Raw vector
CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:L/I:N/A:NCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
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, exploitation aligns with the MITRE ATT&CK technique Junk Data (T1001.001); ranked at the 42th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-0292
Vulnerability Data
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
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
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.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
PR.PS-02 addresses only post-deployment updates/patching and cannot prevent introduction of unsafe deserialization code, yet it can remediate some instances when the flaw exists in outdated libraries or components.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.