CVE-2023-20055
Published: 23 March 2023
Summary
CVE-2023-20055 is a high-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Cisco Catalyst Center. Its CVSS base score is 8.0 (High).
Operationally, ranked in the top 28.4% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-24234
Vulnerability details
A vulnerability in the management API of Cisco DNA Center could allow an authenticated, remote attacker to elevate privileges in the context of the web-based management interface on an affected device. This vulnerability is due to the unintended exposure of…
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sensitive information. An attacker could exploit this vulnerability by inspecting the responses from the API. Under certain circumstances, a successful exploit could allow the attacker to access the API with the privileges of a higher-level user account. To successfully exploit this vulnerability, the attacker would need at least valid Observer credentials.
- CWE(s)
Related Threats
No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Automated marking applies security attributes to system outputs, making it harder for attackers to exploit unmarked sensitive information leading to unauthorized exposure.
Proper attribute retention and permitted-value enforcement limits unauthorized actors from accessing sensitive information lacking correct labels.
Prevents unauthorized exposure of sensitive information by prohibiting untrusted external systems from processing or storing it.
By enforcing authorization matching prior to sharing, the control reduces the risk of exposing sensitive information to unauthorized actors.
Review and removal of nonpublic information from publicly accessible systems directly prevents exposure of sensitive data to unauthorized actors.
Data mining protection mechanisms detect and block unauthorized bulk extraction of sensitive data, directly mitigating exposure to unauthorized actors.
Literacy training teaches users to recognize and avoid actions that result in unauthorized exposure of sensitive information.
Retaining and monitoring training records confirms personnel have completed privacy and security awareness training on handling sensitive data, reducing the chance of unauthorized exposure due to lack of knowledge.