CVE-2023-49297
Published: 05 December 2023
Summary
CVE-2023-49297 is a low-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Iterative Pydrive2. Its CVSS base score is 3.3 (Low).
Operationally, ranked at the 28.5th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-0292
Vulnerability details
PyDrive2 is a wrapper library of google-api-python-client that simplifies many common Google Drive API V2 tasks. Unsafe YAML deserilization will result in arbitrary code execution. A maliciously crafted YAML file can cause arbitrary code execution if PyDrive2 is run in…
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the same directory as it, or if it is loaded in via `LoadSettingsFile`. This is a deserilization attack that will affect any user who initializes GoogleAuth from this package while a malicious yaml file is present in the same directory. This vulnerability does not require the file to be directly loaded through the code, only present. This issue has been addressed in commit `c57355dc` which is included in release version `1.16.2`. Users are advised to upgrade. There are no known workarounds for this vulnerability.
- 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.