CVE-2023-36480
Published: 04 August 2023
Summary
CVE-2023-36480 is a critical-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Aerospike Aerospike Java Client. Its CVSS base score is 9.8 (Critical).
Operationally, ranked in the top 11.6% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-2318
Vulnerability details
The Aerospike Java client is a Java application that implements a network protocol to communicate with an Aerospike server. Prior to versions 7.0.0, 6.2.0, 5.2.0, and 4.5.0 some of the messages received from the server contain Java objects that the…
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client deserializes when it encounters them without further validation. Attackers that manage to trick clients into communicating with a malicious server can include especially crafted objects in its responses that, once deserialized by the client, force it to execute arbitrary code. This can be abused to take control of the machine the client is running on. Versions 7.0.0, 6.2.0, 5.2.0, and 4.5.0 contain a patch for this issue.
- 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.