CVE-2017-3607 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-2017-3607 resides within Oracle Berkeley DB's Data Store component, representing a significant security weakness that affects versions prior to 6.2.32. This issue falls under the category of software flaws that can be exploited by malicious actors with access to the underlying infrastructure where the database system operates. The vulnerability's classification as difficult to exploit indicates that while it requires specific conditions to be met, the potential impact when successfully exploited is severe and can lead to complete system compromise.
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 potentially take complete control of the database system. The CVSS 3.0 scoring of 7.0 reflects the high severity impact across all three core security principles: confidentiality, integrity, and availability. The attack vector is classified as local (AV:L) indicating that the attacker needs physical or network access to the system where the database operates, while the high attack complexity (AC:H) suggests that specialized knowledge or conditions are required for exploitation. The lack of required privileges (PR:N) means that no additional authentication is needed beyond initial system access, and the human interaction requirement (UI:R) indicates that a user action is necessary for successful exploitation, typically involving a specific sequence of operations or interactions with the database system.
The operational impact of this vulnerability is particularly concerning as it can result in complete takeover of the Data Store system, potentially leading to unauthorized data access, modification, or destruction. This compromise affects the fundamental security posture of any organization relying on Oracle Berkeley DB for data storage and management. The vulnerability's implications extend beyond simple data theft, as it can enable attackers to manipulate database contents, disrupt services, and potentially use the compromised system as a foothold for further attacks within the network infrastructure. Organizations utilizing affected versions face significant risk of data breaches and service disruptions, particularly in environments where database security is paramount.
Mitigation strategies for CVE-2017-3607 primarily focus on upgrading to Oracle Berkeley DB version 6.2.32 or later, which contains the necessary patches to address the identified vulnerability. System administrators should also implement additional security controls including network segmentation to limit access to database systems, strict access controls and monitoring of database activities, and regular security assessments to identify potential exploitation attempts. The vulnerability aligns with CWE-284, which addresses improper access control issues in software systems, and represents a clear example of how inadequate privilege management can lead to complete system compromise. From an ATT&CK framework perspective, this vulnerability could be leveraged during the privilege escalation and persistence phases, where an attacker who has already established initial access can use this weakness to gain deeper control over the target system. Organizations should also consider implementing intrusion detection systems and security monitoring solutions to detect potential exploitation attempts and maintain comprehensive audit trails of database activities to support incident response efforts.