CVE-2017-3606 in Berkeley DB
Summary
by MITRE
Vulnerability in the Data Store component of Oracle Berkeley DB. The supported version that is affected is Prior to 6.2.32. Difficult to exploit vulnerability allows unauthenticated attacker with logon to the infrastructure where Data Store executes to compromise Data Store. Successful attacks require human interaction from a person other than the attacker. Successful attacks of this vulnerability can result in takeover of Data Store. CVSS 3.0 Base Score 7.0 (Confidentiality, Integrity and Availability impacts). CVSS Vector: (CVSS:3.0/AV:L/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H).
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Analysis
by VulDB Data Team • 11/29/2022
The vulnerability identified as CVE-2017-3606 resides within Oracle Berkeley DB's Data Store component, representing a significant security weakness that affects versions prior to 6.2.32. This issue manifests as a complex flaw in the database management system's architecture that creates a pathway for malicious actors to compromise the underlying data store infrastructure. The vulnerability's classification as difficult to exploit indicates that while the attack vector requires specific conditions, the potential impact remains severe enough to warrant immediate attention. The affected system components include the Data Store execution environment where database operations are processed, making this vulnerability particularly concerning for organizations relying on Berkeley DB for critical data storage operations.
The technical nature of this vulnerability stems from insufficient access controls and authentication mechanisms within the Data Store component, allowing an attacker who has already gained logon access to the infrastructure to escalate privileges and compromise the database system. This flaw operates under the principle that successful exploitation requires human interaction from someone other than the attacker, suggesting that the vulnerability may be triggered through social engineering or insider threats rather than purely automated attacks. The CVSS 3.0 scoring system assigns this vulnerability a base score of 7.0, reflecting high impacts across all three core security principles: confidentiality, integrity, and availability. The attack vector is classified as local access with high complexity requirements, indicating that the attacker needs physical or network-level access to the target system, while the need for user interaction suggests that the attack requires some form of human involvement beyond the initial compromise.
The operational impact of CVE-2017-3606 extends far beyond simple data theft, as successful exploitation can result in complete takeover of the Data Store system. This comprehensive compromise allows attackers to manipulate database contents, potentially altering critical business data, accessing sensitive information, or disrupting database operations entirely. The vulnerability's potential for system takeover aligns with CWE-284, which addresses improper access control issues, and demonstrates how inadequate privilege management can lead to complete system compromise. Organizations utilizing Oracle Berkeley DB in production environments face substantial risk from this vulnerability, particularly those with less stringent security controls or insufficient monitoring capabilities. The availability impact is particularly concerning as database outages can severely disrupt business operations, while the confidentiality and integrity impacts can lead to data breaches and regulatory compliance violations.
Mitigation strategies for this vulnerability must prioritize immediate patching of affected systems to versions 6.2.32 or later, as this represents the most effective solution to address the underlying flaw. System administrators should implement comprehensive monitoring and access control measures to detect potential exploitation attempts, including log analysis for unusual database activities and unauthorized access patterns. The vulnerability's requirement for human interaction suggests that employee awareness training and social engineering prevention measures should be strengthened to reduce the risk of insider threats. Organizations should also consider implementing network segmentation and least privilege access controls to limit the potential damage from any successful exploitation attempts. According to ATT&CK framework, this vulnerability maps to techniques involving privilege escalation and credential access, making it essential for security teams to monitor for these specific attack patterns. Regular security assessments and vulnerability scanning should be conducted to ensure that all instances of Oracle Berkeley DB are properly updated and monitored for similar vulnerabilities in the future.