CVE-2021-34749
Published: 18 August 2021
Summary
CVE-2021-34749 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Cisco Firepower Management Center Virtual Appliance Firmware. Its CVSS base score is 5.8 (Medium).
Operationally, ranked in the top 15.2% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2021-21399
Vulnerability details
A vulnerability in Server Name Identification (SNI) request filtering of Cisco Web Security Appliance (WSA), Cisco Firepower Threat Defense (FTD), and the Snort detection engine could allow an unauthenticated, remote attacker to bypass filtering technology on an affected device and…
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exfiltrate data from a compromised host. This vulnerability is due to inadequate filtering of the SSL handshake. An attacker could exploit this vulnerability by using data from the SSL client hello packet to communicate with an external server. A successful exploit could allow the attacker to execute a command-and-control attack on a compromised host and perform additional data exfiltration attacks.
- 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.