CVE-2026-49740
Published: 09 June 2026
Summary
CVE-2026-49740 is a medium-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Typo3 CMS (inferred from references). Its CVSS base score is 6.3 (Medium).
Operationally, ranked at the 48.2th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-35401
Vulnerability details
TYPO3's cache frontend (VariableFrontend) and persistent key-value store (Registry) deserialized PHP payloads without integrity validation or class restrictions. An attacker with write access to the underlying storage backend (cache store or sys_registry database table) could inject a crafted serialized payload…
more
to trigger PHP Object Injection, potentially exploiting a gadget chain to achieve Remote Code Execution or other high-impact effects. Exploiting this vulnerability requires direct local write access to the storage, such as the SQL database or file system. This issue affects TYPO3 CMS versions before 10.4.57, 11.0.0-11.5.51, 12.0.0-12.4.46, 13.0.0-13.4.31 and 14.0.0-14.3.3.
- 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.