CVE-2022-3342
Published: 20 October 2023
Summary
CVE-2022-3342 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Automattic Jetpack Crm. Its CVSS base score is 7.5 (High).
Operationally, ranked in the top 17.8% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2022-42729
Vulnerability details
The Jetpack CRM plugin for WordPress is vulnerable to PHAR deserialization via the ‘zbscrmcsvimpf’ parameter in the 'zeroBSCRM_CSVImporterLitehtml_app' function in versions up to, and including, 5.3.1. While the function performs a nonce check, steps 2 and 3 of the check…
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do not take any action upon a failed check. These steps then perform a 'file_exists' check on the value of 'zbscrmcsvimpf'. If a phar:// archive is supplied, its contents will be deserialized and an object injected in the execution stream. This allows an unauthenticated attacker to obtain object injection if they are able to upload a phar archive (for instance if the site supports image uploads) and then trick an administrator into performing an action, such as clicking a link.
- 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.