -e mailbox.pst # Extract attachments
readpst -r mailbox.pst # Recursive extraction
readpst -j 4 mailbox.pst # Parallel (4 threads)
readpst -S mailbox.pst # Separate files per message
PST File Structure
| Component | Description |
|---|---|
| NDB Layer | Node Database - raw data storage |
| LTP Layer | Lists/Tables/Properties - message properties |
| Messaging Layer | Folders, messages, attachments |
Key Message Properties
| Property | MAPI Tag | Description |
|---|---|---|
| Subject | PR_SUBJECT (0x0037) | Email subject |
| Sender | PR_SENDER_NAME (0x0C1A) | Sender display name |
| From | PR_SENT_REPRESENTING_EMAIL (0x0065) | Sender email |
| Delivery Time | PR_MESSAGE_DELIVERY_TIME (0x0E06) | When delivered |
| Headers | PR_TRANSPORT_MESSAGE_HEADERS (0x007D) | Full SMTP headers |
Forensic Considerations
- Deleted Items folder may contain evidence
- Recoverable Items (dumpster) requires special extraction
- Calendar/Contacts may contain relevant data
- Journal entries can provide timeline evidence