Safety CI > py4ds/nbless

pyup-update-tox-3.13.2-to-4.18.0

11 months, 1 week ago

Update tox from 3.13.2 to 4.18.0

click 7.0, black 19.3b0, numpy 1.16.4 and 3 other dependencies have known security vulnerabilities.

Package	Installed	Affected	Info
click	7.0	<8.0.0	show Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'. https://github.com/pallets/click/issues/1752
black	19.3b0	<24.3.0	show Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. NOTE: the vendor states that this reported code behavior is "completely harmless." https://github.com/numpy/numpy/issues/18993
numpy	1.16.4	<1.22.2	show Numpy 1.22.2 includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place. NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.
numpy	1.16.4	<1.21.0rc1	show Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user. https://github.com/numpy/numpy/issues/18939
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally). https://github.com/numpy/numpy/issues/19000
wheel	0.33.4	<0.38.1	show Wheel 0.38.1 includes a fix for CVE-2022-40898: An issue discovered in Python Packaging Authority (PyPA) Wheel 0.37.1 and earlier allows remote attackers to cause a denial of service via attacker controlled input to wheel cli. https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages
Sphinx	2.1.2	<3.0.4	show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.
Sphinx	2.1.2	<3.3.0	show Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in inventory. https://github.com/sphinx-doc/sphinx/issues/8175 https://github.com/sphinx-doc/sphinx/commit/f7b872e673f9b359a61fd287a7338a28077840d2
Sphinx	2.1.2	<3.3.0	show Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in docstring. https://github.com/sphinx-doc/sphinx/issues/8172 https://github.com/sphinx-doc/sphinx/commit/f00e75278c5999f40b214d8934357fbf0e705417
Sphinx	2.1.2	<3.0.4	show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.
twine	1.13.0	<2.0.0	show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix.

pyup-update-matplotlib-3.1.1-to-3.9.2

11 months, 2 weeks ago

74c5c704

Update matplotlib from 3.1.1 to 3.9.2

click 7.0, black 19.3b0, numpy 1.16.4 and 3 other dependencies have known security vulnerabilities.

Package	Installed	Affected	Info
click	7.0	<8.0.0	show Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'. https://github.com/pallets/click/issues/1752
black	19.3b0	<24.3.0	show Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. NOTE: the vendor states that this reported code behavior is "completely harmless." https://github.com/numpy/numpy/issues/18993
numpy	1.16.4	<1.22.2	show Numpy 1.22.2 includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place. NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.
numpy	1.16.4	<1.21.0rc1	show Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user. https://github.com/numpy/numpy/issues/18939
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally). https://github.com/numpy/numpy/issues/19000
wheel	0.33.4	<0.38.1	show Wheel 0.38.1 includes a fix for CVE-2022-40898: An issue discovered in Python Packaging Authority (PyPA) Wheel 0.37.1 and earlier allows remote attackers to cause a denial of service via attacker controlled input to wheel cli. https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages
Sphinx	2.1.2	<3.0.4	show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.
Sphinx	2.1.2	<3.3.0	show Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in inventory. https://github.com/sphinx-doc/sphinx/issues/8175 https://github.com/sphinx-doc/sphinx/commit/f7b872e673f9b359a61fd287a7338a28077840d2
Sphinx	2.1.2	<3.3.0	show Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in docstring. https://github.com/sphinx-doc/sphinx/issues/8172 https://github.com/sphinx-doc/sphinx/commit/f00e75278c5999f40b214d8934357fbf0e705417
Sphinx	2.1.2	<3.0.4	show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.
twine	1.13.0	<2.0.0	show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix.

pyup-update-tox-3.13.2-to-4.17.1

11 months, 2 weeks ago

cdfe10a1

Update tox from 3.13.2 to 4.17.1

click 7.0, black 19.3b0, numpy 1.16.4 and 3 other dependencies have known security vulnerabilities.

Package	Installed	Affected	Info
click	7.0	<8.0.0	show Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'. https://github.com/pallets/click/issues/1752
black	19.3b0	<24.3.0	show Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. NOTE: the vendor states that this reported code behavior is "completely harmless." https://github.com/numpy/numpy/issues/18993
numpy	1.16.4	<1.22.2	show Numpy 1.22.2 includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place. NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.
numpy	1.16.4	<1.21.0rc1	show Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user. https://github.com/numpy/numpy/issues/18939
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally). https://github.com/numpy/numpy/issues/19000
wheel	0.33.4	<0.38.1	show Wheel 0.38.1 includes a fix for CVE-2022-40898: An issue discovered in Python Packaging Authority (PyPA) Wheel 0.37.1 and earlier allows remote attackers to cause a denial of service via attacker controlled input to wheel cli. https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages
Sphinx	2.1.2	<3.0.4	show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.
Sphinx	2.1.2	<3.3.0	show Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in inventory. https://github.com/sphinx-doc/sphinx/issues/8175 https://github.com/sphinx-doc/sphinx/commit/f7b872e673f9b359a61fd287a7338a28077840d2
Sphinx	2.1.2	<3.3.0	show Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in docstring. https://github.com/sphinx-doc/sphinx/issues/8172 https://github.com/sphinx-doc/sphinx/commit/f00e75278c5999f40b214d8934357fbf0e705417
Sphinx	2.1.2	<3.0.4	show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.
twine	1.13.0	<2.0.0	show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix.

pyup-update-matplotlib-3.1.1-to-3.9.1.post1

11 months, 3 weeks ago

fa284d32

Update matplotlib from 3.1.1 to 3.9.1.post1

click 7.0, black 19.3b0, numpy 1.16.4 and 3 other dependencies have known security vulnerabilities.

Package	Installed	Affected	Info
click	7.0	<8.0.0	show Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'. https://github.com/pallets/click/issues/1752
black	19.3b0	<24.3.0	show Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. NOTE: the vendor states that this reported code behavior is "completely harmless." https://github.com/numpy/numpy/issues/18993
numpy	1.16.4	<1.22.2	show Numpy 1.22.2 includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place. NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.
numpy	1.16.4	<1.21.0rc1	show Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user. https://github.com/numpy/numpy/issues/18939
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally). https://github.com/numpy/numpy/issues/19000
wheel	0.33.4	<0.38.1	show Wheel 0.38.1 includes a fix for CVE-2022-40898: An issue discovered in Python Packaging Authority (PyPA) Wheel 0.37.1 and earlier allows remote attackers to cause a denial of service via attacker controlled input to wheel cli. https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages
Sphinx	2.1.2	<3.0.4	show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.
Sphinx	2.1.2	<3.3.0	show Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in inventory. https://github.com/sphinx-doc/sphinx/issues/8175 https://github.com/sphinx-doc/sphinx/commit/f7b872e673f9b359a61fd287a7338a28077840d2
Sphinx	2.1.2	<3.3.0	show Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in docstring. https://github.com/sphinx-doc/sphinx/issues/8172 https://github.com/sphinx-doc/sphinx/commit/f00e75278c5999f40b214d8934357fbf0e705417
Sphinx	2.1.2	<3.0.4	show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.
twine	1.13.0	<2.0.0	show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix.

pyup-update-tox-3.13.2-to-4.17.0

11 months, 3 weeks ago

ac34d877

Update tox from 3.13.2 to 4.17.0

click 7.0, black 19.3b0, numpy 1.16.4 and 3 other dependencies have known security vulnerabilities.

Package	Installed	Affected	Info
click	7.0	<8.0.0	show Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'. https://github.com/pallets/click/issues/1752
black	19.3b0	<24.3.0	show Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. NOTE: the vendor states that this reported code behavior is "completely harmless." https://github.com/numpy/numpy/issues/18993
numpy	1.16.4	<1.22.2	show Numpy 1.22.2 includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place. NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.
numpy	1.16.4	<1.21.0rc1	show Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user. https://github.com/numpy/numpy/issues/18939
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally). https://github.com/numpy/numpy/issues/19000
wheel	0.33.4	<0.38.1	show Wheel 0.38.1 includes a fix for CVE-2022-40898: An issue discovered in Python Packaging Authority (PyPA) Wheel 0.37.1 and earlier allows remote attackers to cause a denial of service via attacker controlled input to wheel cli. https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages
Sphinx	2.1.2	<3.0.4	show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.
Sphinx	2.1.2	<3.3.0	show Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in inventory. https://github.com/sphinx-doc/sphinx/issues/8175 https://github.com/sphinx-doc/sphinx/commit/f7b872e673f9b359a61fd287a7338a28077840d2
Sphinx	2.1.2	<3.3.0	show Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in docstring. https://github.com/sphinx-doc/sphinx/issues/8172 https://github.com/sphinx-doc/sphinx/commit/f00e75278c5999f40b214d8934357fbf0e705417
Sphinx	2.1.2	<3.0.4	show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.
twine	1.13.0	<2.0.0	show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix.

pyup-update-coverage-4.5.3-to-7.6.1

11 months, 3 weeks ago

62816c6a

Update coverage from 4.5.3 to 7.6.1

click 7.0, black 19.3b0, numpy 1.16.4 and 3 other dependencies have known security vulnerabilities.

Package	Installed	Affected	Info
click	7.0	<8.0.0	show Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'. https://github.com/pallets/click/issues/1752
black	19.3b0	<24.3.0	show Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. NOTE: the vendor states that this reported code behavior is "completely harmless." https://github.com/numpy/numpy/issues/18993
numpy	1.16.4	<1.22.2	show Numpy 1.22.2 includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place. NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.
numpy	1.16.4	<1.21.0rc1	show Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user. https://github.com/numpy/numpy/issues/18939
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally). https://github.com/numpy/numpy/issues/19000
wheel	0.33.4	<0.38.1	show Wheel 0.38.1 includes a fix for CVE-2022-40898: An issue discovered in Python Packaging Authority (PyPA) Wheel 0.37.1 and earlier allows remote attackers to cause a denial of service via attacker controlled input to wheel cli. https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages
Sphinx	2.1.2	<3.0.4	show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.
Sphinx	2.1.2	<3.3.0	show Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in inventory. https://github.com/sphinx-doc/sphinx/issues/8175 https://github.com/sphinx-doc/sphinx/commit/f7b872e673f9b359a61fd287a7338a28077840d2
Sphinx	2.1.2	<3.3.0	show Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in docstring. https://github.com/sphinx-doc/sphinx/issues/8172 https://github.com/sphinx-doc/sphinx/commit/f00e75278c5999f40b214d8934357fbf0e705417
Sphinx	2.1.2	<3.0.4	show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.
twine	1.13.0	<2.0.0	show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix.

pyup-update-wheel-0.33.4-to-0.44.0

11 months, 3 weeks ago

7595deb8

Update wheel from 0.33.4 to 0.44.0

click 7.0, black 19.3b0, numpy 1.16.4 and 2 other dependencies have known security vulnerabilities.

Package	Installed	Affected	Info
click	7.0	<8.0.0	show Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'. https://github.com/pallets/click/issues/1752
black	19.3b0	<24.3.0	show Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. NOTE: the vendor states that this reported code behavior is "completely harmless." https://github.com/numpy/numpy/issues/18993
numpy	1.16.4	<1.22.2	show Numpy 1.22.2 includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place. NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.
numpy	1.16.4	<1.21.0rc1	show Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user. https://github.com/numpy/numpy/issues/18939
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally). https://github.com/numpy/numpy/issues/19000
Sphinx	2.1.2	<3.0.4	show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.
Sphinx	2.1.2	<3.3.0	show Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in inventory. https://github.com/sphinx-doc/sphinx/issues/8175 https://github.com/sphinx-doc/sphinx/commit/f7b872e673f9b359a61fd287a7338a28077840d2
Sphinx	2.1.2	<3.3.0	show Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in docstring. https://github.com/sphinx-doc/sphinx/issues/8172 https://github.com/sphinx-doc/sphinx/commit/f00e75278c5999f40b214d8934357fbf0e705417
Sphinx	2.1.2	<3.0.4	show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.
twine	1.13.0	<2.0.0	show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix.

pyup-update-black-19.3b0-to-24.8.0

11 months, 3 weeks ago

26c9a620

Update black from 19.3b0 to 24.8.0

click 7.0, numpy 1.16.4, wheel 0.33.4 and 2 other dependencies have known security vulnerabilities.

Package	Installed	Affected	Info
click	7.0	<8.0.0	show Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'. https://github.com/pallets/click/issues/1752
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. NOTE: the vendor states that this reported code behavior is "completely harmless." https://github.com/numpy/numpy/issues/18993
numpy	1.16.4	<1.22.2	show Numpy 1.22.2 includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place. NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.
numpy	1.16.4	<1.21.0rc1	show Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user. https://github.com/numpy/numpy/issues/18939
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally). https://github.com/numpy/numpy/issues/19000
wheel	0.33.4	<0.38.1	show Wheel 0.38.1 includes a fix for CVE-2022-40898: An issue discovered in Python Packaging Authority (PyPA) Wheel 0.37.1 and earlier allows remote attackers to cause a denial of service via attacker controlled input to wheel cli. https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages
Sphinx	2.1.2	<3.0.4	show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.
Sphinx	2.1.2	<3.3.0	show Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in inventory. https://github.com/sphinx-doc/sphinx/issues/8175 https://github.com/sphinx-doc/sphinx/commit/f7b872e673f9b359a61fd287a7338a28077840d2
Sphinx	2.1.2	<3.3.0	show Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in docstring. https://github.com/sphinx-doc/sphinx/issues/8172 https://github.com/sphinx-doc/sphinx/commit/f00e75278c5999f40b214d8934357fbf0e705417
Sphinx	2.1.2	<3.0.4	show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.
twine	1.13.0	<2.0.0	show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix.

pyup-update-sphinx-2.1.2-to-8.0.2

11 months, 4 weeks ago

3ae2ef1d

Update sphinx from 2.1.2 to 8.0.2

click 7.0, black 19.3b0, numpy 1.16.4 and 2 other dependencies have known security vulnerabilities.

Package	Installed	Affected	Info
click	7.0	<8.0.0	show Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'. https://github.com/pallets/click/issues/1752
black	19.3b0	<24.3.0	show Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. NOTE: the vendor states that this reported code behavior is "completely harmless." https://github.com/numpy/numpy/issues/18993
numpy	1.16.4	<1.22.2	show Numpy 1.22.2 includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place. NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.
numpy	1.16.4	<1.21.0rc1	show Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user. https://github.com/numpy/numpy/issues/18939
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally). https://github.com/numpy/numpy/issues/19000
wheel	0.33.4	<0.38.1	show Wheel 0.38.1 includes a fix for CVE-2022-40898: An issue discovered in Python Packaging Authority (PyPA) Wheel 0.37.1 and earlier allows remote attackers to cause a denial of service via attacker controlled input to wheel cli. https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages
twine	1.13.0	<2.0.0	show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix.

pyup-update-pytest-5.0.1-to-8.3.2

12 months ago

6cc22086

Update pytest from 5.0.1 to 8.3.2

click 7.0, black 19.3b0, numpy 1.16.4 and 3 other dependencies have known security vulnerabilities.

Package	Installed	Affected	Info
click	7.0	<8.0.0	show Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'. https://github.com/pallets/click/issues/1752
black	19.3b0	<24.3.0	show Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. NOTE: the vendor states that this reported code behavior is "completely harmless." https://github.com/numpy/numpy/issues/18993
numpy	1.16.4	<1.22.2	show Numpy 1.22.2 includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place. NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.
numpy	1.16.4	<1.21.0rc1	show Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user. https://github.com/numpy/numpy/issues/18939
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally). https://github.com/numpy/numpy/issues/19000
wheel	0.33.4	<0.38.1	show Wheel 0.38.1 includes a fix for CVE-2022-40898: An issue discovered in Python Packaging Authority (PyPA) Wheel 0.37.1 and earlier allows remote attackers to cause a denial of service via attacker controlled input to wheel cli. https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages
Sphinx	2.1.2	<3.0.4	show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.
Sphinx	2.1.2	<3.3.0	show Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in inventory. https://github.com/sphinx-doc/sphinx/issues/8175 https://github.com/sphinx-doc/sphinx/commit/f7b872e673f9b359a61fd287a7338a28077840d2
Sphinx	2.1.2	<3.3.0	show Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in docstring. https://github.com/sphinx-doc/sphinx/issues/8172 https://github.com/sphinx-doc/sphinx/commit/f00e75278c5999f40b214d8934357fbf0e705417
Sphinx	2.1.2	<3.0.4	show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.
twine	1.13.0	<2.0.0	show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix.

pyup-update-numpy-1.16.4-to-2.0.1

1 year ago

e7f465e3

Update numpy from 1.16.4 to 2.0.1

click 7.0, black 19.3b0, wheel 0.33.4 and 2 other dependencies have known security vulnerabilities.

Package	Installed	Affected	Info
click	7.0	<8.0.0	show Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'. https://github.com/pallets/click/issues/1752
black	19.3b0	<24.3.0	show Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.
wheel	0.33.4	<0.38.1	show Wheel 0.38.1 includes a fix for CVE-2022-40898: An issue discovered in Python Packaging Authority (PyPA) Wheel 0.37.1 and earlier allows remote attackers to cause a denial of service via attacker controlled input to wheel cli. https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages
Sphinx	2.1.2	<3.0.4	show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.
Sphinx	2.1.2	<3.3.0	show Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in inventory. https://github.com/sphinx-doc/sphinx/issues/8175 https://github.com/sphinx-doc/sphinx/commit/f7b872e673f9b359a61fd287a7338a28077840d2
Sphinx	2.1.2	<3.3.0	show Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in docstring. https://github.com/sphinx-doc/sphinx/issues/8172 https://github.com/sphinx-doc/sphinx/commit/f00e75278c5999f40b214d8934357fbf0e705417
Sphinx	2.1.2	<3.0.4	show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.
twine	1.13.0	<2.0.0	show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix.

pyup-update-sphinx-2.1.2-to-7.4.7

1 year ago

5897c981

Update sphinx from 2.1.2 to 7.4.7

click 7.0, black 19.3b0, numpy 1.16.4 and 2 other dependencies have known security vulnerabilities.

Package	Installed	Affected	Info
click	7.0	<8.0.0	show Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'. https://github.com/pallets/click/issues/1752
black	19.3b0	<24.3.0	show Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. NOTE: the vendor states that this reported code behavior is "completely harmless." https://github.com/numpy/numpy/issues/18993
numpy	1.16.4	<1.22.2	show Numpy 1.22.2 includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place. NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.
numpy	1.16.4	<1.21.0rc1	show Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user. https://github.com/numpy/numpy/issues/18939
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally). https://github.com/numpy/numpy/issues/19000
wheel	0.33.4	<0.38.1	show Wheel 0.38.1 includes a fix for CVE-2022-40898: An issue discovered in Python Packaging Authority (PyPA) Wheel 0.37.1 and earlier allows remote attackers to cause a denial of service via attacker controlled input to wheel cli. https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages
twine	1.13.0	<2.0.0	show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix.

pyup-update-pytest-5.0.1-to-8.3.1

1 year ago

dea74ad1

Update pytest from 5.0.1 to 8.3.1

click 7.0, black 19.3b0, numpy 1.16.4 and 3 other dependencies have known security vulnerabilities.

Package	Installed	Affected	Info
click	7.0	<8.0.0	show Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'. https://github.com/pallets/click/issues/1752
black	19.3b0	<24.3.0	show Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. NOTE: the vendor states that this reported code behavior is "completely harmless." https://github.com/numpy/numpy/issues/18993
numpy	1.16.4	<1.22.2	show Numpy 1.22.2 includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place. NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.
numpy	1.16.4	<1.21.0rc1	show Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user. https://github.com/numpy/numpy/issues/18939
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally). https://github.com/numpy/numpy/issues/19000
wheel	0.33.4	<0.38.1	show Wheel 0.38.1 includes a fix for CVE-2022-40898: An issue discovered in Python Packaging Authority (PyPA) Wheel 0.37.1 and earlier allows remote attackers to cause a denial of service via attacker controlled input to wheel cli. https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages
Sphinx	2.1.2	<3.0.4	show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.
Sphinx	2.1.2	<3.3.0	show Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in inventory. https://github.com/sphinx-doc/sphinx/issues/8175 https://github.com/sphinx-doc/sphinx/commit/f7b872e673f9b359a61fd287a7338a28077840d2
Sphinx	2.1.2	<3.3.0	show Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in docstring. https://github.com/sphinx-doc/sphinx/issues/8172 https://github.com/sphinx-doc/sphinx/commit/f00e75278c5999f40b214d8934357fbf0e705417
Sphinx	2.1.2	<3.0.4	show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.
twine	1.13.0	<2.0.0	show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix.

pyup-update-sphinx-2.1.2-to-7.4.6

1 year ago

f3ce32ef

Update sphinx from 2.1.2 to 7.4.6

click 7.0, black 19.3b0, numpy 1.16.4 and 2 other dependencies have known security vulnerabilities.

Package	Installed	Affected	Info
click	7.0	<8.0.0	show Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'. https://github.com/pallets/click/issues/1752
black	19.3b0	<24.3.0	show Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. NOTE: the vendor states that this reported code behavior is "completely harmless." https://github.com/numpy/numpy/issues/18993
numpy	1.16.4	<1.22.2	show Numpy 1.22.2 includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place. NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.
numpy	1.16.4	<1.21.0rc1	show Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user. https://github.com/numpy/numpy/issues/18939
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally). https://github.com/numpy/numpy/issues/19000
wheel	0.33.4	<0.38.1	show Wheel 0.38.1 includes a fix for CVE-2022-40898: An issue discovered in Python Packaging Authority (PyPA) Wheel 0.37.1 and earlier allows remote attackers to cause a denial of service via attacker controlled input to wheel cli. https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages
twine	1.13.0	<2.0.0	show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix.

pyup-update-sphinx-2.1.2-to-7.4.5

1 year ago

7e7065be

Update sphinx from 2.1.2 to 7.4.5

click 7.0, black 19.3b0, numpy 1.16.4 and 2 other dependencies have known security vulnerabilities.

Package	Installed	Affected	Info
click	7.0	<8.0.0	show Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'. https://github.com/pallets/click/issues/1752
black	19.3b0	<24.3.0	show Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. NOTE: the vendor states that this reported code behavior is "completely harmless." https://github.com/numpy/numpy/issues/18993
numpy	1.16.4	<1.22.2	show Numpy 1.22.2 includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place. NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.
numpy	1.16.4	<1.21.0rc1	show Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user. https://github.com/numpy/numpy/issues/18939
numpy	1.16.4	<1.22.0	show Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally). https://github.com/numpy/numpy/issues/19000
wheel	0.33.4	<0.38.1	show Wheel 0.38.1 includes a fix for CVE-2022-40898: An issue discovered in Python Packaging Authority (PyPA) Wheel 0.37.1 and earlier allows remote attackers to cause a denial of service via attacker controlled input to wheel cli. https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages
twine	1.13.0	<2.0.0	show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix.