CVE-2023-44351
Published: 17 November 2023
Summary
CVE-2023-44351 is a critical-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Adobe Coldfusion. Its CVSS base score is 9.8 (Critical).
Operationally, ranked in the top 3.1% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
Deeper analysis
Adobe ColdFusion versions 2023.5 and earlier along with 2021.11 and earlier contain a deserialization of untrusted data vulnerability, tracked as CVE-2023-44351 and CWE-502. The flaw carries a CVSS 3.1 score of 9.8 and permits arbitrary code execution when untrusted data is processed by the affected server components.
An unauthenticated attacker can exploit the issue over the network without any user interaction, achieving full control over confidentiality, integrity, and availability on the target system. The attack vector is rated as network-accessible with low complexity and no required privileges.
Adobe’s security bulletin APSB23-52, referenced at helpx.adobe.com/security/products/coldfusion/apsb23-52.html, supplies the official remediation guidance and patches for supported ColdFusion releases. The current EPSS score of 0.3201 has remained flat at its observed peak, indicating steady but not sharply increasing exploitation interest since disclosure.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-48705
Vulnerability details
Adobe ColdFusion versions 2023.5 (and earlier) and 2021.11 (and earlier) are affected by an Deserialization of Untrusted Data vulnerability that could result in Arbitrary code execution. Exploitation of this issue does not require user interaction.
- 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.