T05 · Unauthorized Access and Privilege Escalation
Error
- Location
- scripts/fetch_orders.py:35
- Finding
- Mailbox Collection Exceeds the Stated Order-Processing Scope## Vulnerability Details **File Location**: `scripts/fetch_orders.py`, lines 35-47 **Vulnerability Type**: Excessive mailbox access and collection **Risk Level**: High ### Vulnerable Code ```python emails = [] for msg in mailbox.fetch(AND(date_gte=date_since.date()), limit=50, reverse=True): emails.append({ 'subject': msg.subject, 'from': msg.from_, 'date': msg.date, 'text': msg.text or msg.html }) print(f"共获取 {len(emails)} 封邮件\n") for i, email in enumerate(emails, 1): print(f"{i}. [{email['date']}] {email['subject']}") print(f" From: {email['from']}") ``` ### Technical Analysis The Skill is described as retrieving order emails, but the IMAP query only restricts messages by date. It does not filter by mailbox folder, sender, recipient, subject, message labels, or other order-specific characteristics. It consequently retrieves the subject, sender, date, and complete plain-text or HTML body of up to 50 recent messages. This violates least-privilege and data-minimization principles. Authentication is performed with a mailbox-wide authorization code, and the implementation uses that access to collect unrelated messages rather than limiting collection to content necessary for order processing. ### Attack Path 1. A user supplies a valid QQ Mail authorization code and runs the documented `fetch_orders.py` command. 2. The script logs in to the mailbox with the user's IMAP privileges. 3. It queries every message within the configured date range, up to the limit of 50 messages. 4. It extracts the complete text or HTML body from each message without determining whether the message concerns an order. 5. The resulting collection becomes available to the calling process or AI workflow for subsequent processing. 6. Unrelated confidential messages may therefore be disclosed beyond the intended order-processing scope. ### Impact Assessment The script can acces ...[truncated 466 chars]
- Remediation
- ## Remediation Suggestions - Require an explicit order-specific sender, subject, folder, or label filter before querying the mailbox. - Retrieve message headers first and fetch a body only after confirming that the message is relevant. - Show the proposed query and scope to the user and obtain confirmation before reading message bodies. - Use a dedicated mailbox or folder for order processing where possible. - Minimize the default date range and message count. - Redact authentication codes, financial data, and other sensitive patterns before passing content to an AI workflow. - Clearly disclose the exact mailbox data that will be read and retained.