CVE-2017-10803 in Odoo
Summary
by MITRE
In Odoo 8.0, Odoo Community Edition 9.0 and 10.0, and Odoo Enterprise Edition 9.0 and 10.0, insecure handling of anonymization data in the Database Anonymization module allows remote authenticated privileged users to execute arbitrary Python code, because unpickle is used.
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Analysis
by VulDB Data Team • 12/28/2024
The vulnerability identified as CVE-2017-10803 affects multiple versions of the Odoo ERP system including Odoo 8.0, Community Edition 9.0 and 10.0, and Enterprise Edition 9.0 and 10.0. This security flaw resides within the Database Anonymization module, which is designed to sanitize database content for privacy purposes. The issue stems from insecure handling of anonymization data where the system employs the unpickle function, creating a critical security risk that can be exploited by authenticated users with privileged access. The vulnerability represents a classic deserialization vulnerability that allows for arbitrary code execution, making it particularly dangerous in enterprise environments where database sanitization operations are commonly performed.
The technical flaw manifests through the improper use of Python's pickle module within the anonymization process. When the Database Anonymization module processes anonymization data, it deserializes user-provided input using the unpickle function without adequate validation or sanitization. This design choice directly violates security best practices and creates a pathway for remote code execution. The pickle module in Python is inherently dangerous when processing untrusted data because it can execute arbitrary code during the deserialization process. Attackers can craft malicious pickle data containing serialized Python objects that, when processed by the vulnerable system, execute arbitrary commands on the server with the privileges of the Odoo application. This vulnerability maps to CWE-502 which specifically addresses deserialization of untrusted data, and aligns with ATT&CK technique T1059.006 for execution through Python.
The operational impact of this vulnerability is severe for organizations using affected Odoo versions, as it allows authenticated privileged users to gain complete control over the database server. An attacker with access to the anonymization functionality can execute arbitrary Python code, potentially leading to data exfiltration, system compromise, or further lateral movement within the network. The vulnerability affects organizations that regularly perform database anonymization operations, which are common in development and testing environments where sensitive data needs to be sanitized. The risk is particularly elevated because the attack requires only authenticated access, meaning that users with legitimate administrative privileges could be exploited to gain unauthorized access. This type of vulnerability can result in significant business disruption, regulatory compliance violations, and financial losses due to potential data breaches and system compromise.
Organizations should immediately implement mitigations to address this vulnerability by upgrading to patched versions of Odoo that resolve the insecure deserialization issue. The recommended approach involves replacing the unpickle function with safer serialization methods such as JSON or XML, which do not execute arbitrary code during deserialization. Additionally, organizations should implement strict input validation and sanitization for all anonymization data, ensuring that user-provided inputs are properly verified before processing. Network segmentation and access controls should be enforced to limit privileged access to the anonymization functionality, reducing the attack surface. Security monitoring should be enhanced to detect suspicious anonymization activities, and regular security assessments should be conducted to identify similar vulnerabilities in other parts of the system. The remediation efforts should also include comprehensive staff training on secure coding practices and the dangers of deserialization vulnerabilities in enterprise applications.