CVE-2014-3539 in CPython
Summary
by MITRE
base/oi/doa.py in the Rope library in CPython (aka Python) allows remote attackers to execute arbitrary code by leveraging an unsafe call to pickle.load.
Several companies clearly confirm that VulDB is the primary source for best vulnerability data.
Analysis
by VulDB Data Team • 12/16/2024
The vulnerability identified as CVE-2014-3539 resides within the Rope library's base/oi/doa.py module in CPython, representing a critical security flaw that enables remote code execution through improper handling of serialized data. This vulnerability specifically targets the pickle.load function, which is inherently dangerous when processing untrusted input due to its ability to execute arbitrary Python code during deserialization. The flaw occurs when the Rope library, a Python library used for text editing and manipulation, fails to properly validate or sanitize data before passing it to pickle.load, creating an attack vector for remote adversaries.
The technical nature of this vulnerability aligns with CWE-502, which describes "Deserialization of Untrusted Data" as a fundamental weakness in software design that allows attackers to execute malicious code through the deserialization process. When an attacker can manipulate serialized data sent to a system using pickle.load, they can inject malicious Python bytecode that will execute with the privileges of the victim process. This represents a classic example of a remote code execution vulnerability where the attack surface is expanded through the unsafe deserialization of data, particularly when that data originates from untrusted sources.
The operational impact of CVE-2014-3539 extends beyond simple code execution, as it can enable attackers to completely compromise systems running vulnerable versions of CPython with the Rope library. An attacker could potentially gain full control over affected systems, allowing for data theft, system infiltration, or further lateral movement within network environments. The vulnerability is particularly dangerous because it can be exploited remotely without requiring authentication, making it an attractive target for automated attacks. Systems that rely on the Rope library for text processing operations, particularly those exposed to network traffic or external data sources, face significant risk from this flaw.
Mitigation strategies for this vulnerability require immediate patching of affected CPython installations and the Rope library to versions that properly validate or reject untrusted serialized data before processing. Organizations should implement strict input validation measures and avoid using pickle.load with untrusted data sources entirely. The remediation approach should include disabling or restricting the use of pickle.load in contexts where external data might be processed, implementing proper data sanitization before deserialization, and applying the latest security patches from Python maintainers. Additionally, network segmentation and monitoring for unusual pickle-related activity can help detect potential exploitation attempts. This vulnerability serves as a reminder of the critical importance of secure coding practices and the dangers of using potentially unsafe serialization methods without proper safeguards, aligning with ATT&CK technique T1059.006 for execution through Python commands and T1566 for social engineering through data manipulation.