T09 · Insecure Skill Coding Practices
Warning
- Location
- SKILL.md:390
- Finding
- Spreadsheet Formula Injection Through Unsanitized OCR Data## Vulnerability Details **File Location**: `SKILL.md`, lines 390–401 **Vulnerability Type**: Spreadsheet formula injection **Risk Level**: Medium ### Vulnerable Code ```python ws[f'A{last_row}'] = invoice_data.get('entry_date', date.today()) ws[f'B{last_row}'] = invoice_data.get('invoice_code') ws[f'C{last_row}'] = invoice_data.get('invoice_number') ws[f'D{last_row}'] = invoice_data.get('product_name') ws[f'E{last_row}'] = invoice_data.get('spec') ws[f'F{last_row}'] = invoice_data.get('quantity') ws[f'G{last_row}'] = invoice_data.get('unit_price') ws[f'H{last_row}'] = invoice_data.get('amount') ws[f'I{last_row}'] = invoice_data.get('tax_amount') ws[f'J{last_row}'] = invoice_data.get('total_amount') ws[f'K{last_row}'] = invoice_data.get('seller_name') ws[f'L{last_row}'] = invoice_data.get('purchase_order_no') ``` ### Technical Analysis The function writes OCR-derived invoice fields directly into Excel cells without validating their expected types or neutralizing spreadsheet formula prefixes. Text beginning with `=`, `+`, `-`, or `@` may be interpreted as a formula by Excel or another spreadsheet client rather than as literal invoice data. An attacker who controls invoice content could place a formula-like payload in fields such as the product name, specification, seller name, or purchase-order number. If OCR preserves that content, `openpyxl` stores it in the workbook without a protective literal-text prefix. The payload may then be evaluated when a finance user opens the workbook. The precise behavior depends on the spreadsheet client and its security configuration. Potential payloads include deceptive formulas, malicious hyperlinks, and formulas that attempt external-data access. There is no evidence in the audited project of direct operating-system command execution; such an outcome would require additional client-specific unsafe features or user interaction. ### Attack Path 1. An attacker creates or modifies an invoice image containing formula-prefi ...[truncated 1347 chars]
- Remediation
- ## Remediation Suggestions 1. Apply centralized sanitization to every untrusted value before writing it to a spreadsheet: ```python def excel_safe(value): if isinstance(value, str): value = value.strip() if value.startswith(("=", "+", "-", "@")): return "'" + value return value ``` 2. Use the sanitizer for all OCR-derived textual fields: ```python ws[f'D{last_row}'] = excel_safe(invoice_data.get('product_name')) ws[f'E{last_row}'] = excel_safe(invoice_data.get('spec')) ws[f'K{last_row}'] = excel_safe(invoice_data.get('seller_name')) ws[f'L{last_row}'] = excel_safe(invoice_data.get('purchase_order_no')) ``` 3. Enforce field-specific validation: - Require invoice codes and numbers to match documented numeric formats. - Parse monetary values, quantities, and tax rates into numeric types before writing them. - Apply length and character restrictions to names, specifications, and order identifiers. - Reject values containing control characters or unexpected formula syntax. 4. Treat all OCR output as untrusted, even if the source resembles an official invoice. 5. Add regression tests covering values beginning with `=`, `+`, `-`, and `@`, including malicious hyperlinks and external-reference formulas. 6. Document that generated workbooks contain imported content and should be opened with external links, macros, and automatic data updates disabled.