CVE-2021-34771
Published: 09 September 2021
Summary
CVE-2021-34771 is a medium-severity Insertion of Sensitive Information Into Sent Data (CWE-201) vulnerability in Cisco Ios Xr. Its CVSS base score is 5.5 (Medium).
Operationally, ranked at the 31.7th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2021-21421
Vulnerability details
A vulnerability in the Cisco IOS XR Software CLI could allow an authenticated, local attacker to view more information than their privileges allow. This vulnerability is due to insufficient application of restrictions during the execution of a specific command. An…
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attacker could exploit this vulnerability by running a specific command. A successful exploit could allow the attacker to view sensitive configuration information that their privileges might not otherwise allow them to access.
- 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.
Tainting directly detects exfiltration resulting from exposure of sensitive information to unauthorized actors.
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.