Regular expression denial of service in Pydanic affected versions allows remote attackers to cause denial of service via a crafted email string.

Pydantic 1.10.13 and 2.4.0 include a fix for a regular expression denial of service vulnerability (REDoS).
https://github.com/pydantic/pydantic/pull/7360
https://github.com/pydantic/pydantic/pull/7673

Pydantic 1.10.2 prevents long strings as int inputs to fix CVE-2020-10735.
https://github.com/pydantic/pydantic/commit/eccd85e4d012e70ffbd81f379179da900d4621c5

Pydantic 1.8.2, 1.7.4 and 1.6.2 include a fix for CVE-2021-29510: In affected versions of Pydantic passing either `'infinity'`, `'inf'` or `float('inf')` (or their negatives) to `datetime` or `date` fields causes validation to run forever with 100% CPU usage (on one CPU). Pydantic has been patched with fixes available in the following versions: v1.8.2, v1.7.4, v1.6.2. All these versions are available on pypi(https://pypi.org/project/pydantic/#history), and will be available on conda-forge(https://anaconda.org/conda-forge/pydantic) soon. See the changelog(https://pydantic-docs.helpmanual.io/) for details. If you absolutely can't upgrade, you can work around this risk using a validator(https://pydantic-docs.helpmanual.io/usage/validators/) to catch these values. This is not an ideal solution (in particular you'll need a slightly different function for datetimes), instead of a hack like this you should upgrade pydantic. If you are not using v1.8.x, v1.7.x or v1.6.x and are unable to upgrade to a fixed version of pydantic, please create an issue at https://github.com/samuelcolvin/pydantic/issues requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic.

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Yamale does not protect against intentionally malicious schemas. Ensure that your schema definitions come from internal or trusted sources.

Yamale 3.0.8 includes a fix for CVE-2021-38305: 23andMe Yamale before 3.0.8 allows remote attackers to execute arbitrary code via a crafted schema file. The schema parser uses eval as part of its processing, and tries to protect from malicious expressions by limiting the builtins that are passed to the eval. When processing the schema, each line is run through Python's eval function to make the validator available. A well-constructed string within the schema rules can execute system commands; thus, by exploiting the vulnerability, an attacker can run arbitrary code on the image that invokes Yamale.
https://github.com/23andMe/Yamale/pull/165
https://github.com/23andMe/Yamale/releases/tag/3.0.8

Yamale version 4.0.0 includes a fix for a RCE vulnerability.
https://github.com/23andMe/Yamale/issues/167

Pylint 2.7.0 includes a fix for vulnerable regular expressions in 'pyreverse'.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pylint 2.13.0 fixes a crash when using the doc_params extension.
https://github.com/PyCQA/pylint/issues/5322

Pylint 2.5.0 no longer allows ``python -m pylint ...`` to import user code. Previously, it added the current working directory as the first element of ``sys.path``. This opened up a potential security hole where ``pylint`` would import user level code as long as that code resided in modules having the same name as stdlib or pylint's own modules.

Pylint before 2.6.1 is susceptible to a Regular Expression Denial of Service (ReDoS) vulnerability due to issues in its pyreverse component. This issue arises from certain regular expressions in pyreverse that can be exploited by causing catastrophic backtracking, significantly slowing down the service by forcing it to take a disproportionate amount of time to process inputs. This vulnerability allows attackers to use specially crafted inputs that increase the processing time exponentially, potentially leading to a service becoming inaccessible to legitimate users.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Regular expression denial of service in Pydanic affected versions allows remote attackers to cause denial of service via a crafted email string.

Pydantic 1.10.13 and 2.4.0 include a fix for a regular expression denial of service vulnerability (REDoS).
https://github.com/pydantic/pydantic/pull/7360
https://github.com/pydantic/pydantic/pull/7673

Pydantic 1.10.2 prevents long strings as int inputs to fix CVE-2020-10735.
https://github.com/pydantic/pydantic/commit/eccd85e4d012e70ffbd81f379179da900d4621c5

Pydantic 1.8.2, 1.7.4 and 1.6.2 include a fix for CVE-2021-29510: In affected versions of Pydantic passing either `'infinity'`, `'inf'` or `float('inf')` (or their negatives) to `datetime` or `date` fields causes validation to run forever with 100% CPU usage (on one CPU). Pydantic has been patched with fixes available in the following versions: v1.8.2, v1.7.4, v1.6.2. All these versions are available on pypi(https://pypi.org/project/pydantic/#history), and will be available on conda-forge(https://anaconda.org/conda-forge/pydantic) soon. See the changelog(https://pydantic-docs.helpmanual.io/) for details. If you absolutely can't upgrade, you can work around this risk using a validator(https://pydantic-docs.helpmanual.io/usage/validators/) to catch these values. This is not an ideal solution (in particular you'll need a slightly different function for datetimes), instead of a hack like this you should upgrade pydantic. If you are not using v1.8.x, v1.7.x or v1.6.x and are unable to upgrade to a fixed version of pydantic, please create an issue at https://github.com/samuelcolvin/pydantic/issues requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic.

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Yamale does not protect against intentionally malicious schemas. Ensure that your schema definitions come from internal or trusted sources.

Yamale 3.0.8 includes a fix for CVE-2021-38305: 23andMe Yamale before 3.0.8 allows remote attackers to execute arbitrary code via a crafted schema file. The schema parser uses eval as part of its processing, and tries to protect from malicious expressions by limiting the builtins that are passed to the eval. When processing the schema, each line is run through Python's eval function to make the validator available. A well-constructed string within the schema rules can execute system commands; thus, by exploiting the vulnerability, an attacker can run arbitrary code on the image that invokes Yamale.
https://github.com/23andMe/Yamale/pull/165
https://github.com/23andMe/Yamale/releases/tag/3.0.8

Yamale version 4.0.0 includes a fix for a RCE vulnerability.
https://github.com/23andMe/Yamale/issues/167

Regular expression denial of service in Pydanic affected versions allows remote attackers to cause denial of service via a crafted email string.

Pydantic 1.10.13 and 2.4.0 include a fix for a regular expression denial of service vulnerability (REDoS).
https://github.com/pydantic/pydantic/pull/7360
https://github.com/pydantic/pydantic/pull/7673

Pydantic 1.10.2 prevents long strings as int inputs to fix CVE-2020-10735.
https://github.com/pydantic/pydantic/commit/eccd85e4d012e70ffbd81f379179da900d4621c5

Pydantic 1.8.2, 1.7.4 and 1.6.2 include a fix for CVE-2021-29510: In affected versions of Pydantic passing either `'infinity'`, `'inf'` or `float('inf')` (or their negatives) to `datetime` or `date` fields causes validation to run forever with 100% CPU usage (on one CPU). Pydantic has been patched with fixes available in the following versions: v1.8.2, v1.7.4, v1.6.2. All these versions are available on pypi(https://pypi.org/project/pydantic/#history), and will be available on conda-forge(https://anaconda.org/conda-forge/pydantic) soon. See the changelog(https://pydantic-docs.helpmanual.io/) for details. If you absolutely can't upgrade, you can work around this risk using a validator(https://pydantic-docs.helpmanual.io/usage/validators/) to catch these values. This is not an ideal solution (in particular you'll need a slightly different function for datetimes), instead of a hack like this you should upgrade pydantic. If you are not using v1.8.x, v1.7.x or v1.6.x and are unable to upgrade to a fixed version of pydantic, please create an issue at https://github.com/samuelcolvin/pydantic/issues requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic.

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Yamale does not protect against intentionally malicious schemas. Ensure that your schema definitions come from internal or trusted sources.

Yamale 3.0.8 includes a fix for CVE-2021-38305: 23andMe Yamale before 3.0.8 allows remote attackers to execute arbitrary code via a crafted schema file. The schema parser uses eval as part of its processing, and tries to protect from malicious expressions by limiting the builtins that are passed to the eval. When processing the schema, each line is run through Python's eval function to make the validator available. A well-constructed string within the schema rules can execute system commands; thus, by exploiting the vulnerability, an attacker can run arbitrary code on the image that invokes Yamale.
https://github.com/23andMe/Yamale/pull/165
https://github.com/23andMe/Yamale/releases/tag/3.0.8

Yamale version 4.0.0 includes a fix for a RCE vulnerability.
https://github.com/23andMe/Yamale/issues/167

Pylint 2.7.0 includes a fix for vulnerable regular expressions in 'pyreverse'.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pylint 2.13.0 fixes a crash when using the doc_params extension.
https://github.com/PyCQA/pylint/issues/5322

Pylint 2.5.0 no longer allows ``python -m pylint ...`` to import user code. Previously, it added the current working directory as the first element of ``sys.path``. This opened up a potential security hole where ``pylint`` would import user level code as long as that code resided in modules having the same name as stdlib or pylint's own modules.

Pylint before 2.6.1 is susceptible to a Regular Expression Denial of Service (ReDoS) vulnerability due to issues in its pyreverse component. This issue arises from certain regular expressions in pyreverse that can be exploited by causing catastrophic backtracking, significantly slowing down the service by forcing it to take a disproportionate amount of time to process inputs. This vulnerability allows attackers to use specially crafted inputs that increase the processing time exponentially, potentially leading to a service becoming inaccessible to legitimate users.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Yamale does not protect against intentionally malicious schemas. Ensure that your schema definitions come from internal or trusted sources.

Yamale 3.0.8 includes a fix for CVE-2021-38305: 23andMe Yamale before 3.0.8 allows remote attackers to execute arbitrary code via a crafted schema file. The schema parser uses eval as part of its processing, and tries to protect from malicious expressions by limiting the builtins that are passed to the eval. When processing the schema, each line is run through Python's eval function to make the validator available. A well-constructed string within the schema rules can execute system commands; thus, by exploiting the vulnerability, an attacker can run arbitrary code on the image that invokes Yamale.
https://github.com/23andMe/Yamale/pull/165
https://github.com/23andMe/Yamale/releases/tag/3.0.8

Yamale version 4.0.0 includes a fix for a RCE vulnerability.
https://github.com/23andMe/Yamale/issues/167

Pylint 2.7.0 includes a fix for vulnerable regular expressions in 'pyreverse'.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pylint 2.13.0 fixes a crash when using the doc_params extension.
https://github.com/PyCQA/pylint/issues/5322

Pylint 2.5.0 no longer allows ``python -m pylint ...`` to import user code. Previously, it added the current working directory as the first element of ``sys.path``. This opened up a potential security hole where ``pylint`` would import user level code as long as that code resided in modules having the same name as stdlib or pylint's own modules.

Pylint before 2.6.1 is susceptible to a Regular Expression Denial of Service (ReDoS) vulnerability due to issues in its pyreverse component. This issue arises from certain regular expressions in pyreverse that can be exploited by causing catastrophic backtracking, significantly slowing down the service by forcing it to take a disproportionate amount of time to process inputs. This vulnerability allows attackers to use specially crafted inputs that increase the processing time exponentially, potentially leading to a service becoming inaccessible to legitimate users.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Yamale does not protect against intentionally malicious schemas. Ensure that your schema definitions come from internal or trusted sources.

Yamale 3.0.8 includes a fix for CVE-2021-38305: 23andMe Yamale before 3.0.8 allows remote attackers to execute arbitrary code via a crafted schema file. The schema parser uses eval as part of its processing, and tries to protect from malicious expressions by limiting the builtins that are passed to the eval. When processing the schema, each line is run through Python's eval function to make the validator available. A well-constructed string within the schema rules can execute system commands; thus, by exploiting the vulnerability, an attacker can run arbitrary code on the image that invokes Yamale.
https://github.com/23andMe/Yamale/pull/165
https://github.com/23andMe/Yamale/releases/tag/3.0.8

Yamale version 4.0.0 includes a fix for a RCE vulnerability.
https://github.com/23andMe/Yamale/issues/167

Pylint 2.7.0 includes a fix for vulnerable regular expressions in 'pyreverse'.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pylint 2.13.0 fixes a crash when using the doc_params extension.
https://github.com/PyCQA/pylint/issues/5322

Pylint 2.5.0 no longer allows ``python -m pylint ...`` to import user code. Previously, it added the current working directory as the first element of ``sys.path``. This opened up a potential security hole where ``pylint`` would import user level code as long as that code resided in modules having the same name as stdlib or pylint's own modules.

Pylint before 2.6.1 is susceptible to a Regular Expression Denial of Service (ReDoS) vulnerability due to issues in its pyreverse component. This issue arises from certain regular expressions in pyreverse that can be exploited by causing catastrophic backtracking, significantly slowing down the service by forcing it to take a disproportionate amount of time to process inputs. This vulnerability allows attackers to use specially crafted inputs that increase the processing time exponentially, potentially leading to a service becoming inaccessible to legitimate users.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Yamale does not protect against intentionally malicious schemas. Ensure that your schema definitions come from internal or trusted sources.

Yamale 3.0.8 includes a fix for CVE-2021-38305: 23andMe Yamale before 3.0.8 allows remote attackers to execute arbitrary code via a crafted schema file. The schema parser uses eval as part of its processing, and tries to protect from malicious expressions by limiting the builtins that are passed to the eval. When processing the schema, each line is run through Python's eval function to make the validator available. A well-constructed string within the schema rules can execute system commands; thus, by exploiting the vulnerability, an attacker can run arbitrary code on the image that invokes Yamale.
https://github.com/23andMe/Yamale/pull/165
https://github.com/23andMe/Yamale/releases/tag/3.0.8

Yamale version 4.0.0 includes a fix for a RCE vulnerability.
https://github.com/23andMe/Yamale/issues/167

Pylint 2.7.0 includes a fix for vulnerable regular expressions in 'pyreverse'.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pylint 2.13.0 fixes a crash when using the doc_params extension.
https://github.com/PyCQA/pylint/issues/5322

Pylint 2.5.0 no longer allows ``python -m pylint ...`` to import user code. Previously, it added the current working directory as the first element of ``sys.path``. This opened up a potential security hole where ``pylint`` would import user level code as long as that code resided in modules having the same name as stdlib or pylint's own modules.

Pylint before 2.6.1 is susceptible to a Regular Expression Denial of Service (ReDoS) vulnerability due to issues in its pyreverse component. This issue arises from certain regular expressions in pyreverse that can be exploited by causing catastrophic backtracking, significantly slowing down the service by forcing it to take a disproportionate amount of time to process inputs. This vulnerability allows attackers to use specially crafted inputs that increase the processing time exponentially, potentially leading to a service becoming inaccessible to legitimate users.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Regular expression denial of service in Pydanic affected versions allows remote attackers to cause denial of service via a crafted email string.

Pydantic 1.10.13 and 2.4.0 include a fix for a regular expression denial of service vulnerability (REDoS).
https://github.com/pydantic/pydantic/pull/7360
https://github.com/pydantic/pydantic/pull/7673

Pydantic 1.10.2 prevents long strings as int inputs to fix CVE-2020-10735.
https://github.com/pydantic/pydantic/commit/eccd85e4d012e70ffbd81f379179da900d4621c5

Pydantic 1.8.2, 1.7.4 and 1.6.2 include a fix for CVE-2021-29510: In affected versions of Pydantic passing either `'infinity'`, `'inf'` or `float('inf')` (or their negatives) to `datetime` or `date` fields causes validation to run forever with 100% CPU usage (on one CPU). Pydantic has been patched with fixes available in the following versions: v1.8.2, v1.7.4, v1.6.2. All these versions are available on pypi(https://pypi.org/project/pydantic/#history), and will be available on conda-forge(https://anaconda.org/conda-forge/pydantic) soon. See the changelog(https://pydantic-docs.helpmanual.io/) for details. If you absolutely can't upgrade, you can work around this risk using a validator(https://pydantic-docs.helpmanual.io/usage/validators/) to catch these values. This is not an ideal solution (in particular you'll need a slightly different function for datetimes), instead of a hack like this you should upgrade pydantic. If you are not using v1.8.x, v1.7.x or v1.6.x and are unable to upgrade to a fixed version of pydantic, please create an issue at https://github.com/samuelcolvin/pydantic/issues requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic.

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Yamale does not protect against intentionally malicious schemas. Ensure that your schema definitions come from internal or trusted sources.

Yamale 3.0.8 includes a fix for CVE-2021-38305: 23andMe Yamale before 3.0.8 allows remote attackers to execute arbitrary code via a crafted schema file. The schema parser uses eval as part of its processing, and tries to protect from malicious expressions by limiting the builtins that are passed to the eval. When processing the schema, each line is run through Python's eval function to make the validator available. A well-constructed string within the schema rules can execute system commands; thus, by exploiting the vulnerability, an attacker can run arbitrary code on the image that invokes Yamale.
https://github.com/23andMe/Yamale/pull/165
https://github.com/23andMe/Yamale/releases/tag/3.0.8

Yamale version 4.0.0 includes a fix for a RCE vulnerability.
https://github.com/23andMe/Yamale/issues/167

Pylint 2.7.0 includes a fix for vulnerable regular expressions in 'pyreverse'.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pylint 2.13.0 fixes a crash when using the doc_params extension.
https://github.com/PyCQA/pylint/issues/5322

Pylint 2.5.0 no longer allows ``python -m pylint ...`` to import user code. Previously, it added the current working directory as the first element of ``sys.path``. This opened up a potential security hole where ``pylint`` would import user level code as long as that code resided in modules having the same name as stdlib or pylint's own modules.

Pylint before 2.6.1 is susceptible to a Regular Expression Denial of Service (ReDoS) vulnerability due to issues in its pyreverse component. This issue arises from certain regular expressions in pyreverse that can be exploited by causing catastrophic backtracking, significantly slowing down the service by forcing it to take a disproportionate amount of time to process inputs. This vulnerability allows attackers to use specially crafted inputs that increase the processing time exponentially, potentially leading to a service becoming inaccessible to legitimate users.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Regular expression denial of service in Pydanic affected versions allows remote attackers to cause denial of service via a crafted email string.

Pydantic 1.10.13 and 2.4.0 include a fix for a regular expression denial of service vulnerability (REDoS).
https://github.com/pydantic/pydantic/pull/7360
https://github.com/pydantic/pydantic/pull/7673

Pydantic 1.10.2 prevents long strings as int inputs to fix CVE-2020-10735.
https://github.com/pydantic/pydantic/commit/eccd85e4d012e70ffbd81f379179da900d4621c5

Pydantic 1.8.2, 1.7.4 and 1.6.2 include a fix for CVE-2021-29510: In affected versions of Pydantic passing either `'infinity'`, `'inf'` or `float('inf')` (or their negatives) to `datetime` or `date` fields causes validation to run forever with 100% CPU usage (on one CPU). Pydantic has been patched with fixes available in the following versions: v1.8.2, v1.7.4, v1.6.2. All these versions are available on pypi(https://pypi.org/project/pydantic/#history), and will be available on conda-forge(https://anaconda.org/conda-forge/pydantic) soon. See the changelog(https://pydantic-docs.helpmanual.io/) for details. If you absolutely can't upgrade, you can work around this risk using a validator(https://pydantic-docs.helpmanual.io/usage/validators/) to catch these values. This is not an ideal solution (in particular you'll need a slightly different function for datetimes), instead of a hack like this you should upgrade pydantic. If you are not using v1.8.x, v1.7.x or v1.6.x and are unable to upgrade to a fixed version of pydantic, please create an issue at https://github.com/samuelcolvin/pydantic/issues requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic.

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Yamale does not protect against intentionally malicious schemas. Ensure that your schema definitions come from internal or trusted sources.

Yamale 3.0.8 includes a fix for CVE-2021-38305: 23andMe Yamale before 3.0.8 allows remote attackers to execute arbitrary code via a crafted schema file. The schema parser uses eval as part of its processing, and tries to protect from malicious expressions by limiting the builtins that are passed to the eval. When processing the schema, each line is run through Python's eval function to make the validator available. A well-constructed string within the schema rules can execute system commands; thus, by exploiting the vulnerability, an attacker can run arbitrary code on the image that invokes Yamale.
https://github.com/23andMe/Yamale/pull/165
https://github.com/23andMe/Yamale/releases/tag/3.0.8

Yamale version 4.0.0 includes a fix for a RCE vulnerability.
https://github.com/23andMe/Yamale/issues/167

Pylint 2.7.0 includes a fix for vulnerable regular expressions in 'pyreverse'.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pylint 2.13.0 fixes a crash when using the doc_params extension.
https://github.com/PyCQA/pylint/issues/5322

Pylint 2.5.0 no longer allows ``python -m pylint ...`` to import user code. Previously, it added the current working directory as the first element of ``sys.path``. This opened up a potential security hole where ``pylint`` would import user level code as long as that code resided in modules having the same name as stdlib or pylint's own modules.

Pylint before 2.6.1 is susceptible to a Regular Expression Denial of Service (ReDoS) vulnerability due to issues in its pyreverse component. This issue arises from certain regular expressions in pyreverse that can be exploited by causing catastrophic backtracking, significantly slowing down the service by forcing it to take a disproportionate amount of time to process inputs. This vulnerability allows attackers to use specially crafted inputs that increase the processing time exponentially, potentially leading to a service becoming inaccessible to legitimate users.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Regular expression denial of service in Pydanic affected versions allows remote attackers to cause denial of service via a crafted email string.

Pydantic 1.10.13 and 2.4.0 include a fix for a regular expression denial of service vulnerability (REDoS).
https://github.com/pydantic/pydantic/pull/7360
https://github.com/pydantic/pydantic/pull/7673

Pydantic 1.10.2 prevents long strings as int inputs to fix CVE-2020-10735.
https://github.com/pydantic/pydantic/commit/eccd85e4d012e70ffbd81f379179da900d4621c5

Pydantic 1.8.2, 1.7.4 and 1.6.2 include a fix for CVE-2021-29510: In affected versions of Pydantic passing either `'infinity'`, `'inf'` or `float('inf')` (or their negatives) to `datetime` or `date` fields causes validation to run forever with 100% CPU usage (on one CPU). Pydantic has been patched with fixes available in the following versions: v1.8.2, v1.7.4, v1.6.2. All these versions are available on pypi(https://pypi.org/project/pydantic/#history), and will be available on conda-forge(https://anaconda.org/conda-forge/pydantic) soon. See the changelog(https://pydantic-docs.helpmanual.io/) for details. If you absolutely can't upgrade, you can work around this risk using a validator(https://pydantic-docs.helpmanual.io/usage/validators/) to catch these values. This is not an ideal solution (in particular you'll need a slightly different function for datetimes), instead of a hack like this you should upgrade pydantic. If you are not using v1.8.x, v1.7.x or v1.6.x and are unable to upgrade to a fixed version of pydantic, please create an issue at https://github.com/samuelcolvin/pydantic/issues requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic.

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Yamale does not protect against intentionally malicious schemas. Ensure that your schema definitions come from internal or trusted sources.

Yamale 3.0.8 includes a fix for CVE-2021-38305: 23andMe Yamale before 3.0.8 allows remote attackers to execute arbitrary code via a crafted schema file. The schema parser uses eval as part of its processing, and tries to protect from malicious expressions by limiting the builtins that are passed to the eval. When processing the schema, each line is run through Python's eval function to make the validator available. A well-constructed string within the schema rules can execute system commands; thus, by exploiting the vulnerability, an attacker can run arbitrary code on the image that invokes Yamale.
https://github.com/23andMe/Yamale/pull/165
https://github.com/23andMe/Yamale/releases/tag/3.0.8

Yamale version 4.0.0 includes a fix for a RCE vulnerability.
https://github.com/23andMe/Yamale/issues/167

Pylint 2.7.0 includes a fix for vulnerable regular expressions in 'pyreverse'.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pylint 2.13.0 fixes a crash when using the doc_params extension.
https://github.com/PyCQA/pylint/issues/5322

Pylint 2.5.0 no longer allows ``python -m pylint ...`` to import user code. Previously, it added the current working directory as the first element of ``sys.path``. This opened up a potential security hole where ``pylint`` would import user level code as long as that code resided in modules having the same name as stdlib or pylint's own modules.

Pylint before 2.6.1 is susceptible to a Regular Expression Denial of Service (ReDoS) vulnerability due to issues in its pyreverse component. This issue arises from certain regular expressions in pyreverse that can be exploited by causing catastrophic backtracking, significantly slowing down the service by forcing it to take a disproportionate amount of time to process inputs. This vulnerability allows attackers to use specially crafted inputs that increase the processing time exponentially, potentially leading to a service becoming inaccessible to legitimate users.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Regular expression denial of service in Pydanic affected versions allows remote attackers to cause denial of service via a crafted email string.

Pydantic 1.10.13 and 2.4.0 include a fix for a regular expression denial of service vulnerability (REDoS).
https://github.com/pydantic/pydantic/pull/7360
https://github.com/pydantic/pydantic/pull/7673

Pydantic 1.10.2 prevents long strings as int inputs to fix CVE-2020-10735.
https://github.com/pydantic/pydantic/commit/eccd85e4d012e70ffbd81f379179da900d4621c5

Pydantic 1.8.2, 1.7.4 and 1.6.2 include a fix for CVE-2021-29510: In affected versions of Pydantic passing either `'infinity'`, `'inf'` or `float('inf')` (or their negatives) to `datetime` or `date` fields causes validation to run forever with 100% CPU usage (on one CPU). Pydantic has been patched with fixes available in the following versions: v1.8.2, v1.7.4, v1.6.2. All these versions are available on pypi(https://pypi.org/project/pydantic/#history), and will be available on conda-forge(https://anaconda.org/conda-forge/pydantic) soon. See the changelog(https://pydantic-docs.helpmanual.io/) for details. If you absolutely can't upgrade, you can work around this risk using a validator(https://pydantic-docs.helpmanual.io/usage/validators/) to catch these values. This is not an ideal solution (in particular you'll need a slightly different function for datetimes), instead of a hack like this you should upgrade pydantic. If you are not using v1.8.x, v1.7.x or v1.6.x and are unable to upgrade to a fixed version of pydantic, please create an issue at https://github.com/samuelcolvin/pydantic/issues requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic.

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Yamale does not protect against intentionally malicious schemas. Ensure that your schema definitions come from internal or trusted sources.

Yamale 3.0.8 includes a fix for CVE-2021-38305: 23andMe Yamale before 3.0.8 allows remote attackers to execute arbitrary code via a crafted schema file. The schema parser uses eval as part of its processing, and tries to protect from malicious expressions by limiting the builtins that are passed to the eval. When processing the schema, each line is run through Python's eval function to make the validator available. A well-constructed string within the schema rules can execute system commands; thus, by exploiting the vulnerability, an attacker can run arbitrary code on the image that invokes Yamale.
https://github.com/23andMe/Yamale/pull/165
https://github.com/23andMe/Yamale/releases/tag/3.0.8

Yamale version 4.0.0 includes a fix for a RCE vulnerability.
https://github.com/23andMe/Yamale/issues/167

Pylint 2.7.0 includes a fix for vulnerable regular expressions in 'pyreverse'.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pylint 2.13.0 fixes a crash when using the doc_params extension.
https://github.com/PyCQA/pylint/issues/5322

Pylint 2.5.0 no longer allows ``python -m pylint ...`` to import user code. Previously, it added the current working directory as the first element of ``sys.path``. This opened up a potential security hole where ``pylint`` would import user level code as long as that code resided in modules having the same name as stdlib or pylint's own modules.

Pylint before 2.6.1 is susceptible to a Regular Expression Denial of Service (ReDoS) vulnerability due to issues in its pyreverse component. This issue arises from certain regular expressions in pyreverse that can be exploited by causing catastrophic backtracking, significantly slowing down the service by forcing it to take a disproportionate amount of time to process inputs. This vulnerability allows attackers to use specially crafted inputs that increase the processing time exponentially, potentially leading to a service becoming inaccessible to legitimate users.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Regular expression denial of service in Pydanic affected versions allows remote attackers to cause denial of service via a crafted email string.

Pydantic 1.10.13 and 2.4.0 include a fix for a regular expression denial of service vulnerability (REDoS).
https://github.com/pydantic/pydantic/pull/7360
https://github.com/pydantic/pydantic/pull/7673

Pydantic 1.10.2 prevents long strings as int inputs to fix CVE-2020-10735.
https://github.com/pydantic/pydantic/commit/eccd85e4d012e70ffbd81f379179da900d4621c5

Pydantic 1.8.2, 1.7.4 and 1.6.2 include a fix for CVE-2021-29510: In affected versions of Pydantic passing either `'infinity'`, `'inf'` or `float('inf')` (or their negatives) to `datetime` or `date` fields causes validation to run forever with 100% CPU usage (on one CPU). Pydantic has been patched with fixes available in the following versions: v1.8.2, v1.7.4, v1.6.2. All these versions are available on pypi(https://pypi.org/project/pydantic/#history), and will be available on conda-forge(https://anaconda.org/conda-forge/pydantic) soon. See the changelog(https://pydantic-docs.helpmanual.io/) for details. If you absolutely can't upgrade, you can work around this risk using a validator(https://pydantic-docs.helpmanual.io/usage/validators/) to catch these values. This is not an ideal solution (in particular you'll need a slightly different function for datetimes), instead of a hack like this you should upgrade pydantic. If you are not using v1.8.x, v1.7.x or v1.6.x and are unable to upgrade to a fixed version of pydantic, please create an issue at https://github.com/samuelcolvin/pydantic/issues requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic.

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Yamale does not protect against intentionally malicious schemas. Ensure that your schema definitions come from internal or trusted sources.

Yamale 3.0.8 includes a fix for CVE-2021-38305: 23andMe Yamale before 3.0.8 allows remote attackers to execute arbitrary code via a crafted schema file. The schema parser uses eval as part of its processing, and tries to protect from malicious expressions by limiting the builtins that are passed to the eval. When processing the schema, each line is run through Python's eval function to make the validator available. A well-constructed string within the schema rules can execute system commands; thus, by exploiting the vulnerability, an attacker can run arbitrary code on the image that invokes Yamale.
https://github.com/23andMe/Yamale/pull/165
https://github.com/23andMe/Yamale/releases/tag/3.0.8

Yamale version 4.0.0 includes a fix for a RCE vulnerability.
https://github.com/23andMe/Yamale/issues/167

Pylint 2.7.0 includes a fix for vulnerable regular expressions in 'pyreverse'.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pylint 2.13.0 fixes a crash when using the doc_params extension.
https://github.com/PyCQA/pylint/issues/5322

Pylint 2.5.0 no longer allows ``python -m pylint ...`` to import user code. Previously, it added the current working directory as the first element of ``sys.path``. This opened up a potential security hole where ``pylint`` would import user level code as long as that code resided in modules having the same name as stdlib or pylint's own modules.

Pylint before 2.6.1 is susceptible to a Regular Expression Denial of Service (ReDoS) vulnerability due to issues in its pyreverse component. This issue arises from certain regular expressions in pyreverse that can be exploited by causing catastrophic backtracking, significantly slowing down the service by forcing it to take a disproportionate amount of time to process inputs. This vulnerability allows attackers to use specially crafted inputs that increase the processing time exponentially, potentially leading to a service becoming inaccessible to legitimate users.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Regular expression denial of service in Pydanic affected versions allows remote attackers to cause denial of service via a crafted email string.

Pydantic 1.10.13 and 2.4.0 include a fix for a regular expression denial of service vulnerability (REDoS).
https://github.com/pydantic/pydantic/pull/7360
https://github.com/pydantic/pydantic/pull/7673

Pydantic 1.10.2 prevents long strings as int inputs to fix CVE-2020-10735.
https://github.com/pydantic/pydantic/commit/eccd85e4d012e70ffbd81f379179da900d4621c5

Pydantic 1.8.2, 1.7.4 and 1.6.2 include a fix for CVE-2021-29510: In affected versions of Pydantic passing either `'infinity'`, `'inf'` or `float('inf')` (or their negatives) to `datetime` or `date` fields causes validation to run forever with 100% CPU usage (on one CPU). Pydantic has been patched with fixes available in the following versions: v1.8.2, v1.7.4, v1.6.2. All these versions are available on pypi(https://pypi.org/project/pydantic/#history), and will be available on conda-forge(https://anaconda.org/conda-forge/pydantic) soon. See the changelog(https://pydantic-docs.helpmanual.io/) for details. If you absolutely can't upgrade, you can work around this risk using a validator(https://pydantic-docs.helpmanual.io/usage/validators/) to catch these values. This is not an ideal solution (in particular you'll need a slightly different function for datetimes), instead of a hack like this you should upgrade pydantic. If you are not using v1.8.x, v1.7.x or v1.6.x and are unable to upgrade to a fixed version of pydantic, please create an issue at https://github.com/samuelcolvin/pydantic/issues requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic.

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Yamale does not protect against intentionally malicious schemas. Ensure that your schema definitions come from internal or trusted sources.

Yamale 3.0.8 includes a fix for CVE-2021-38305: 23andMe Yamale before 3.0.8 allows remote attackers to execute arbitrary code via a crafted schema file. The schema parser uses eval as part of its processing, and tries to protect from malicious expressions by limiting the builtins that are passed to the eval. When processing the schema, each line is run through Python's eval function to make the validator available. A well-constructed string within the schema rules can execute system commands; thus, by exploiting the vulnerability, an attacker can run arbitrary code on the image that invokes Yamale.
https://github.com/23andMe/Yamale/pull/165
https://github.com/23andMe/Yamale/releases/tag/3.0.8

Yamale version 4.0.0 includes a fix for a RCE vulnerability.
https://github.com/23andMe/Yamale/issues/167

Regular expression denial of service in Pydanic affected versions allows remote attackers to cause denial of service via a crafted email string.

Pydantic 1.10.13 and 2.4.0 include a fix for a regular expression denial of service vulnerability (REDoS).
https://github.com/pydantic/pydantic/pull/7360
https://github.com/pydantic/pydantic/pull/7673

Pydantic 1.10.2 prevents long strings as int inputs to fix CVE-2020-10735.
https://github.com/pydantic/pydantic/commit/eccd85e4d012e70ffbd81f379179da900d4621c5

Pydantic 1.8.2, 1.7.4 and 1.6.2 include a fix for CVE-2021-29510: In affected versions of Pydantic passing either `'infinity'`, `'inf'` or `float('inf')` (or their negatives) to `datetime` or `date` fields causes validation to run forever with 100% CPU usage (on one CPU). Pydantic has been patched with fixes available in the following versions: v1.8.2, v1.7.4, v1.6.2. All these versions are available on pypi(https://pypi.org/project/pydantic/#history), and will be available on conda-forge(https://anaconda.org/conda-forge/pydantic) soon. See the changelog(https://pydantic-docs.helpmanual.io/) for details. If you absolutely can't upgrade, you can work around this risk using a validator(https://pydantic-docs.helpmanual.io/usage/validators/) to catch these values. This is not an ideal solution (in particular you'll need a slightly different function for datetimes), instead of a hack like this you should upgrade pydantic. If you are not using v1.8.x, v1.7.x or v1.6.x and are unable to upgrade to a fixed version of pydantic, please create an issue at https://github.com/samuelcolvin/pydantic/issues requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic.

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Yamale does not protect against intentionally malicious schemas. Ensure that your schema definitions come from internal or trusted sources.

Yamale 3.0.8 includes a fix for CVE-2021-38305: 23andMe Yamale before 3.0.8 allows remote attackers to execute arbitrary code via a crafted schema file. The schema parser uses eval as part of its processing, and tries to protect from malicious expressions by limiting the builtins that are passed to the eval. When processing the schema, each line is run through Python's eval function to make the validator available. A well-constructed string within the schema rules can execute system commands; thus, by exploiting the vulnerability, an attacker can run arbitrary code on the image that invokes Yamale.
https://github.com/23andMe/Yamale/pull/165
https://github.com/23andMe/Yamale/releases/tag/3.0.8

Yamale version 4.0.0 includes a fix for a RCE vulnerability.
https://github.com/23andMe/Yamale/issues/167

Pylint 2.7.0 includes a fix for vulnerable regular expressions in 'pyreverse'.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pylint 2.13.0 fixes a crash when using the doc_params extension.
https://github.com/PyCQA/pylint/issues/5322

Pylint 2.5.0 no longer allows ``python -m pylint ...`` to import user code. Previously, it added the current working directory as the first element of ``sys.path``. This opened up a potential security hole where ``pylint`` would import user level code as long as that code resided in modules having the same name as stdlib or pylint's own modules.

Pylint before 2.6.1 is susceptible to a Regular Expression Denial of Service (ReDoS) vulnerability due to issues in its pyreverse component. This issue arises from certain regular expressions in pyreverse that can be exploited by causing catastrophic backtracking, significantly slowing down the service by forcing it to take a disproportionate amount of time to process inputs. This vulnerability allows attackers to use specially crafted inputs that increase the processing time exponentially, potentially leading to a service becoming inaccessible to legitimate users.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Regular expression denial of service in Pydanic affected versions allows remote attackers to cause denial of service via a crafted email string.

Pydantic 1.10.13 and 2.4.0 include a fix for a regular expression denial of service vulnerability (REDoS).
https://github.com/pydantic/pydantic/pull/7360
https://github.com/pydantic/pydantic/pull/7673

Pydantic 1.10.2 prevents long strings as int inputs to fix CVE-2020-10735.
https://github.com/pydantic/pydantic/commit/eccd85e4d012e70ffbd81f379179da900d4621c5

Pydantic 1.8.2, 1.7.4 and 1.6.2 include a fix for CVE-2021-29510: In affected versions of Pydantic passing either `'infinity'`, `'inf'` or `float('inf')` (or their negatives) to `datetime` or `date` fields causes validation to run forever with 100% CPU usage (on one CPU). Pydantic has been patched with fixes available in the following versions: v1.8.2, v1.7.4, v1.6.2. All these versions are available on pypi(https://pypi.org/project/pydantic/#history), and will be available on conda-forge(https://anaconda.org/conda-forge/pydantic) soon. See the changelog(https://pydantic-docs.helpmanual.io/) for details. If you absolutely can't upgrade, you can work around this risk using a validator(https://pydantic-docs.helpmanual.io/usage/validators/) to catch these values. This is not an ideal solution (in particular you'll need a slightly different function for datetimes), instead of a hack like this you should upgrade pydantic. If you are not using v1.8.x, v1.7.x or v1.6.x and are unable to upgrade to a fixed version of pydantic, please create an issue at https://github.com/samuelcolvin/pydantic/issues requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic.

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Yamale does not protect against intentionally malicious schemas. Ensure that your schema definitions come from internal or trusted sources.

Yamale 3.0.8 includes a fix for CVE-2021-38305: 23andMe Yamale before 3.0.8 allows remote attackers to execute arbitrary code via a crafted schema file. The schema parser uses eval as part of its processing, and tries to protect from malicious expressions by limiting the builtins that are passed to the eval. When processing the schema, each line is run through Python's eval function to make the validator available. A well-constructed string within the schema rules can execute system commands; thus, by exploiting the vulnerability, an attacker can run arbitrary code on the image that invokes Yamale.
https://github.com/23andMe/Yamale/pull/165
https://github.com/23andMe/Yamale/releases/tag/3.0.8

Yamale version 4.0.0 includes a fix for a RCE vulnerability.
https://github.com/23andMe/Yamale/issues/167

Regular expression denial of service in Pydanic affected versions allows remote attackers to cause denial of service via a crafted email string.

Pydantic 1.10.13 and 2.4.0 include a fix for a regular expression denial of service vulnerability (REDoS).
https://github.com/pydantic/pydantic/pull/7360
https://github.com/pydantic/pydantic/pull/7673

Pydantic 1.10.2 prevents long strings as int inputs to fix CVE-2020-10735.
https://github.com/pydantic/pydantic/commit/eccd85e4d012e70ffbd81f379179da900d4621c5

Pydantic 1.8.2, 1.7.4 and 1.6.2 include a fix for CVE-2021-29510: In affected versions of Pydantic passing either `'infinity'`, `'inf'` or `float('inf')` (or their negatives) to `datetime` or `date` fields causes validation to run forever with 100% CPU usage (on one CPU). Pydantic has been patched with fixes available in the following versions: v1.8.2, v1.7.4, v1.6.2. All these versions are available on pypi(https://pypi.org/project/pydantic/#history), and will be available on conda-forge(https://anaconda.org/conda-forge/pydantic) soon. See the changelog(https://pydantic-docs.helpmanual.io/) for details. If you absolutely can't upgrade, you can work around this risk using a validator(https://pydantic-docs.helpmanual.io/usage/validators/) to catch these values. This is not an ideal solution (in particular you'll need a slightly different function for datetimes), instead of a hack like this you should upgrade pydantic. If you are not using v1.8.x, v1.7.x or v1.6.x and are unable to upgrade to a fixed version of pydantic, please create an issue at https://github.com/samuelcolvin/pydantic/issues requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic.

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Yamale does not protect against intentionally malicious schemas. Ensure that your schema definitions come from internal or trusted sources.

Yamale 3.0.8 includes a fix for CVE-2021-38305: 23andMe Yamale before 3.0.8 allows remote attackers to execute arbitrary code via a crafted schema file. The schema parser uses eval as part of its processing, and tries to protect from malicious expressions by limiting the builtins that are passed to the eval. When processing the schema, each line is run through Python's eval function to make the validator available. A well-constructed string within the schema rules can execute system commands; thus, by exploiting the vulnerability, an attacker can run arbitrary code on the image that invokes Yamale.
https://github.com/23andMe/Yamale/pull/165
https://github.com/23andMe/Yamale/releases/tag/3.0.8

Yamale version 4.0.0 includes a fix for a RCE vulnerability.
https://github.com/23andMe/Yamale/issues/167