analyzing-outlook-pst-for-email-forensics skill
Parse Microsoft Outlook PST and OST files using libpff and pst-utils to extract message content, headers, attachments, deleted items, and MAPI metadata, including recovery of items from the Recoverable Items folder. Use when conducting email forensic investigations, legal e-discovery, or incident response that requires reconstructing communication patterns or tracing message routing from Outlook archives.
Is the analyzing-outlook-pst-for-email-forensics skill safe?
Clean: nothing in its files matched our rules. We read 6 files in the folder on 2026-09-28.
No findings.
Install the analyzing-outlook-pst-for-email-forensics skill
A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description.
git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git /tmp/Anthropic-Cybersecurity-Skills mkdir -p ~/.claude/skills cp -r /tmp/Anthropic-Cybersecurity-Skills/skills/analyzing-outlook-pst-for-email-forensics ~/.claude/skills/analyzing-outlook-pst-for-email-forensics
In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub
The instructions your agent would load
SKILL.md as published, without the frontmatter. Read it on GitHub
Analyzing Outlook PST for Email Forensics
Overview
Microsoft Outlook PST (Personal Storage Table) and OST (Offline Storage Table) files are critical evidence sources in digital forensics investigations. PST files store email messages, calendar events, contacts, tasks, and notes in a proprietary binary format based on the MAPI (Messaging Application Programming Interface) property system. Forensic analysis of these files enables recovery of deleted emails (from the Recoverable Items folder), extraction of email headers for tracing message routes, analysis of attachments for malware or exfiltrated data, and reconstruction of communication patterns. Modern PST files use Unicode format with 4KB pages and can grow up to 50GB, while legacy ANSI format is limited to 2GB.
When to Use
- When investigating security incidents that require analyzing outlook pst for email forensics
- When building detection rules or threat hunting queries for this domain
- When SOC analysts need structured procedures for this analysis type
- When validating security monitoring coverage for related attack techniques
Prerequisites
- libpff/pffexport (open-source PST parser)
- Python 3.8+ with pypff or libratom libraries
- MailXaminer, Forensic Email Collector, or SysTools PST Forensics (commercial)
- Microsoft Outlook (optional, for native PST access)
- Sufficient disk space for extracted content
PST File Locations
Analysis with Open-Source Tools
libpff / pffexport
# Export all items from PST file
pffexport -m all evidence.pst -t exported_pst
# Export only email messages
pffexport -m items evidence.pst -t exported_emails
# Export recovered/deleted items
pffexport -m recovered evidence.pst -t recovered_items
# Get PST file information
pffinfo evidence.pstPython PST Analysis
import pypff
import os
import json
import hashlib
import email
import sys
from datetime import datetime
from collections import defaultdict
class PSTForensicAnalyzer:
"""Forensic analysis of Outlook PST/OST files."""
def __init__(self, pst_path: str, output_dir: str):
self.pst_path = pst_path
self.output_dir = output_dir
os.makedirs(output_dir, exist_ok=True)
self.pst = pypff.file()
self.pst.open(pst_path)
self.messages = []
self.attachments = []
self.stats = defaultdict(int)
def process_folder(self, folder, folder_path: str = ""):
"""Recursively process PST folders and extract messages."""
folder_name = folder.name or "Root"
current_path = f"{folder_path}/{folder_name}" if folder_path else folder_name
for i in range(folder.number_of_sub_messages):
try:
message = folder.get_sub_message(i)
msg_data = self.extract_message(message, current_path)
if msg_data:
self.messages.append(msg_data)
self.stats["total_messages"] += 1
except Exception as e:
selEmail Header Analysis
Key headers for forensic investigation:
References
- MailXaminer PST Forensics: https://www.mailxaminer.com/blog/outlook-pst-file-forensics/
- libpff Documentation: https://github.com/libyal/libpff
- PST File Format Specification: https://docs.microsoft.com/en-us/openspecs/officefileformats/ms-pst/
- SANS Email Forensics: https://www.sans.org/blog/email-forensics/
Example Output
$ pffexport /evidence/jsmith_archive.pst -t /analysis/pst_output
pffexport 20231205 - libpff PST/OST Export Tool
=================================================
Input: /evidence/jsmith_archive.pst (2.3 GB)
Exporting PST contents...
Folders: 45
Messages: 12,456
Attachments: 3,234
Contacts: 567
Calendar: 234
Tasks: 89
Export completed in 3m 42s.
$ python3 pst_analyzer.py /analysis/pst_output /analysis/email_report
PST Forensic Analysis Report
==============================
Source: jsmith_archive.pst (john.smith@corporate.com)
Date Range: 2023-06-01 to 2024-01-18
--- Mailbox Statistics ---
Total Emails: 12,456
Sent: 4,567
Received: 7,889
With Attachments: 3,234
Deleted (recovered): 234
--- Phishing / Suspicious Emails ---
Email #8923
Date: 2024-01-15 14:30:22 UTC
From: "IT Support" <it-support@c0rporate-help.com>
To: john.smith@corporate.com
Subject: Urgent: Password Reset Required
Headers:
Return-Path: bounce@mail-relay.c0rporate-help.com
X-Originating-IP: 203.0.113.55
Received: from mail-relay.c0rporate-help.com (203.0.113.55)
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