CVE-2022-22241
Published: 18 October 2022
Summary
CVE-2022-22241 is a high-severity Improper Input Validation (CWE-20) vulnerability in Juniper Junos. Its CVSS base score is 8.1 (High).
Operationally, ranked in the top 11.9% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2022-27388
Vulnerability details
An Improper Input Validation vulnerability in the J-Web component of Juniper Networks Junos OS may allow an unauthenticated attacker to access data without proper authorization. Utilizing a crafted POST request, deserialization may occur which could lead to unauthorized local file…
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access or the ability to execute arbitrary commands. This issue affects Juniper Networks Junos OS: all versions prior to 19.1R3-S9; 19.2 versions prior to 19.2R3-S6; 19.3 versions prior to 19.3R3-S7; 19.4 versions prior to 19.4R2-S7, 19.4R3-S9; 20.1 versions prior to 20.1R3-S5; 20.2 versions prior to 20.2R3-S5; 20.3 versions prior to 20.3R3-S5; 20.4 versions prior to 20.4R3-S4; 21.1 versions prior to 21.1R3-S2; 21.2 versions prior to 21.2R3-S1; 21.3 versions prior to 21.3R2-S2, 21.3R3; 21.4 versions prior to 21.4R1-S2, 21.4R2-S1, 21.4R3; 22.1 versions prior to 22.1R1-S1, 22.1R2.
- 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.
Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.
Directly implements checks on information inputs to reject invalid data before processing.
Penetration testing supplies malicious serialized objects, detecting unsafe deserialization and supporting corrective actions.
Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.
Untrusted serialized data can be deserialized and observed inside the chamber, blocking gadget-chain exploitation outside the sandbox.
Identifies and blocks malicious code introduced through deserialization of untrusted data at system boundaries.
Integrity verification of serialized information can detect tampering before deserialization occurs.
Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.