CVE-2024-27281
Published: 14 May 2024
Summary
CVE-2024-27281 is a medium-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Hackerone (inferred from references). Its CVSS base score is 4.5 (Medium).
Operationally, ranked in the top 14.2% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-0826
Vulnerability details
An issue was discovered in RDoc 6.3.3 through 6.6.2, as distributed in Ruby 3.x through 3.3.0. When parsing .rdoc_options (used for configuration in RDoc) as a YAML file, object injection and resultant remote code execution are possible because there are…
more
no restrictions on the classes that can be restored. (When loading the documentation cache, object injection and resultant remote code execution are also possible if there were a crafted cache.) The main fixed version is 6.6.3.1. For Ruby 3.0 users, a fixed version is rdoc 6.3.4.1. For Ruby 3.1 users, a fixed version is rdoc 6.4.1.1. For Ruby 3.2 users, a fixed version is rdoc 6.5.1.1.
- 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.