CVE-2022-21828
Published: 04 March 2022
Summary
CVE-2022-21828 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Ivanti Incapptic Connect. Its CVSS base score is 7.2 (High).
Operationally, ranked in the top 5.2% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
Deeper analysis
CVE-2022-21828 is a remote code execution vulnerability affecting the Incapptic Connect web console in versions 1.40.0, 1.39.1, 1.39.0, 1.38.1, 1.38.0, 1.37.1, 1.37.0, 1.36.0, 1.35.5, 1.35.4, and 1.35.3. The flaw is associated with CWE-502 and carries a CVSS 3.1 base score of 7.2, reflecting network-accessible attack vectors that require high privileges but no user interaction.
An authenticated user with high-privilege access to the web console can leverage an unspecified attack vector to execute arbitrary code on the underlying Incapptic Connect server, resulting in full compromise of confidentiality, integrity, and availability on the host.
Vendor advisories addressing the issue are published by Ivanti under reference SA-2022-02-23 and are available at https://forums.ivanti.com/s/article/SA-2022-02-23?language=en_US. The EPSS score for this CVE has remained in the 0.15–0.17 range without a pronounced upward trajectory after disclosure.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2022-26987
Vulnerability details
A user with high privilege access to the Incapptic Connect web console can remotely execute code on the Incapptic Connect server using a unspecified attack vector in Incapptic Connect version 1.40.0, 1.39.1, 1.39.0, 1.38.1, 1.38.0, 1.37.1, 1.37.0, 1.36.0, 1.35.5, 1.35.4…
more
and 1.35.3.
- 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.
Penetration testing supplies malicious serialized objects, detecting unsafe deserialization and supporting corrective actions.
Evaluation of untrusted data handling (deserialization testing) reveals unsafe processing, which the required remediation process addresses.
Untrusted serialized data can be deserialized and observed inside the chamber, blocking gadget-chain exploitation outside the sandbox.
Validates or rejects untrusted serialized data before deserialization occurs.
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.
Provenance of associated data allows detection of untrusted sources before deserialization or processing occurs.