CVE-2026-8727
Published: 19 May 2026
Summary
CVE-2026-8727 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Typo3 (inferred from references). Its CVSS base score is 7.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 30.6th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-30854
Vulnerability details
The Crawler extension passes the X-T3Crawler-Meta response header from crawled URLs directly to PHP's unserialize(). An attacker controlling a crawled endpoint can inject arbitrary serialized PHP objects, leading to Remote Code Execution on the TYPO3 server. Exploitation requires administrative privileges…
more
to configure a crawler-enabled page and trigger the crawl via a Scheduler task.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Deserialization of untrusted data (CWE-502) in a web crawler component directly enables RCE; requires prior admin access so maps to initial/privileged app exploitation plus command execution.
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.