Lookup for vulnerable packages by Package URL.
| Purl | pkg:pypi/scikit-learn@0.15.0b2 |
| Type | pypi |
| Namespace | |
| Name | scikit-learn |
| Version | 0.15.0b2 |
| Qualifiers |
|
| Subpath | |
| Is_vulnerable | true |
| Next_non_vulnerable_version | 1.5.0 |
| Latest_non_vulnerable_version | 1.5.0 |
| Affected_by_vulnerabilities |
| 0 |
| url |
VCID-fcrh-qvee-ryhf |
| vulnerability_id |
VCID-fcrh-qvee-ryhf |
| summary |
scikit-learn (aka sklearn) through 0.23.0 can unserialize and execute commands from an untrusted file that is passed to the joblib.load() function, if __reduce__ makes an os.system call. NOTE: third parties dispute this issue because the joblib.load() function is documented as unsafe and it is the user's responsibility to use the function in a secure manner |
| references |
|
| fixed_packages |
|
| aliases |
CVE-2020-13092, GHSA-jjw5-xxj6-pcv5, PYSEC-2020-107
|
| risk_score |
null |
| exploitability |
0.5 |
| weighted_severity |
0.0 |
| resource_url |
http://public2.vulnerablecode.io/vulnerabilities/VCID-fcrh-qvee-ryhf |
|
| 1 |
| url |
VCID-fd91-hz39-73fy |
| vulnerability_id |
VCID-fd91-hz39-73fy |
| summary |
svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn 0.23.2 and other products, allows attackers to cause a denial of service (segmentation fault) via a crafted model SVM (introduced via pickle, json, or any other model permanence standard) with a large value in the _n_support array. NOTE: the scikit-learn vendor's position is that the behavior can only occur if the library's API is violated by an application that changes a private attribute. |
| references |
|
| fixed_packages |
|
| aliases |
CVE-2020-28975, GHSA-jxfp-4rvq-9h9m, PYSEC-2020-108
|
| risk_score |
4.0 |
| exploitability |
0.5 |
| weighted_severity |
8.0 |
| resource_url |
http://public2.vulnerablecode.io/vulnerabilities/VCID-fd91-hz39-73fy |
|
|
| Fixing_vulnerabilities |
|
| Risk_score | 4.0 |
| Resource_url | http://public2.vulnerablecode.io/packages/pkg:pypi/scikit-learn@0.15.0b2 |