CVE-2017-3617 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-2017-3617 resides within Oracle Berkeley DB's Data Store component, representing a significant security weakness that affects versions prior to 6.2.32. This database system serves as a foundational element for numerous applications requiring embedded database functionality, making this flaw particularly concerning for organizations relying on Berkeley DB for critical data storage operations. The vulnerability's classification as difficult to exploit indicates that while the attack surface exists, it requires specific conditions to be met for successful compromise. The CVSS 3.0 score of 7.0 reflects a high severity rating that encompasses impacts to confidentiality, integrity, and availability, demonstrating the comprehensive nature of potential damage.
The technical flaw manifests as a privilege escalation vulnerability that can be leveraged by an attacker who already possesses logon credentials to the system where the Data Store component operates. This requirement for existing system access aligns with the CVSS vector's AV:L classification, indicating local attack scope. The attack complexity is rated as high (AC:H) due to the specific conditions needed for exploitation, while the lack of required privileges (PR:N) suggests that no additional authentication is necessary once initial access is obtained. The human interaction requirement (UI:R) implies that successful exploitation depends on some form of user involvement beyond the automated attack process, potentially through social engineering or specific operational procedures that must be manipulated.
The operational impact of this vulnerability extends far beyond simple data compromise, as successful exploitation can result in complete takeover of the Data Store component. This represents a critical escalation from mere data theft to system control, allowing attackers to manipulate database operations, modify data structures, and potentially use the compromised system as a pivot point for broader network attacks. The confidentiality, integrity, and availability impacts are all rated as high (C:H, I:H, A:H), indicating that attackers can access sensitive data, modify database contents, and potentially render the database service unavailable. This vulnerability directly impacts the foundational security of applications that depend on Berkeley DB for their data persistence mechanisms.
Organizations should prioritize immediate patching of affected systems to address this vulnerability, as the risk of exploitation increases with the duration of exposure. The remediation process must include comprehensive testing of patched systems to ensure that the update does not introduce compatibility issues with existing applications. Security teams should implement network segmentation and monitoring to detect potential exploitation attempts, particularly focusing on unusual database access patterns and unauthorized logon activities. The vulnerability's characteristics align with ATT&CK technique T1068, which involves exploiting vulnerabilities in legitimate programs to gain system access, and CWE-284, which addresses improper access control in software systems. Organizations should also consider implementing additional security controls such as database activity monitoring, access logging, and regular security assessments to reduce the overall risk exposure.