CVE-2008-3143 in Python
Summary
by MITRE
Multiple integer overflows in Python before 2.5.2 might allow context-dependent attackers to have an unknown impact via vectors related to (1) Include/pymem.h; (2) _csv.c, (3) _struct.c, (4) arraymodule.c, (5) audioop.c, (6) binascii.c, (7) cPickle.c, (8) cStringIO.c, (9) cjkcodecs/multibytecodec.c, (10) datetimemodule.c, (11) md5.c, (12) rgbimgmodule.c, and (13) stropmodule.c in Modules/; (14) bufferobject.c, (15) listobject.c, and (16) obmalloc.c in Objects/; (17) Parser/node.c; and (18) asdl.c, (19) ast.c, (20) bltinmodule.c, and (21) compile.c in Python/, as addressed by "checks for integer overflows, contributed by Google."
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Analysis
by VulDB Data Team • 08/15/2019
The vulnerability described in CVE-2008-3143 represents a critical class of integer overflow flaws affecting Python versions prior to 2.5.2. These vulnerabilities stem from insufficient input validation and overflow checking mechanisms within core Python modules, creating potential pathways for malicious exploitation that could result in arbitrary code execution or system compromise. The affected components span across multiple subsystems including memory management, string handling, data serialization, and parsing modules, indicating a systemic issue in Python's internal implementation that requires comprehensive remediation.
The technical nature of these integer overflows manifests in various Python core modules where integer arithmetic operations are performed without adequate bounds checking. Specifically, the vulnerabilities exist in pymem.h which handles memory allocation, _csv.c and _struct.c for data processing, arraymodule.c for array operations, and numerous other modules including audioop.c for audio processing, binascii.c for binary data handling, and cPickle.c for object serialization. These modules are particularly susceptible because they process user-supplied data that could trigger integer overflow conditions when handling large inputs or malformed data structures.
The operational impact of these vulnerabilities extends beyond simple memory corruption, potentially enabling attackers to execute arbitrary code with the privileges of the Python interpreter process. The context-dependent nature of the attack vectors means that exploitation requires specific conditions related to the data being processed by the vulnerable modules, but once triggered, the consequences can be severe. Attackers could leverage these flaws to bypass security controls, escalate privileges, or cause denial of service conditions that could affect applications relying on Python for critical operations. The vulnerabilities are particularly concerning because they affect fundamental Python operations that are widely used across different applications and systems.
The root cause of these vulnerabilities aligns with CWE-190, which describes integer overflow and wraparound conditions, and can be mapped to ATT&CK techniques involving privilege escalation and code execution. The affected modules represent different attack surfaces within Python's architecture, from memory management in obmalloc.c to parsing operations in Parser/node.c and compile.c. The implementation of checks for integer overflows contributed by Google represents a targeted fix addressing these specific weaknesses, but the vulnerability demonstrates the importance of rigorous input validation and overflow protection in interpreted languages. Organizations should prioritize updating to Python 2.5.2 or later versions to mitigate these risks, as the vulnerabilities could be exploited to compromise entire systems depending on Python-based applications. The widespread use of Python in web applications, scientific computing, and system administration makes these vulnerabilities particularly dangerous, requiring immediate attention from security teams responsible for maintaining Python environments across their infrastructure.