Safety CI > dssg/triage

master

1 year, 7 months ago

python versions

scipy 1.8.0, scikit-learn 1.0.2 and mkdocs-material 8.2.12 have known security vulnerabilities.

Package	Installed	Affected	Info
scikit-learn	1.0.2	<1.5.0	show A sensitive data leakage vulnerability was identified in affected versions of scikit-learn TfidfVectorizer. The vulnerability arises from the unexpected storage of all tokens present in the training data within the `stop_words_` attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the `stop_words_` attribute could contain tokens that were meant to be discarded and not stored, such as passwords or keys. The impact of this vulnerability varies based on the nature of the data being processed by the vectorizer.
scikit-learn	1.0.2	<1.1.0rc1	show * Disputed * Scikit-learn 1.1.0rc1 includes a fix for CVE-2020-28975: svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn 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.
mkdocs-material	8.2.12	<9.5.5	show Mkdocs-material 9.5.5 includes a change in its dependency on Pillow. Previously set to approximately version 9.4, it has now been updated to version 10.22. This change was made in response to the security vulnerability identified as CVE-2023-504477. https://github.com/squidfunk/mkdocs-material/commit/fe11bc0cabd692d37bc4cc4e8034dbe6783ef36b
mkdocs-material	8.2.12	<9.1.13	show Mkdocs-material 9.1.13 includes a fix for a Race Condition Vulnerability. Social plugin triggers the race condition vulnerability when downloading fonts. https://github.com/squidfunk/mkdocs-material/issues/5515 https://github.com/squidfunk/mkdocs-material/issues/5521
mkdocs-material	8.2.12	<9.5.32	show MKDocs Material addresses an RXSS vulnerability found in deep links within search results.

master

1 year, 7 months ago

6fa104fb

uncomment tests for csvs

scipy 1.8.0, scikit-learn 1.0.2 and mkdocs-material 8.2.12 have known security vulnerabilities.

Package	Installed	Affected	Info
scikit-learn	1.0.2	<1.5.0	show A sensitive data leakage vulnerability was identified in affected versions of scikit-learn TfidfVectorizer. The vulnerability arises from the unexpected storage of all tokens present in the training data within the `stop_words_` attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the `stop_words_` attribute could contain tokens that were meant to be discarded and not stored, such as passwords or keys. The impact of this vulnerability varies based on the nature of the data being processed by the vectorizer.
scikit-learn	1.0.2	<1.1.0rc1	show * Disputed * Scikit-learn 1.1.0rc1 includes a fix for CVE-2020-28975: svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn 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.
mkdocs-material	8.2.12	<9.5.5	show Mkdocs-material 9.5.5 includes a change in its dependency on Pillow. Previously set to approximately version 9.4, it has now been updated to version 10.22. This change was made in response to the security vulnerability identified as CVE-2023-504477. https://github.com/squidfunk/mkdocs-material/commit/fe11bc0cabd692d37bc4cc4e8034dbe6783ef36b
mkdocs-material	8.2.12	<9.1.13	show Mkdocs-material 9.1.13 includes a fix for a Race Condition Vulnerability. Social plugin triggers the race condition vulnerability when downloading fonts. https://github.com/squidfunk/mkdocs-material/issues/5515 https://github.com/squidfunk/mkdocs-material/issues/5521
mkdocs-material	8.2.12	<9.5.32	show MKDocs Material addresses an RXSS vulnerability found in deep links within search results.

master

1 year, 7 months ago

f3ccae89

version of actions

scipy 1.8.0, scikit-learn 1.0.2 and mkdocs-material 8.2.12 have known security vulnerabilities.

Package	Installed	Affected	Info
scikit-learn	1.0.2	<1.5.0	show A sensitive data leakage vulnerability was identified in affected versions of scikit-learn TfidfVectorizer. The vulnerability arises from the unexpected storage of all tokens present in the training data within the `stop_words_` attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the `stop_words_` attribute could contain tokens that were meant to be discarded and not stored, such as passwords or keys. The impact of this vulnerability varies based on the nature of the data being processed by the vectorizer.
scikit-learn	1.0.2	<1.1.0rc1	show * Disputed * Scikit-learn 1.1.0rc1 includes a fix for CVE-2020-28975: svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn 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.
mkdocs-material	8.2.12	<9.5.5	show Mkdocs-material 9.5.5 includes a change in its dependency on Pillow. Previously set to approximately version 9.4, it has now been updated to version 10.22. This change was made in response to the security vulnerability identified as CVE-2023-504477. https://github.com/squidfunk/mkdocs-material/commit/fe11bc0cabd692d37bc4cc4e8034dbe6783ef36b
mkdocs-material	8.2.12	<9.1.13	show Mkdocs-material 9.1.13 includes a fix for a Race Condition Vulnerability. Social plugin triggers the race condition vulnerability when downloading fonts. https://github.com/squidfunk/mkdocs-material/issues/5515 https://github.com/squidfunk/mkdocs-material/issues/5521
mkdocs-material	8.2.12	<9.5.32	show MKDocs Material addresses an RXSS vulnerability found in deep links within search results.

master

1 year, 7 months ago

d668c1d9

comment tests

scipy 1.8.0, scikit-learn 1.0.2 and mkdocs-material 8.2.12 have known security vulnerabilities.

Package	Installed	Affected	Info
scikit-learn	1.0.2	<1.5.0	show A sensitive data leakage vulnerability was identified in affected versions of scikit-learn TfidfVectorizer. The vulnerability arises from the unexpected storage of all tokens present in the training data within the `stop_words_` attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the `stop_words_` attribute could contain tokens that were meant to be discarded and not stored, such as passwords or keys. The impact of this vulnerability varies based on the nature of the data being processed by the vectorizer.
scikit-learn	1.0.2	<1.1.0rc1	show * Disputed * Scikit-learn 1.1.0rc1 includes a fix for CVE-2020-28975: svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn 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.
mkdocs-material	8.2.12	<9.5.5	show Mkdocs-material 9.5.5 includes a change in its dependency on Pillow. Previously set to approximately version 9.4, it has now been updated to version 10.22. This change was made in response to the security vulnerability identified as CVE-2023-504477. https://github.com/squidfunk/mkdocs-material/commit/fe11bc0cabd692d37bc4cc4e8034dbe6783ef36b
mkdocs-material	8.2.12	<9.1.13	show Mkdocs-material 9.1.13 includes a fix for a Race Condition Vulnerability. Social plugin triggers the race condition vulnerability when downloading fonts. https://github.com/squidfunk/mkdocs-material/issues/5515 https://github.com/squidfunk/mkdocs-material/issues/5521
mkdocs-material	8.2.12	<9.5.32	show MKDocs Material addresses an RXSS vulnerability found in deep links within search results.

master

1 year, 7 months ago

01b66a5d

Bump 5.2.3 -> 5.3.0

scipy 1.8.0, scikit-learn 1.0.2 and mkdocs-material 8.2.12 have known security vulnerabilities.

Package	Installed	Affected	Info
scikit-learn	1.0.2	<1.5.0	show A sensitive data leakage vulnerability was identified in affected versions of scikit-learn TfidfVectorizer. The vulnerability arises from the unexpected storage of all tokens present in the training data within the `stop_words_` attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the `stop_words_` attribute could contain tokens that were meant to be discarded and not stored, such as passwords or keys. The impact of this vulnerability varies based on the nature of the data being processed by the vectorizer.
scikit-learn	1.0.2	<1.1.0rc1	show * Disputed * Scikit-learn 1.1.0rc1 includes a fix for CVE-2020-28975: svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn 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.
mkdocs-material	8.2.12	<9.5.5	show Mkdocs-material 9.5.5 includes a change in its dependency on Pillow. Previously set to approximately version 9.4, it has now been updated to version 10.22. This change was made in response to the security vulnerability identified as CVE-2023-504477. https://github.com/squidfunk/mkdocs-material/commit/fe11bc0cabd692d37bc4cc4e8034dbe6783ef36b
mkdocs-material	8.2.12	<9.1.13	show Mkdocs-material 9.1.13 includes a fix for a Race Condition Vulnerability. Social plugin triggers the race condition vulnerability when downloading fonts. https://github.com/squidfunk/mkdocs-material/issues/5515 https://github.com/squidfunk/mkdocs-material/issues/5521
mkdocs-material	8.2.12	<9.5.32	show MKDocs Material addresses an RXSS vulnerability found in deep links within search results.

master

1 year, 7 months ago

1fb375ef

Bump 5.2.3 -> 5.3.0

scipy 1.8.0, scikit-learn 1.0.2 and mkdocs-material 8.2.12 have known security vulnerabilities.

Package	Installed	Affected	Info
scikit-learn	1.0.2	<1.5.0	show A sensitive data leakage vulnerability was identified in affected versions of scikit-learn TfidfVectorizer. The vulnerability arises from the unexpected storage of all tokens present in the training data within the `stop_words_` attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the `stop_words_` attribute could contain tokens that were meant to be discarded and not stored, such as passwords or keys. The impact of this vulnerability varies based on the nature of the data being processed by the vectorizer.
scikit-learn	1.0.2	<1.1.0rc1	show * Disputed * Scikit-learn 1.1.0rc1 includes a fix for CVE-2020-28975: svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn 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.
mkdocs-material	8.2.12	<9.5.5	show Mkdocs-material 9.5.5 includes a change in its dependency on Pillow. Previously set to approximately version 9.4, it has now been updated to version 10.22. This change was made in response to the security vulnerability identified as CVE-2023-504477. https://github.com/squidfunk/mkdocs-material/commit/fe11bc0cabd692d37bc4cc4e8034dbe6783ef36b
mkdocs-material	8.2.12	<9.1.13	show Mkdocs-material 9.1.13 includes a fix for a Race Condition Vulnerability. Social plugin triggers the race condition vulnerability when downloading fonts. https://github.com/squidfunk/mkdocs-material/issues/5515 https://github.com/squidfunk/mkdocs-material/issues/5521
mkdocs-material	8.2.12	<9.5.32	show MKDocs Material addresses an RXSS vulnerability found in deep links within search results.

master

1 year, 7 months ago

04d5daa6

Bump version 5.2.3 -> 5.3.0

scipy 1.8.0, scikit-learn 1.0.2 and mkdocs-material 8.2.12 have known security vulnerabilities.

Package	Installed	Affected	Info
scikit-learn	1.0.2	<1.5.0	show A sensitive data leakage vulnerability was identified in affected versions of scikit-learn TfidfVectorizer. The vulnerability arises from the unexpected storage of all tokens present in the training data within the `stop_words_` attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the `stop_words_` attribute could contain tokens that were meant to be discarded and not stored, such as passwords or keys. The impact of this vulnerability varies based on the nature of the data being processed by the vectorizer.
scikit-learn	1.0.2	<1.1.0rc1	show * Disputed * Scikit-learn 1.1.0rc1 includes a fix for CVE-2020-28975: svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn 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.
mkdocs-material	8.2.12	<9.5.5	show Mkdocs-material 9.5.5 includes a change in its dependency on Pillow. Previously set to approximately version 9.4, it has now been updated to version 10.22. This change was made in response to the security vulnerability identified as CVE-2023-504477. https://github.com/squidfunk/mkdocs-material/commit/fe11bc0cabd692d37bc4cc4e8034dbe6783ef36b
mkdocs-material	8.2.12	<9.1.13	show Mkdocs-material 9.1.13 includes a fix for a Race Condition Vulnerability. Social plugin triggers the race condition vulnerability when downloading fonts. https://github.com/squidfunk/mkdocs-material/issues/5515 https://github.com/squidfunk/mkdocs-material/issues/5521
mkdocs-material	8.2.12	<9.5.32	show MKDocs Material addresses an RXSS vulnerability found in deep links within search results.

master

1 year, 7 months ago

718e4155

Merging dev into master, adding polars DF.

scipy 1.8.0, scikit-learn 1.0.2 and mkdocs-material 8.2.12 have known security vulnerabilities.

Package	Installed	Affected	Info
scikit-learn	1.0.2	<1.5.0	show A sensitive data leakage vulnerability was identified in affected versions of scikit-learn TfidfVectorizer. The vulnerability arises from the unexpected storage of all tokens present in the training data within the `stop_words_` attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the `stop_words_` attribute could contain tokens that were meant to be discarded and not stored, such as passwords or keys. The impact of this vulnerability varies based on the nature of the data being processed by the vectorizer.
scikit-learn	1.0.2	<1.1.0rc1	show * Disputed * Scikit-learn 1.1.0rc1 includes a fix for CVE-2020-28975: svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn 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.
mkdocs-material	8.2.12	<9.5.5	show Mkdocs-material 9.5.5 includes a change in its dependency on Pillow. Previously set to approximately version 9.4, it has now been updated to version 10.22. This change was made in response to the security vulnerability identified as CVE-2023-504477. https://github.com/squidfunk/mkdocs-material/commit/fe11bc0cabd692d37bc4cc4e8034dbe6783ef36b
mkdocs-material	8.2.12	<9.1.13	show Mkdocs-material 9.1.13 includes a fix for a Race Condition Vulnerability. Social plugin triggers the race condition vulnerability when downloading fonts. https://github.com/squidfunk/mkdocs-material/issues/5515 https://github.com/squidfunk/mkdocs-material/issues/5521
mkdocs-material	8.2.12	<9.5.32	show MKDocs Material addresses an RXSS vulnerability found in deep links within search results.

expand_feature_group_defs

1 year, 7 months ago

c4171f2b

update logging level

scipy 1.8.0, scikit-learn 1.0.2 and mkdocs-material 8.2.12 have known security vulnerabilities.

Package	Installed	Affected	Info
scikit-learn	1.0.2	<1.5.0	show A sensitive data leakage vulnerability was identified in affected versions of scikit-learn TfidfVectorizer. The vulnerability arises from the unexpected storage of all tokens present in the training data within the `stop_words_` attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the `stop_words_` attribute could contain tokens that were meant to be discarded and not stored, such as passwords or keys. The impact of this vulnerability varies based on the nature of the data being processed by the vectorizer.
scikit-learn	1.0.2	<1.1.0rc1	show * Disputed * Scikit-learn 1.1.0rc1 includes a fix for CVE-2020-28975: svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn 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.
mkdocs-material	8.2.12	<9.5.5	show Mkdocs-material 9.5.5 includes a change in its dependency on Pillow. Previously set to approximately version 9.4, it has now been updated to version 10.22. This change was made in response to the security vulnerability identified as CVE-2023-504477. https://github.com/squidfunk/mkdocs-material/commit/fe11bc0cabd692d37bc4cc4e8034dbe6783ef36b
mkdocs-material	8.2.12	<9.1.13	show Mkdocs-material 9.1.13 includes a fix for a Race Condition Vulnerability. Social plugin triggers the race condition vulnerability when downloading fonts. https://github.com/squidfunk/mkdocs-material/issues/5515 https://github.com/squidfunk/mkdocs-material/issues/5521
mkdocs-material	8.2.12	<9.5.32	show MKDocs Material addresses an RXSS vulnerability found in deep links within search results.

postmodeling_revision_2023

1 year, 7 months ago

80a0431d

postmodeling report subset fixes

scipy 1.8.0, scikit-learn 1.0.2 and mkdocs-material 8.2.12 have known security vulnerabilities.

Package	Installed	Affected	Info
scikit-learn	1.0.2	<1.5.0	show A sensitive data leakage vulnerability was identified in affected versions of scikit-learn TfidfVectorizer. The vulnerability arises from the unexpected storage of all tokens present in the training data within the `stop_words_` attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the `stop_words_` attribute could contain tokens that were meant to be discarded and not stored, such as passwords or keys. The impact of this vulnerability varies based on the nature of the data being processed by the vectorizer.
scikit-learn	1.0.2	<1.1.0rc1	show * Disputed * Scikit-learn 1.1.0rc1 includes a fix for CVE-2020-28975: svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn 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.
mkdocs-material	8.2.12	<9.5.5	show Mkdocs-material 9.5.5 includes a change in its dependency on Pillow. Previously set to approximately version 9.4, it has now been updated to version 10.22. This change was made in response to the security vulnerability identified as CVE-2023-504477. https://github.com/squidfunk/mkdocs-material/commit/fe11bc0cabd692d37bc4cc4e8034dbe6783ef36b
mkdocs-material	8.2.12	<9.1.13	show Mkdocs-material 9.1.13 includes a fix for a Race Condition Vulnerability. Social plugin triggers the race condition vulnerability when downloading fonts. https://github.com/squidfunk/mkdocs-material/issues/5515 https://github.com/squidfunk/mkdocs-material/issues/5521
mkdocs-material	8.2.12	<9.5.32	show MKDocs Material addresses an RXSS vulnerability found in deep links within search results.

pyup-scheduled-update-2024-01-01

1 year, 7 months ago

50b015bd

Update tox from 3.25.0 to 4.11.4

No dependencies with known security vulnerabilities.

pyup-scheduled-update-2024-01-01

1 year, 7 months ago

5842802d

Update flake8 from 4.0.1 to 6.1.0

No dependencies with known security vulnerabilities.

pyup-scheduled-update-2024-01-01

1 year, 7 months ago

74e7a63c

Update hypothesis from 6.46.1 to 6.92.2

No dependencies with known security vulnerabilities.

pyup-scheduled-update-2024-01-01

1 year, 7 months ago

c4731bec

Update fakeredis from 1.7.1 to 2.20.1

No dependencies with known security vulnerabilities.

pyup-scheduled-update-2024-01-01

1 year, 7 months ago

a3373d6c

Update pytest-cov from 3.0.0 to 4.1.0

No dependencies with known security vulnerabilities.