CVE-2020-15523 (GCVE-0-2020-15523)
Vulnerability from cvelistv5 – Published: 2020-07-04 22:54 – Updated: 2026-10-08 21:03
VLAI
EPSS
VEX
Summary
In Python 3.6 through 3.6.10, 3.7 through 3.7.8, 3.8 through 3.8.4rc1, and 3.9 through 3.9.0b4 on Windows, a Trojan horse python3.dll might be used in cases where CPython is embedded in a native application. This occurs because python3X.dll may use an invalid search path for python3.dll loading (after Py_SetPath has been used). NOTE: this issue CANNOT occur when using python.exe from a standard (non-embedded) Python installation on Windows.
Severity
No CVSS data available.
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-08 21:01 UTC
CWE
- n/a
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://bugs.python.org/issue29778 | x_refsource_MISC |
| https://github.com/python/cpython/pull/21297 | x_refsource_MISC |
| https://security.netapp.com/advisory/ntap-2021031… | x_refsource_CONFIRM |
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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