CVE-2022-22183
Published: 14 April 2022
Summary
CVE-2022-22183 is a high-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Juniper Junos Os Evolved. Its CVSS base score is 7.5 (High).
Operationally, ranked in the top 21.0% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2022-27330
Vulnerability details
An Improper Access Control vulnerability in Juniper Networks Junos OS Evolved allows a network-based unauthenticated attacker who is able to connect to a specific open IPv4 port, which in affected releases should otherwise be unreachable, to cause the CPU to…
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consume all resources as more traffic is sent to the port to create a Denial of Service (DoS) condition. Continued receipt and processing of these packets will create a sustained Denial of Service (DoS) condition. This issue affects: Juniper Networks Junos OS Evolved 20.4 versions prior to 20.4R3-S2-EVO; 21.1 versions prior to 21.1R3-S1-EVO; 21.2 versions prior to 21.2R3-EVO; 21.3 versions prior to 21.3R2-EVO; 21.4 versions prior to 21.4R2-EVO. This issue does not affect Junos OS.
- 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.
Associating and retaining security attributes with data directly supports enforcement of access control decisions across storage, processing, and transmission.
Enforces rules governing access to the system and its data from external systems based on established trust relationships.
This control requires verifying that a sharing partner's access authorizations match the information's restrictions before sharing occurs.
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.