CVE-2023-44350
Published: 17 November 2023
Summary
CVE-2023-44350 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 1.6% 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 CWE-502. The flaw is rated 9.8 under CVSS 3.1 with an attack vector of network, low complexity, no privileges, and no user interaction, resulting in full confidentiality, integrity, and availability impact through arbitrary code execution.
An unauthenticated remote attacker can supply a malicious serialized object to an affected ColdFusion instance and trigger code execution without any user interaction or authentication. Successful exploitation grants the attacker complete control over the server process and underlying system.
The official Adobe advisory at https://helpx.adobe.com/security/products/coldfusion/apsb23-52.html details the available patches and recommended remediation steps for both supported branches. The associated EPSS score has remained at 0.6189 with no material increase after disclosure.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-48704
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.