CVE-2017-12852 in Numpy
Summary
by MITRE
The numpy.pad function in Numpy 1.13.1 and older versions is missing input validation. An empty list or ndarray will stick into an infinite loop, which can allow attackers to cause a DoS attack.
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Analysis
by VulDB Data Team • 03/04/2025
The numpy.pad function vulnerability identified as CVE-2017-12852 represents a critical denial of service weakness in the popular numerical computing library numpy. This flaw exists in versions 1.13.1 and earlier, where the function fails to properly validate input parameters, creating a dangerous condition that can be exploited by malicious actors. The vulnerability specifically manifests when the function receives empty list or ndarray inputs, which trigger an infinite loop execution pattern that consumes system resources indefinitely.
The technical implementation of this vulnerability stems from inadequate parameter validation within the numpy.pad function's internal processing logic. When an empty list or empty ndarray is passed as input, the function's loop conditions fail to properly terminate, creating a scenario where the execution enters an endless cycle. This behavior directly violates the principle of input validation that should be implemented at all levels of software development to prevent unexpected execution paths. The flaw can be categorized under CWE-20, which describes improper input validation, and specifically aligns with CWE-400, indicating improper handling of exceptional conditions through infinite loops.
From an operational standpoint, this vulnerability presents a significant risk to systems utilizing numpy for data processing tasks, particularly those exposed to untrusted input sources. Attackers can exploit this weakness by crafting malicious input parameters that consist of empty lists or arrays, causing the targeted application to enter an infinite loop state. This resource exhaustion scenario can lead to complete system unresponsiveness or denial of service conditions, affecting legitimate users and potentially causing cascading failures in larger systems. The vulnerability is particularly concerning in web applications and APIs that process user-supplied data, as these environments provide ample opportunities for exploitation.
The impact of this vulnerability extends beyond simple resource consumption, as it can be leveraged as part of broader attack strategies within the MITRE ATT&CK framework, specifically under the T1499 category for network denial of service attacks. Organizations relying on numpy for scientific computing, data analysis, and machine learning applications face potential disruption when this vulnerability is exploited. The infinite loop condition makes it particularly challenging to detect and mitigate, as the system may appear to be functioning normally while consuming resources in an unbounded manner.
Mitigation strategies for CVE-2017-12852 primarily focus on upgrading to numpy version 1.13.2 or later, where the input validation has been properly implemented to prevent the infinite loop scenario. System administrators should also implement input sanitization measures at application layers that process numpy functions, ensuring that empty inputs are properly rejected before reaching the vulnerable function. Additionally, monitoring systems should be configured to detect unusual resource consumption patterns that may indicate exploitation attempts. Organizations should consider implementing application-level firewalls or input validation proxies to prevent malformed input from reaching vulnerable components, aligning with defensive strategies recommended in the CWE guidelines for preventing input validation flaws.