CVE-2007-4965 in Python
Summary
by MITRE
Multiple integer overflows in the imageop module in Python 2.5.1 and earlier allow context-dependent attackers to cause a denial of service (application crash) and possibly obtain sensitive information (memory contents) via crafted arguments to (1) the tovideo method, and unspecified other vectors related to (2) imageop.c, (3) rbgimgmodule.c, and other files, which trigger heap-based buffer overflows.
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Analysis
by VulDB Data Team • 01/26/2025
The vulnerability identified as CVE-2007-4965 represents a critical security flaw within Python's image processing modules, specifically affecting versions 2.5.1 and earlier. This issue stems from multiple integer overflow conditions that occur in the imageop module, which is responsible for handling various image operations within the Python environment. The vulnerability creates a dangerous scenario where maliciously crafted input can lead to unpredictable system behavior and potential information disclosure.
The technical implementation of this vulnerability involves integer overflows occurring in several core files including imageop.c, rbgimgmodule.c, and other related modules within the Python image processing framework. These overflows manifest when the application processes crafted arguments through methods such as tovideo and other image manipulation functions. The integer overflow conditions cause heap-based buffer overflows, where the application attempts to write data beyond the allocated memory boundaries. This memory corruption can result in application crashes, making the system unavailable to legitimate users through denial of service attacks.
The operational impact of this vulnerability extends beyond simple service disruption to potentially expose sensitive memory contents to attackers. When integer overflows occur in memory management operations, they can create opportunities for information disclosure attacks where attackers might extract confidential data from the application's memory space. The context-dependent nature of this vulnerability means that exploitation requires specific conditions to be met, typically involving the injection of specially crafted arguments that trigger the overflow conditions during image processing operations.
From a cybersecurity perspective, this vulnerability aligns with CWE-190, which specifically addresses integer overflow conditions that can lead to buffer overflows and memory corruption. The attack vector described in CVE-2007-4965 follows patterns consistent with the MITRE ATT&CK framework's techniques for privilege escalation and denial of service, particularly through memory corruption vulnerabilities. The vulnerability demonstrates how seemingly benign image processing operations can become attack vectors when proper input validation and memory management controls are absent.
Organizations should implement immediate mitigation strategies including upgrading to Python versions that address these integer overflow conditions, implementing strict input validation for all image processing operations, and deploying memory protection mechanisms such as stack canaries and address space layout randomization. The vulnerability underscores the importance of proper integer handling in security-critical applications and highlights the need for comprehensive code reviews focusing on memory management operations in legacy systems. Regular security assessments and vulnerability scanning should be conducted to identify similar integer overflow conditions that may exist in other parts of the application stack.