Analyzing Outlook Pst For Email Forensics

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#!/usr/bin/env python3
"""Outlook PST file forensic analysis agent.

Parses PST/OST files using pypff (libpff) to extract emails, attachments,
metadata, and deleted items for forensic investigation.
"""

import os
import sys
import json
import hashlib
import re

try:
    import pypff
    HAS_PYPFF = True
except ImportError:
    HAS_PYPFF = False


def compute_hash(filepath):
    sha256 = hashlib.sha256()
    with open(filepath, "rb") as f:
        for chunk in iter(lambda: f.read(65536), b""):
            sha256.update(chunk)
    return sha256.hexdigest()


def open_pst(filepath):
    if not HAS_PYPFF:
        return None, "pypff not installed. pip install libpff-python"
    pst = pypff.file()
    pst.open(filepath)
    return pst, None


def extract_messages(folder, max_messages=1000):
    messages = []
    for i in range(min(folder.number_of_sub_messages, max_messages)):
        msg = folder.get_sub_message(i)
        entry = {
            "subject": msg.subject or "",
            "sender": msg.sender_name or "",
            "headers": (msg.transport_headers or "")[:500],
            "creation_time": str(msg.creation_time) if msg.creation_time else "",
            "delivery_time": str(msg.delivery_time) if msg.delivery_time else "",
            "has_attachments": msg.number_of_attachments > 0,
            "attachment_count": msg.number_of_attachments,
            "body_size": len(msg.plain_text_body or "") if msg.plain_text_body else 0,
        }
        # Extract attachment metadata
        attachments = []
        for j in range(msg.number_of_attachments):
            att = msg.get_attachment(j)
            attachments.append({
                "name": att.name or f"attachment_{j}",
                "size": att.size,
            })
        entry["attachments"] = attachments
        messages.append(entry)
    return messages


def walk_folders(folder, path="", results=None):
    if results is None:
        results = []
    current_path = f"{path}/{folder.name}" if folder.name else path or "/Root"
    messages = extract_messages(folder)
    if messages:
        results.append({
            "folder": current_path,
            "message_count": len(messages),
            "messages": messages,
        })
    for i in range(folder.number_of_sub_folders):
        subfolder = folder.get_sub_folder(i)
        walk_folders(subfolder, current_path, results)
    return results


def extract_email_addresses(messages):
    addresses = set()
    email_pattern = re.compile(r"[\w.+-]+@[\w-]+\.[\w.-]+")
    for msg in messages:
        for field in [msg.get("sender", ""), msg.get("headers", "")]:
            addresses.update(email_pattern.findall(field))
    return sorted(addresses)


def detect_suspicious_emails(messages):
    findings = []
    suspicious_exts = [".exe", ".scr", ".bat", ".cmd", ".ps1", ".vbs",
                       ".js", ".hta", ".lnk", ".iso", ".img"]
    for msg in messages:
        for att in msg.get("attachments", []):
            name = (att.get("name") or "").lower()
            for ext in suspicious_exts:
                if name.endswith(ext):
                    findings.append({
                        "type": "suspicious_attachment",
                        "subject": msg.get("subject", "")[:80],
                        "attachment": att.get("name"),
                        "extension": ext,
                        "severity": "HIGH",
                    })
        subject = (msg.get("subject") or "").lower()
        urgency_words = ["urgent", "immediate action", "password expired",
                         "verify your account", "suspended", "click here"]
        for word in urgency_words:
            if word in subject:
                findings.append({
                    "type": "phishing_indicator",
                    "subject": msg.get("subject", "")[:80],
                    "keyword": word,
                    "severity": "MEDIUM",
                })
                break
    return findings


def generate_report(filepath, folder_data):
    all_messages = []
    for fd in folder_data:
        all_messages.extend(fd.get("messages", []))
    addresses = extract_email_addresses(all_messages)
    suspicious = detect_suspicious_emails(all_messages)
    return {
        "file": filepath,
        "sha256": compute_hash(filepath),
        "size": os.path.getsize(filepath),
        "total_folders": len(folder_data),
        "total_messages": len(all_messages),
        "unique_addresses": len(addresses),
        "top_addresses": addresses[:20],
        "suspicious_findings": suspicious,
        "folders": [{
            "path": f["folder"],
            "count": f["message_count"],
        } for f in folder_data],
    }


if __name__ == "__main__":
    print("=" * 60)
    print("Outlook PST Forensic Analysis Agent")
    print("Email extraction, attachment analysis, phishing detection")
    print("=" * 60)

    target = sys.argv[1] if len(sys.argv) > 1 else None
    if not target or not os.path.exists(target):
        print("\n[DEMO] Usage: python agent.py <mailbox.pst>")
        print(f"  pypff available: {HAS_PYPFF}")
        sys.exit(0)

    pst, err = open_pst(target)
    if err:
        print(f"[!] {err}")
        sys.exit(1)

    print(f"\n[*] Parsing: {target}")
    root = pst.get_root_folder()
    folder_data = walk_folders(root)
    report = generate_report(target, folder_data)

    print(f"[*] Folders: {report['total_folders']}")
    print(f"[*] Messages: {report['total_messages']}")
    print(f"[*] Unique addresses: {report['unique_addresses']}")

    print("\n--- Folder Structure ---")
    for f in report["folders"]:
        print(f"  {f['path']}: {f['count']} messages")

    print(f"\n--- Suspicious ({len(report['suspicious_findings'])}) ---")
    for s in report["suspicious_findings"][:10]:
        print(f"  [{s['severity']}] {s['type']}: {s.get('attachment', s.get('keyword', ''))}")

    pst.close()
    print(f"\n{json.dumps(report, indent=2, default=str)}")