pyup-update-coverage-4.5.1-to-7.5.2
9 months, 3 weeks ago
Update coverage from 4.5.1 to 7.5.2
scipy 1.1.0, tqdm 4.25.0 and 5 other dependencies have known security vulnerabilities.
| Package | Installed | Affected | Info |
|---|---|---|---|
| tqdm | 4.25.0 | <4.66.3 |
show Tqdm version 4.66.3 addresses CVE-2024-34062, a vulnerability where optional non-boolean CLI arguments like `--delim`, `--buf-size`, and `--manpath` were passed through Python's `eval`, allowing for arbitrary code execution. This security risk, only locally exploitable, has been mitigated in this release. Users are advised to upgrade to version 4.66.3 immediately as there are no workarounds for this issue. |
| numpy | 1.15.2 | <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 | 1.15.2 | <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 | 1.15.2 | <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 |
| numpy | 1.15.2 | <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 | 1.15.2 | <1.16.3 |
show Numpy 1.16.3 includes a fix for CVE-2019-6446: It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call. NOTE: Third parties dispute this issue because it is a behavior that might have legitimate applications in (for example) loading serialized Python object arrays from trusted and authenticated sources. https://github.com/numpy/numpy/commit/89b688732b37616c9d26623f81aaee1703c30ffb |
| wheel | 0.31.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| Sphinx | 1.8.1 | <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 | 1.8.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| twine | 1.12.1 | <2.0.0 |
show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix. |
| nbdime | 1.0.2 | >=0,<1.1.1 , >=2.0.0,<2.1.1 , >=3.0.0,<3.1.1 |
show nbdime provides tools for diffing and merging of Jupyter Notebooks. In affected versions a stored cross-site scripting (XSS) issue exists within the Jupyter-owned nbdime project. It appears that when reading the file name and path from disk, the extension does not sanitize the string it constructs before returning it to be displayed. The diffNotebookCheckpoint function within nbdime causes this issue. When attempting to display the name of the local notebook (diffNotebookCheckpoint), nbdime appears to simply append .ipynb to the name of the input file. The NbdimeWidget is then created, and the base string is passed through to the request API function. From there, the frontend simply renders the HTML tag and anything along with it. Users are advised to patch to the most recent version of the affected product. |
pyup-update-watchdog-0.9.0-to-4.0.1
9 months, 3 weeks ago
Update watchdog from 0.9.0 to 4.0.1
scipy 1.1.0, tqdm 4.25.0 and 5 other dependencies have known security vulnerabilities.
| Package | Installed | Affected | Info |
|---|---|---|---|
| tqdm | 4.25.0 | <4.66.3 |
show Tqdm version 4.66.3 addresses CVE-2024-34062, a vulnerability where optional non-boolean CLI arguments like `--delim`, `--buf-size`, and `--manpath` were passed through Python's `eval`, allowing for arbitrary code execution. This security risk, only locally exploitable, has been mitigated in this release. Users are advised to upgrade to version 4.66.3 immediately as there are no workarounds for this issue. |
| numpy | 1.15.2 | <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 | 1.15.2 | <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 | 1.15.2 | <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 |
| numpy | 1.15.2 | <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 | 1.15.2 | <1.16.3 |
show Numpy 1.16.3 includes a fix for CVE-2019-6446: It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call. NOTE: Third parties dispute this issue because it is a behavior that might have legitimate applications in (for example) loading serialized Python object arrays from trusted and authenticated sources. https://github.com/numpy/numpy/commit/89b688732b37616c9d26623f81aaee1703c30ffb |
| wheel | 0.31.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| Sphinx | 1.8.1 | <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 | 1.8.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| twine | 1.12.1 | <2.0.0 |
show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix. |
| nbdime | 1.0.2 | >=0,<1.1.1 , >=2.0.0,<2.1.1 , >=3.0.0,<3.1.1 |
show nbdime provides tools for diffing and merging of Jupyter Notebooks. In affected versions a stored cross-site scripting (XSS) issue exists within the Jupyter-owned nbdime project. It appears that when reading the file name and path from disk, the extension does not sanitize the string it constructs before returning it to be displayed. The diffNotebookCheckpoint function within nbdime causes this issue. When attempting to display the name of the local notebook (diffNotebookCheckpoint), nbdime appears to simply append .ipynb to the name of the input file. The NbdimeWidget is then created, and the base string is passed through to the request API function. From there, the frontend simply renders the HTML tag and anything along with it. Users are advised to patch to the most recent version of the affected product. |
pyup-update-scipy-1.1.0-to-1.13.1
9 months, 3 weeks ago
Update scipy from 1.1.0 to 1.13.1
tqdm 4.25.0, numpy 1.15.2 and 4 other dependencies have known security vulnerabilities.
| Package | Installed | Affected | Info |
|---|---|---|---|
| tqdm | 4.25.0 | <4.66.3 |
show Tqdm version 4.66.3 addresses CVE-2024-34062, a vulnerability where optional non-boolean CLI arguments like `--delim`, `--buf-size`, and `--manpath` were passed through Python's `eval`, allowing for arbitrary code execution. This security risk, only locally exploitable, has been mitigated in this release. Users are advised to upgrade to version 4.66.3 immediately as there are no workarounds for this issue. |
| numpy | 1.15.2 | <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 | 1.15.2 | <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 | 1.15.2 | <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 |
| numpy | 1.15.2 | <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 | 1.15.2 | <1.16.3 |
show Numpy 1.16.3 includes a fix for CVE-2019-6446: It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call. NOTE: Third parties dispute this issue because it is a behavior that might have legitimate applications in (for example) loading serialized Python object arrays from trusted and authenticated sources. https://github.com/numpy/numpy/commit/89b688732b37616c9d26623f81aaee1703c30ffb |
| wheel | 0.31.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| Sphinx | 1.8.1 | <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 | 1.8.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| twine | 1.12.1 | <2.0.0 |
show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix. |
| nbdime | 1.0.2 | >=0,<1.1.1 , >=2.0.0,<2.1.1 , >=3.0.0,<3.1.1 |
show nbdime provides tools for diffing and merging of Jupyter Notebooks. In affected versions a stored cross-site scripting (XSS) issue exists within the Jupyter-owned nbdime project. It appears that when reading the file name and path from disk, the extension does not sanitize the string it constructs before returning it to be displayed. The diffNotebookCheckpoint function within nbdime causes this issue. When attempting to display the name of the local notebook (diffNotebookCheckpoint), nbdime appears to simply append .ipynb to the name of the input file. The NbdimeWidget is then created, and the base string is passed through to the request API function. From there, the frontend simply renders the HTML tag and anything along with it. Users are advised to patch to the most recent version of the affected product. |
pyup-update-pytest-3.8.1-to-8.2.1
9 months, 4 weeks ago
Update pytest from 3.8.1 to 8.2.1
scipy 1.1.0, tqdm 4.25.0 and 5 other dependencies have known security vulnerabilities.
| Package | Installed | Affected | Info |
|---|---|---|---|
| tqdm | 4.25.0 | <4.66.3 |
show Tqdm version 4.66.3 addresses CVE-2024-34062, a vulnerability where optional non-boolean CLI arguments like `--delim`, `--buf-size`, and `--manpath` were passed through Python's `eval`, allowing for arbitrary code execution. This security risk, only locally exploitable, has been mitigated in this release. Users are advised to upgrade to version 4.66.3 immediately as there are no workarounds for this issue. |
| numpy | 1.15.2 | <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 | 1.15.2 | <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 | 1.15.2 | <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 |
| numpy | 1.15.2 | <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 | 1.15.2 | <1.16.3 |
show Numpy 1.16.3 includes a fix for CVE-2019-6446: It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call. NOTE: Third parties dispute this issue because it is a behavior that might have legitimate applications in (for example) loading serialized Python object arrays from trusted and authenticated sources. https://github.com/numpy/numpy/commit/89b688732b37616c9d26623f81aaee1703c30ffb |
| wheel | 0.31.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| Sphinx | 1.8.1 | <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 | 1.8.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| twine | 1.12.1 | <2.0.0 |
show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix. |
| nbdime | 1.0.2 | >=0,<1.1.1 , >=2.0.0,<2.1.1 , >=3.0.0,<3.1.1 |
show nbdime provides tools for diffing and merging of Jupyter Notebooks. In affected versions a stored cross-site scripting (XSS) issue exists within the Jupyter-owned nbdime project. It appears that when reading the file name and path from disk, the extension does not sanitize the string it constructs before returning it to be displayed. The diffNotebookCheckpoint function within nbdime causes this issue. When attempting to display the name of the local notebook (diffNotebookCheckpoint), nbdime appears to simply append .ipynb to the name of the input file. The NbdimeWidget is then created, and the base string is passed through to the request API function. From there, the frontend simply renders the HTML tag and anything along with it. Users are advised to patch to the most recent version of the affected product. |
pyup-update-twine-1.12.1-to-5.1.0
10 months ago
Update twine from 1.12.1 to 5.1.0
scipy 1.1.0, tqdm 4.25.0 and 4 other dependencies have known security vulnerabilities.
| Package | Installed | Affected | Info |
|---|---|---|---|
| tqdm | 4.25.0 | <4.66.3 |
show Tqdm version 4.66.3 addresses CVE-2024-34062, a vulnerability where optional non-boolean CLI arguments like `--delim`, `--buf-size`, and `--manpath` were passed through Python's `eval`, allowing for arbitrary code execution. This security risk, only locally exploitable, has been mitigated in this release. Users are advised to upgrade to version 4.66.3 immediately as there are no workarounds for this issue. |
| numpy | 1.15.2 | <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 | 1.15.2 | <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 | 1.15.2 | <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 |
| numpy | 1.15.2 | <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 | 1.15.2 | <1.16.3 |
show Numpy 1.16.3 includes a fix for CVE-2019-6446: It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call. NOTE: Third parties dispute this issue because it is a behavior that might have legitimate applications in (for example) loading serialized Python object arrays from trusted and authenticated sources. https://github.com/numpy/numpy/commit/89b688732b37616c9d26623f81aaee1703c30ffb |
| wheel | 0.31.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| Sphinx | 1.8.1 | <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 | 1.8.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| nbdime | 1.0.2 | >=0,<1.1.1 , >=2.0.0,<2.1.1 , >=3.0.0,<3.1.1 |
show nbdime provides tools for diffing and merging of Jupyter Notebooks. In affected versions a stored cross-site scripting (XSS) issue exists within the Jupyter-owned nbdime project. It appears that when reading the file name and path from disk, the extension does not sanitize the string it constructs before returning it to be displayed. The diffNotebookCheckpoint function within nbdime causes this issue. When attempting to display the name of the local notebook (diffNotebookCheckpoint), nbdime appears to simply append .ipynb to the name of the input file. The NbdimeWidget is then created, and the base string is passed through to the request API function. From there, the frontend simply renders the HTML tag and anything along with it. Users are advised to patch to the most recent version of the affected product. |
pyup-update-matplotlib-3.0.0-to-3.9.0
10 months ago
Update matplotlib from 3.0.0 to 3.9.0
scipy 1.1.0, tqdm 4.25.0 and 5 other dependencies have known security vulnerabilities.
| Package | Installed | Affected | Info |
|---|---|---|---|
| tqdm | 4.25.0 | <4.66.3 |
show Tqdm version 4.66.3 addresses CVE-2024-34062, a vulnerability where optional non-boolean CLI arguments like `--delim`, `--buf-size`, and `--manpath` were passed through Python's `eval`, allowing for arbitrary code execution. This security risk, only locally exploitable, has been mitigated in this release. Users are advised to upgrade to version 4.66.3 immediately as there are no workarounds for this issue. |
| numpy | 1.15.2 | <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 | 1.15.2 | <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 | 1.15.2 | <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 |
| numpy | 1.15.2 | <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 | 1.15.2 | <1.16.3 |
show Numpy 1.16.3 includes a fix for CVE-2019-6446: It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call. NOTE: Third parties dispute this issue because it is a behavior that might have legitimate applications in (for example) loading serialized Python object arrays from trusted and authenticated sources. https://github.com/numpy/numpy/commit/89b688732b37616c9d26623f81aaee1703c30ffb |
| wheel | 0.31.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| Sphinx | 1.8.1 | <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 | 1.8.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| twine | 1.12.1 | <2.0.0 |
show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix. |
| nbdime | 1.0.2 | >=0,<1.1.1 , >=2.0.0,<2.1.1 , >=3.0.0,<3.1.1 |
show nbdime provides tools for diffing and merging of Jupyter Notebooks. In affected versions a stored cross-site scripting (XSS) issue exists within the Jupyter-owned nbdime project. It appears that when reading the file name and path from disk, the extension does not sanitize the string it constructs before returning it to be displayed. The diffNotebookCheckpoint function within nbdime causes this issue. When attempting to display the name of the local notebook (diffNotebookCheckpoint), nbdime appears to simply append .ipynb to the name of the input file. The NbdimeWidget is then created, and the base string is passed through to the request API function. From there, the frontend simply renders the HTML tag and anything along with it. Users are advised to patch to the most recent version of the affected product. |
pyup-update-coverage-4.5.1-to-7.5.1
10 months, 2 weeks ago
Update coverage from 4.5.1 to 7.5.1
scipy 1.1.0, tqdm 4.25.0 and 5 other dependencies have known security vulnerabilities.
| Package | Installed | Affected | Info |
|---|---|---|---|
| tqdm | 4.25.0 | <4.66.3 |
show Tqdm version 4.66.3 addresses CVE-2024-34062, a vulnerability where optional non-boolean CLI arguments like `--delim`, `--buf-size`, and `--manpath` were passed through Python's `eval`, allowing for arbitrary code execution. This security risk, only locally exploitable, has been mitigated in this release. Users are advised to upgrade to version 4.66.3 immediately as there are no workarounds for this issue. |
| numpy | 1.15.2 | <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 | 1.15.2 | <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 | 1.15.2 | <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 |
| numpy | 1.15.2 | <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 | 1.15.2 | <1.16.3 |
show Numpy 1.16.3 includes a fix for CVE-2019-6446: It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call. NOTE: Third parties dispute this issue because it is a behavior that might have legitimate applications in (for example) loading serialized Python object arrays from trusted and authenticated sources. https://github.com/numpy/numpy/commit/89b688732b37616c9d26623f81aaee1703c30ffb |
| wheel | 0.31.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| Sphinx | 1.8.1 | <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 | 1.8.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| twine | 1.12.1 | <2.0.0 |
show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix. |
| nbdime | 1.0.2 | >=0,<1.1.1 , >=2.0.0,<2.1.1 , >=3.0.0,<3.1.1 |
show nbdime provides tools for diffing and merging of Jupyter Notebooks. In affected versions a stored cross-site scripting (XSS) issue exists within the Jupyter-owned nbdime project. It appears that when reading the file name and path from disk, the extension does not sanitize the string it constructs before returning it to be displayed. The diffNotebookCheckpoint function within nbdime causes this issue. When attempting to display the name of the local notebook (diffNotebookCheckpoint), nbdime appears to simply append .ipynb to the name of the input file. The NbdimeWidget is then created, and the base string is passed through to the request API function. From there, the frontend simply renders the HTML tag and anything along with it. Users are advised to patch to the most recent version of the affected product. |
pyup-update-tqdm-4.25.0-to-4.66.4
10 months, 2 weeks ago
Update tqdm from 4.25.0 to 4.66.4
scipy 1.1.0, numpy 1.15.2 and 4 other dependencies have known security vulnerabilities.
| Package | Installed | Affected | Info |
|---|---|---|---|
| numpy | 1.15.2 | <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 | 1.15.2 | <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 | 1.15.2 | <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 |
| numpy | 1.15.2 | <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 | 1.15.2 | <1.16.3 |
show Numpy 1.16.3 includes a fix for CVE-2019-6446: It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call. NOTE: Third parties dispute this issue because it is a behavior that might have legitimate applications in (for example) loading serialized Python object arrays from trusted and authenticated sources. https://github.com/numpy/numpy/commit/89b688732b37616c9d26623f81aaee1703c30ffb |
| wheel | 0.31.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| Sphinx | 1.8.1 | <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 | 1.8.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| twine | 1.12.1 | <2.0.0 |
show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix. |
| nbdime | 1.0.2 | >=0,<1.1.1 , >=2.0.0,<2.1.1 , >=3.0.0,<3.1.1 |
show nbdime provides tools for diffing and merging of Jupyter Notebooks. In affected versions a stored cross-site scripting (XSS) issue exists within the Jupyter-owned nbdime project. It appears that when reading the file name and path from disk, the extension does not sanitize the string it constructs before returning it to be displayed. The diffNotebookCheckpoint function within nbdime causes this issue. When attempting to display the name of the local notebook (diffNotebookCheckpoint), nbdime appears to simply append .ipynb to the name of the input file. The NbdimeWidget is then created, and the base string is passed through to the request API function. From there, the frontend simply renders the HTML tag and anything along with it. Users are advised to patch to the most recent version of the affected product. |
pyup-update-wurlitzer-1.0.2-to-3.1.0
10 months, 2 weeks ago
Update wurlitzer from 1.0.2 to 3.1.0
scipy 1.1.0, numpy 1.15.2 and 4 other dependencies have known security vulnerabilities.
| Package | Installed | Affected | Info |
|---|---|---|---|
| numpy | 1.15.2 | <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 | 1.15.2 | <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 | 1.15.2 | <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 |
| numpy | 1.15.2 | <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 | 1.15.2 | <1.16.3 |
show Numpy 1.16.3 includes a fix for CVE-2019-6446: It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call. NOTE: Third parties dispute this issue because it is a behavior that might have legitimate applications in (for example) loading serialized Python object arrays from trusted and authenticated sources. https://github.com/numpy/numpy/commit/89b688732b37616c9d26623f81aaee1703c30ffb |
| wheel | 0.31.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| Sphinx | 1.8.1 | <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 | 1.8.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| twine | 1.12.1 | <2.0.0 |
show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix. |
| nbdime | 1.0.2 | >=0,<1.1.1 , >=2.0.0,<2.1.1 , >=3.0.0,<3.1.1 |
show nbdime provides tools for diffing and merging of Jupyter Notebooks. In affected versions a stored cross-site scripting (XSS) issue exists within the Jupyter-owned nbdime project. It appears that when reading the file name and path from disk, the extension does not sanitize the string it constructs before returning it to be displayed. The diffNotebookCheckpoint function within nbdime causes this issue. When attempting to display the name of the local notebook (diffNotebookCheckpoint), nbdime appears to simply append .ipynb to the name of the input file. The NbdimeWidget is then created, and the base string is passed through to the request API function. From there, the frontend simply renders the HTML tag and anything along with it. Users are advised to patch to the most recent version of the affected product. |
pyup-update-pytest-3.8.1-to-8.2.0
10 months, 2 weeks ago
Update pytest from 3.8.1 to 8.2.0
scipy 1.1.0, numpy 1.15.2 and 4 other dependencies have known security vulnerabilities.
| Package | Installed | Affected | Info |
|---|---|---|---|
| numpy | 1.15.2 | <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 | 1.15.2 | <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 | 1.15.2 | <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 |
| numpy | 1.15.2 | <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 | 1.15.2 | <1.16.3 |
show Numpy 1.16.3 includes a fix for CVE-2019-6446: It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call. NOTE: Third parties dispute this issue because it is a behavior that might have legitimate applications in (for example) loading serialized Python object arrays from trusted and authenticated sources. https://github.com/numpy/numpy/commit/89b688732b37616c9d26623f81aaee1703c30ffb |
| wheel | 0.31.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| Sphinx | 1.8.1 | <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 | 1.8.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| twine | 1.12.1 | <2.0.0 |
show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix. |
| nbdime | 1.0.2 | >=0,<1.1.1 , >=2.0.0,<2.1.1 , >=3.0.0,<3.1.1 |
show nbdime provides tools for diffing and merging of Jupyter Notebooks. In affected versions a stored cross-site scripting (XSS) issue exists within the Jupyter-owned nbdime project. It appears that when reading the file name and path from disk, the extension does not sanitize the string it constructs before returning it to be displayed. The diffNotebookCheckpoint function within nbdime causes this issue. When attempting to display the name of the local notebook (diffNotebookCheckpoint), nbdime appears to simply append .ipynb to the name of the input file. The NbdimeWidget is then created, and the base string is passed through to the request API function. From there, the frontend simply renders the HTML tag and anything along with it. Users are advised to patch to the most recent version of the affected product. |
pyup-update-pytest-3.8.1-to-8.1.2
10 months, 3 weeks ago
Update pytest from 3.8.1 to 8.1.2
scipy 1.1.0, numpy 1.15.2 and 4 other dependencies have known security vulnerabilities.
| Package | Installed | Affected | Info |
|---|---|---|---|
| numpy | 1.15.2 | <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 | 1.15.2 | <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 | 1.15.2 | <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 |
| numpy | 1.15.2 | <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 | 1.15.2 | <1.16.3 |
show Numpy 1.16.3 includes a fix for CVE-2019-6446: It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call. NOTE: Third parties dispute this issue because it is a behavior that might have legitimate applications in (for example) loading serialized Python object arrays from trusted and authenticated sources. https://github.com/numpy/numpy/commit/89b688732b37616c9d26623f81aaee1703c30ffb |
| wheel | 0.31.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| Sphinx | 1.8.1 | <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 | 1.8.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| twine | 1.12.1 | <2.0.0 |
show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix. |
| nbdime | 1.0.2 | >=0,<1.1.1 , >=2.0.0,<2.1.1 , >=3.0.0,<3.1.1 |
show nbdime provides tools for diffing and merging of Jupyter Notebooks. In affected versions a stored cross-site scripting (XSS) issue exists within the Jupyter-owned nbdime project. It appears that when reading the file name and path from disk, the extension does not sanitize the string it constructs before returning it to be displayed. The diffNotebookCheckpoint function within nbdime causes this issue. When attempting to display the name of the local notebook (diffNotebookCheckpoint), nbdime appears to simply append .ipynb to the name of the input file. The NbdimeWidget is then created, and the base string is passed through to the request API function. From there, the frontend simply renders the HTML tag and anything along with it. Users are advised to patch to the most recent version of the affected product. |
pyup-update-coverage-4.5.1-to-7.5.0
10 months, 3 weeks ago
Update coverage from 4.5.1 to 7.5.0
scipy 1.1.0, numpy 1.15.2 and 4 other dependencies have known security vulnerabilities.
| Package | Installed | Affected | Info |
|---|---|---|---|
| numpy | 1.15.2 | <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 | 1.15.2 | <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 | 1.15.2 | <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 |
| numpy | 1.15.2 | <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 | 1.15.2 | <1.16.3 |
show Numpy 1.16.3 includes a fix for CVE-2019-6446: It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call. NOTE: Third parties dispute this issue because it is a behavior that might have legitimate applications in (for example) loading serialized Python object arrays from trusted and authenticated sources. https://github.com/numpy/numpy/commit/89b688732b37616c9d26623f81aaee1703c30ffb |
| wheel | 0.31.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| Sphinx | 1.8.1 | <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 | 1.8.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| twine | 1.12.1 | <2.0.0 |
show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix. |
| nbdime | 1.0.2 | >=0,<1.1.1 , >=2.0.0,<2.1.1 , >=3.0.0,<3.1.1 |
show nbdime provides tools for diffing and merging of Jupyter Notebooks. In affected versions a stored cross-site scripting (XSS) issue exists within the Jupyter-owned nbdime project. It appears that when reading the file name and path from disk, the extension does not sanitize the string it constructs before returning it to be displayed. The diffNotebookCheckpoint function within nbdime causes this issue. When attempting to display the name of the local notebook (diffNotebookCheckpoint), nbdime appears to simply append .ipynb to the name of the input file. The NbdimeWidget is then created, and the base string is passed through to the request API function. From there, the frontend simply renders the HTML tag and anything along with it. Users are advised to patch to the most recent version of the affected product. |
pyup-update-scikit-image-0.14.0-to-0.23.2
10 months, 4 weeks ago
Update scikit-image from 0.14.0 to 0.23.2
scipy 1.1.0, numpy 1.15.2 and 4 other dependencies have known security vulnerabilities.
| Package | Installed | Affected | Info |
|---|---|---|---|
| numpy | 1.15.2 | <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 | 1.15.2 | <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 | 1.15.2 | <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 |
| numpy | 1.15.2 | <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 | 1.15.2 | <1.16.3 |
show Numpy 1.16.3 includes a fix for CVE-2019-6446: It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call. NOTE: Third parties dispute this issue because it is a behavior that might have legitimate applications in (for example) loading serialized Python object arrays from trusted and authenticated sources. https://github.com/numpy/numpy/commit/89b688732b37616c9d26623f81aaee1703c30ffb |
| wheel | 0.31.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| Sphinx | 1.8.1 | <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 | 1.8.1 | <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 | 1.8.1 | <3.0.4 |
show Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons. |
| twine | 1.12.1 | <2.0.0 |
show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix. |
| nbdime | 1.0.2 | >=0,<1.1.1 , >=2.0.0,<2.1.1 , >=3.0.0,<3.1.1 |
show nbdime provides tools for diffing and merging of Jupyter Notebooks. In affected versions a stored cross-site scripting (XSS) issue exists within the Jupyter-owned nbdime project. It appears that when reading the file name and path from disk, the extension does not sanitize the string it constructs before returning it to be displayed. The diffNotebookCheckpoint function within nbdime causes this issue. When attempting to display the name of the local notebook (diffNotebookCheckpoint), nbdime appears to simply append .ipynb to the name of the input file. The NbdimeWidget is then created, and the base string is passed through to the request API function. From there, the frontend simply renders the HTML tag and anything along with it. Users are advised to patch to the most recent version of the affected product. |
pyup-update-sphinx-1.8.1-to-7.3.7
10 months, 4 weeks ago
Update sphinx from 1.8.1 to 7.3.7
scipy 1.1.0, numpy 1.15.2 and 3 other dependencies have known security vulnerabilities.
| Package | Installed | Affected | Info |
|---|---|---|---|
| numpy | 1.15.2 | <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 | 1.15.2 | <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 | 1.15.2 | <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 |
| numpy | 1.15.2 | <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 | 1.15.2 | <1.16.3 |
show Numpy 1.16.3 includes a fix for CVE-2019-6446: It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call. NOTE: Third parties dispute this issue because it is a behavior that might have legitimate applications in (for example) loading serialized Python object arrays from trusted and authenticated sources. https://github.com/numpy/numpy/commit/89b688732b37616c9d26623f81aaee1703c30ffb |
| wheel | 0.31.1 | <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 | 1.12.1 | <2.0.0 |
show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix. |
| nbdime | 1.0.2 | >=0,<1.1.1 , >=2.0.0,<2.1.1 , >=3.0.0,<3.1.1 |
show nbdime provides tools for diffing and merging of Jupyter Notebooks. In affected versions a stored cross-site scripting (XSS) issue exists within the Jupyter-owned nbdime project. It appears that when reading the file name and path from disk, the extension does not sanitize the string it constructs before returning it to be displayed. The diffNotebookCheckpoint function within nbdime causes this issue. When attempting to display the name of the local notebook (diffNotebookCheckpoint), nbdime appears to simply append .ipynb to the name of the input file. The NbdimeWidget is then created, and the base string is passed through to the request API function. From there, the frontend simply renders the HTML tag and anything along with it. Users are advised to patch to the most recent version of the affected product. |
pyup-update-sphinx-1.8.1-to-7.3.6
11 months ago
Update sphinx from 1.8.1 to 7.3.6
scipy 1.1.0, numpy 1.15.2 and 3 other dependencies have known security vulnerabilities.
| Package | Installed | Affected | Info |
|---|---|---|---|
| numpy | 1.15.2 | <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 | 1.15.2 | <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 | 1.15.2 | <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 |
| numpy | 1.15.2 | <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 | 1.15.2 | <1.16.3 |
show Numpy 1.16.3 includes a fix for CVE-2019-6446: It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call. NOTE: Third parties dispute this issue because it is a behavior that might have legitimate applications in (for example) loading serialized Python object arrays from trusted and authenticated sources. https://github.com/numpy/numpy/commit/89b688732b37616c9d26623f81aaee1703c30ffb |
| wheel | 0.31.1 | <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 | 1.12.1 | <2.0.0 |
show Twine 2.0.0 updates requests to 2.20 (or later) to include a security fix. |
| nbdime | 1.0.2 | >=0,<1.1.1 , >=2.0.0,<2.1.1 , >=3.0.0,<3.1.1 |
show nbdime provides tools for diffing and merging of Jupyter Notebooks. In affected versions a stored cross-site scripting (XSS) issue exists within the Jupyter-owned nbdime project. It appears that when reading the file name and path from disk, the extension does not sanitize the string it constructs before returning it to be displayed. The diffNotebookCheckpoint function within nbdime causes this issue. When attempting to display the name of the local notebook (diffNotebookCheckpoint), nbdime appears to simply append .ipynb to the name of the input file. The NbdimeWidget is then created, and the base string is passed through to the request API function. From there, the frontend simply renders the HTML tag and anything along with it. Users are advised to patch to the most recent version of the affected product. |
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