CVE-2023-45805
Published: 20 October 2023
Summary
CVE-2023-45805 is a high-severity Improper Input Validation (CWE-20) vulnerability in Frostming Pdm. Its CVSS base score is 7.8 (High).
Operationally, ranked at the 28.9th 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-2023-2755
Vulnerability details
pdm is a Python package and dependency manager supporting the latest PEP standards. It's possible to craft a malicious `pdm.lock` file that could allow e.g. an insider or a malicious open source project to appear to depend on a trusted…
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PyPI project, but actually install another project. A project `foo` can be targeted by creating the project `foo-2` and uploading the file `foo-2-2.tar.gz` to pypi.org. PyPI will see this as project `foo-2` version `2`, while PDM will see this as project `foo` version `2-2`. The version must only be `parseable as a version` and the filename must be a prefix of the project name, but it's not verified to match the version being installed. Version `2-2` is also not a valid normalized version per PEP 440. Matching the project name exactly (not just prefix) would fix the issue. When installing dependencies with PDM, what's actually installed could differ from what's listed in `pyproject.toml` (including arbitrary code execution on install). It could also be used for downgrade attacks by only changing the version. This issue has been addressed in commit `6853e2642df` which is included in release version `2.9.4`. 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.
Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.
Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.
Directly implements checks on information inputs to reject invalid data before processing.
Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.