CVE-2018-1000048 in RtRetrievalFramework
Summary
by MITRE
NASA RtRetrievalFramework version v1.0 contains a CWE-502 vulnerability in Data retrieval functionality of RtRetrieval framework that can result in remote code execution. This attack appear to be exploitable via Victim tries to retrieve and process a weather data file.
If you want to get the best quality for vulnerability data then you always have to consider VulDB.
Analysis
by VulDB Data Team • 01/03/2020
The CVE-2018-1000048 vulnerability resides within NASA's RtRetrievalFramework version v1.0, specifically targeting the data retrieval functionality that processes weather data files. This vulnerability represents a critical security flaw classified under CWE-502, which pertains to deserialization of untrusted data. The framework's implementation fails to properly validate and sanitize data inputs during the retrieval process, creating a pathway for malicious actors to exploit the system through carefully crafted weather data files. The vulnerability's exploitation occurs when the system attempts to process and deserialize data from external sources, particularly weather data files that may contain malicious serialized objects designed to execute arbitrary code on the target system. This deserialization flaw enables attackers to bypass normal security controls and gain unauthorized access to the underlying system.
The technical execution of this vulnerability follows a well-established pattern that aligns with ATT&CK framework techniques categorized under T1203 and T1059, where adversaries leverage deserialization vulnerabilities to achieve remote code execution. When the RtRetrievalFramework processes a maliciously crafted weather data file, the deserialization mechanism attempts to reconstruct objects from the serialized data stream without proper validation. This allows attackers to inject malicious code that executes with the privileges of the application process, potentially leading to complete system compromise. The vulnerability is particularly dangerous because it operates within a legitimate data processing workflow, making it difficult to detect through traditional network monitoring or intrusion detection systems. The attack vector is specifically exploitable via victim systems attempting to retrieve and process weather data files, which are commonly used in scientific and meteorological applications where data integrity and source verification are paramount.
The operational impact of CVE-2018-1000048 extends beyond simple remote code execution, as it can enable attackers to establish persistent access to affected systems and potentially escalate privileges within the network. Organizations using NASA's RtRetrievalFramework for weather data processing face significant risks including data exfiltration, system compromise, and potential lateral movement within their infrastructure. The vulnerability's exploitation can result in unauthorized access to sensitive meteorological data, disruption of critical weather monitoring systems, and potential compromise of research data repositories. Given that this framework is used in scientific and research environments, the impact could be particularly severe as it may affect weather forecasting systems, climate research databases, and other critical infrastructure components that rely on accurate and secure data processing. The vulnerability's classification as a remote code execution flaw means that attackers can potentially compromise systems from external networks without requiring physical access or prior authentication.
Mitigation strategies for CVE-2018-1000048 should focus on implementing robust input validation and sanitization mechanisms within the RtRetrievalFramework's data processing pipeline. Organizations should immediately update to patched versions of the framework, if available, or implement network segmentation to isolate systems using this component from critical network segments. The implementation of strict data validation protocols, including content type checking and digital signature verification for weather data files, can significantly reduce exploitation risks. Security controls should also include monitoring for unusual data processing patterns and implementing application whitelisting to prevent execution of unauthorized code. Additionally, organizations should conduct thorough vulnerability assessments of their scientific data processing systems and implement regular security audits to identify similar deserialization vulnerabilities in other components. The remediation process should also include comprehensive staff training on secure coding practices and the importance of validating all external data inputs to prevent similar vulnerabilities from emerging in other applications.