CVE-2022-29972 in Simba Amazon Redshift ODBC Driver
Summary
by MITRE • 05/09/2022
An argument injection vulnerability in the browser-based authentication component of the Magnitude Simba Amazon Redshift ODBC Driver (1.4.14 through 1.4.21.1001 and 1.4.22 through 1.4.x before 1.4.52) may allow a local user to execute arbitrary code.
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Analysis
by VulDB Data Team • 05/12/2022
The CVE-2022-29972 vulnerability represents a critical argument injection flaw within the browser-based authentication component of the Magnitude Simba Amazon Redshift ODBC Driver. This vulnerability affects specific versions ranging from 1.4.14 through 1.4.21.1001 and 1.4.22 through 1.4.x before 1.4.52, creating a significant security risk for organizations utilizing Amazon Redshift database connections. The flaw exists in how the driver processes authentication arguments, particularly within its browser-based authentication mechanism that facilitates secure database access through web interfaces.
The technical implementation of this vulnerability stems from insufficient input validation and sanitization within the authentication component. When the driver processes authentication parameters, it fails to properly escape or validate user-supplied arguments that are passed to underlying system calls or command executions. This creates an environment where maliciously crafted input can be interpreted as additional command-line arguments or parameters, effectively allowing an attacker to inject arbitrary commands into the authentication process. The vulnerability is classified as an argument injection issue that aligns with CWE-77, which specifically addresses command injection through improper argument handling in software components.
From an operational perspective, this vulnerability presents a severe risk to database security infrastructure as it enables local privilege escalation through arbitrary code execution. An attacker with local access to a system running the affected driver could potentially execute malicious code with the privileges of the authenticated user or service account. The impact extends beyond simple code execution to include potential data exfiltration, system compromise, and lateral movement within network environments where Redshift databases are accessed. The browser-based authentication component makes this particularly dangerous as it may be accessible through web interfaces or integrated development environments that users interact with regularly.
The attack surface for this vulnerability is particularly concerning given the widespread use of Amazon Redshift and ODBC drivers in enterprise environments. Organizations that rely on database connectivity through these components face potential exploitation through various attack vectors including social engineering, compromised user accounts, or insider threats. The vulnerability's classification under ATT&CK technique T1059.003 for command and scripting interpreter demonstrates how attackers could leverage this flaw to execute malicious commands through the compromised authentication flow. Security professionals should consider this vulnerability as part of broader attack chains that could lead to full system compromise or data breaches.
Mitigation strategies for CVE-2022-29972 should prioritize immediate patching of affected versions to 1.4.52 or later, as provided by the vendor. Organizations should also implement network segmentation to limit access to systems running the affected driver, particularly those with database connectivity. Additional controls include monitoring for unusual authentication patterns, implementing strict input validation for all user-supplied parameters, and conducting regular vulnerability assessments of database connectivity components. The remediation process should include comprehensive testing of patched versions to ensure no regression in functionality while maintaining the security improvements. Security teams should also consider implementing privileged access management solutions to limit the potential impact of successful exploitation attempts.