CVE-2021-1562
Published: 08 July 2021
Summary
CVE-2021-1562 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Cisco Broadworks Application Server. Its CVSS base score is 4.3 (Medium).
Operationally, ranked at the 43.1th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2021-7029
Vulnerability details
A vulnerability in the XSI-Actions interface of Cisco BroadWorks Application Server could allow an authenticated, remote attacker to access sensitive information on an affected system. This vulnerability is due to improper input validation and authorization of specific commands that a…
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user can execute within the XSI-Actions interface. An attacker could exploit this vulnerability by authenticating to an affected device and issuing a specific set of commands. A successful exploit could allow the attacker to join a Call Center instance and have calls that they do not have permissions to access distributed to them from the Call Center queue. At the time of publication, Cisco had not released updates that address this vulnerability for Cisco BroadWorks Application Server. However, firmware patches are available.
- 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.