A buffer overflow vulnerability exists in the array_from_pyobj function of fortranobject.c in NumPy versions prior to 1.19. This vulnerability allows attackers to conduct Denial of Service attacks by carefully constructing an array with negative values. Although the vendor does not agree that this constitutes a vulnerability, as such arrays can only be created by an already privileged user or internally, the risks associated with this flaw still warrant attention.
The severity of this vulnerability is rated as medium, with a CVSS score of 5.5. This indicates that while the attack complexity is low, the potential impact on availability is high. Consequently, organizations using affected versions of NumPy should consider this vulnerability a priority.
Given the nature of the vulnerability and the circumstances under which it can be exploited, it is crucial for defenders to understand the real-world risk context. Organizations should prioritize patching immediately to mitigate any potential Denial of Service scenarios.
Currently, there is no known exploit available for this vulnerability, and it has not been included in the Known Exploited Vulnerabilities (KEV) catalog. However, organizations should not become complacent, as vulnerabilities can evolve, and attackers may still leverage this weakness.
In summary, the medium-severity buffer overflow in NumPy requires immediate attention from organizations to prevent potential Denial of Service attacks.
Vulnerability Details
This vulnerability allows for an overflow in the array_from_pyobj function of fortranobject.c in NumPy versions prior to 1.19. The official CVE description states that this vulnerability is associated with a buffer overflow, which allows attackers to conduct Denial of Service attacks by constructing arrays with negative values. The vendor, however, disputes the classification of this as a vulnerability, stating that such dimensions can only be created by privileged users or internally.
The CVSS score for this vulnerability is 5.5, indicating medium severity. The attack vector is classified as local, with low complexity, and requires low privileges. There is no user interaction required, and the impact on availability is high, while the impacts on confidentiality and integrity are none.
The vulnerability was published on December 17, 2021. It is associated with CWE-120, which pertains to buffer errors.
Technical Analysis
The root cause of this vulnerability stems from insufficient validation of array dimensions within the array_from_pyobj function. The function does not adequately handle negative values, leading to a buffer overflow.
The attack vector for this vulnerability is local, meaning an attacker would need local access to the affected system. The attack complexity is low, and the privileges required to exploit this vulnerability are also low. User interaction is not required for successful exploitation.
The impacts of this vulnerability include high availability impact, meaning that a successful attack could render the affected application or service unavailable. There are no confidentiality or integrity impacts associated with this vulnerability.
Risk & Impact Analysis
Organizations utilizing NumPy versions prior to 1.19 face real-world deployment risks associated with this vulnerability. The potential for Denial of Service attacks poses a significant threat, particularly for applications reliant on NumPy for data processing and numerical computations.
The urgency for organizations using affected versions of NumPy is high. Given the CVSS score of 5.5 and the associated availability impact, organizations should prioritize addressing this vulnerability in their patch cycles to ensure operational integrity.
Failure to address this vulnerability could lead to substantial downtime, affecting business continuity and potentially resulting in financial losses.
Organizations should also consider the blast radius of this vulnerability as it could affect any application or service that relies on NumPy, potentially impacting multiple systems.
Exploitation Status
Signal | Status |
|---|---|
Known Exploit | No |
Public PoC | No |
Actively Exploited | No |
Ransomware Use | No |
Affected Versions
All versions of NumPy prior to 1.19 are affected by this vulnerability. Organizations should ensure they upgrade to the latest version to mitigate this risk.
Mitigation & Remediation
To address this vulnerability, organizations should upgrade to NumPy version 1.19 or later. If immediate upgrading is not feasible, implementing configuration hardening and network controls may mitigate some risks associated with this vulnerability.
Organizations should validate the effectiveness of their patches through penetration testing and security assessments to identify similar weaknesses.
Detection Guidance
Organizations should monitor logs for any unusual behaviors or errors that could indicate exploitation attempts. Behavioral anomalies, especially those related to memory handling and array operations, should also be scrutinized.
Additionally, network signatures may help detect malicious activities attempting to exploit this vulnerability.
AppSecure Threat Intelligence Insight
The buffer overflow vulnerability in NumPy serves as a reminder of the need for robust input validation within software. Vulnerabilities of this nature highlight the importance of secure coding practices and regular updates to dependencies.
This case exemplifies how even minor flaws can have significant implications, particularly in widely used libraries like NumPy. Organizations should remain vigilant and proactive in their security measures.
To bolster defenses, security teams can benefit from resources such as penetration testing methodology and vulnerability management programs to create a robust security posture.
The ongoing evolution of vulnerabilities, such as this one, necessitates continuous education and adaptation in security practices. Organizations should prioritize ongoing training for their security teams to remain ahead of emerging threats.
For further information on security services, organizations may explore red teaming services and other offerings that enhance security posture.
Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.
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