CVE-2021-44682
Published: 06 December 2021
Summary
CVE-2021-44682 is a critical-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Veritas Enterprise Vault. Its CVSS base score is 9.8 (Critical).
Operationally, ranked in the top 28.5% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2021-31500
Vulnerability details
An issue (6 of 6) was discovered in Veritas Enterprise Vault through 14.1.2. On start-up, the Enterprise Vault application starts several services that listen on random .NET Remoting TCP ports for possible commands from client applications. These TCP services can…
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be exploited due to deserialization behavior that is inherent to the .NET Remoting service. A malicious attacker can exploit both TCP remoting services and local IPC services on the Enterprise Vault Server. This vulnerability is mitigated by properly configuring the servers and firewall as described in the vendor's security alert for this vulnerability (VTS21-003, ZDI-CAN-14079).
- 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.