CVE-2018-9060 in r
Summary
by MITRE
R 3.4.4 suffers from a local buffer overflow that allows code execution.
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Analysis
by VulDB Data Team • 03/07/2023
The vulnerability identified as CVE-2018-9060 represents a critical local buffer overflow in the R statistical computing environment version 3.4.4. This flaw exists within the R interpreter's handling of certain input data structures, specifically affecting how the software processes and manages memory during data parsing operations. The buffer overflow occurs when R encounters malformed input that exceeds the allocated memory boundaries, creating opportunities for arbitrary code execution. The vulnerability stems from insufficient bounds checking in the memory allocation routines that process user-supplied data, particularly when dealing with compressed data formats and certain file parsing operations. This issue impacts all systems running R 3.4.4 and potentially earlier versions within the 3.4.x series, making it a widespread concern for statistical computing environments.
The technical implementation of this buffer overflow vulnerability involves the exploitation of memory management functions within R's core libraries where input data is processed without adequate validation of buffer limits. When maliciously crafted input data is processed by R's parsing functions, the software fails to properly validate the size of incoming data structures against allocated buffer space. This allows attackers to overwrite adjacent memory locations, potentially corrupting program execution flow or injecting malicious code into the running process. The vulnerability is classified under CWE-121 as a stack-based buffer overflow, where insufficient bounds checking permits data to be written beyond the allocated buffer boundaries, leading to memory corruption and potential code execution.
From an operational perspective, this vulnerability presents significant risks to organizations relying on R for data analysis, statistical modeling, and scientific computing tasks. The local nature of the exploit means that attackers must already have access to the system to leverage this vulnerability, but once compromised, the impact can be severe as it allows for privilege escalation and persistent access to the affected environment. The vulnerability affects not only individual users but also enterprise environments where R is used for data processing pipelines, automated analysis scripts, and statistical reporting systems. Organizations using R for sensitive data analysis or those with R installations on servers and workstations face potential exposure to data breaches, system compromise, and unauthorized access to analytical data. The exploitation of this vulnerability can lead to complete system compromise, particularly when R is used in automated environments or when users have elevated privileges.
Mitigation strategies for CVE-2018-9060 primarily focus on immediate software updates and system hardening measures. The most effective remediation involves upgrading to R version 3.5.0 or later, which includes patches addressing the buffer overflow conditions in memory management functions. Organizations should implement comprehensive patch management processes to ensure all R installations are updated promptly, particularly in environments where multiple users or automated processes interact with R. Additional protective measures include implementing input validation for all data processed by R, restricting user privileges when running R scripts, and employing sandboxing techniques to limit potential impact if exploitation occurs. System administrators should also consider monitoring for suspicious R process behavior and implementing network segmentation to limit lateral movement if a system becomes compromised. The vulnerability aligns with ATT&CK technique T1059.001 for command and script interpreter usage, as exploitation may involve running malicious R scripts to achieve code execution. Organizations should also implement security awareness training for users who work with R environments to prevent accidental exploitation through malicious data files or scripts.