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    <link>https://cve.radiocsirt.org</link>
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    <item>
      <title>BREW-pydantic-CVE-2021-29510 — Use of "infinity" as an input to datetime and date fields causes infinite loop in pydantic</title>
      <link>https://cve.radiocsirt.org/vuln/brew-pydantic-cve-2021-29510</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; Homebrew: pydantic&lt;/p&gt;
&lt;p&gt;Impact&lt;/p&gt;
&lt;p&gt;Passing either &amp;#39;infinity&amp;#39;, &amp;#39;inf&amp;#39; or float(&amp;#39;inf&amp;#39;) (or their negatives) to datetime or date fields causes validation to run forever with 100% CPU usage (on one CPU).
Patches&lt;/p&gt;
&lt;p&gt;Pydantic is be patched with fixes available in the following versions:&lt;/p&gt;
&lt;p&gt;v1.8.2
    v1.7.4
    v1.6.2&lt;/p&gt;
&lt;p&gt;All these versions are available on pypi, and will be available on conda-forge soon.&lt;/p&gt;
&lt;p&gt;See the changelog for details.
Workarounds&lt;/p&gt;
&lt;p&gt;If you absolutely can&amp;#39;t upgrade, you can work around this risk using a validator to catch these values, brief demo:&lt;/p&gt;
&lt;p&gt;from datetime import date
from pydantic import BaseModel, validator&lt;/p&gt;
&lt;p&gt;class DemoModel(BaseModel):
    date_of_birth: date&lt;/p&gt;
&lt;p&gt;@validator(&amp;#39;date_of_birth&amp;#39;, pre=True)
    def skip_infinite_values(cls, v):
        try:
            seconds = float(v)
        except (ValueError, TypeError):
            return v
        else:
            if seconds == float(&amp;#39;inf&amp;#39;):
                return date.max
            elif seconds == float(&amp;#39;-inf&amp;#39;):
                return date.min
            else:
                return seconds&lt;/p&gt;
&lt;p&gt;Note: this is not an ideal solution (in particular you&amp;#39;ll need a slightly different function for datetimes), instead of a hack like this you should upgrade pydantic.&lt;/p&gt;
&lt;p&gt;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 requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic.
References&lt;/p&gt;
&lt;p&gt;This was fixed in commit 7e83fdd.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; Homebrew: pydantic&lt;/p&gt;
&lt;p&gt;Impact&lt;/p&gt;
&lt;p&gt;Passing either &amp;#39;infinity&amp;#39;, &amp;#39;inf&amp;#39; or float(&amp;#39;inf&amp;#39;) (or their negatives) to datetime or date fields causes validation to run forever with 100% CPU usage (on one CPU).
Patches&lt;/p&gt;
&lt;p&gt;Pydantic is be patched with fixes available in the following versions:&lt;/p&gt;
&lt;p&gt;v1.8.2
    v1.7.4
    v1.6.2&lt;/p&gt;
&lt;p&gt;All these versions are available on pypi, and will be available on conda-forge soon.&lt;/p&gt;
&lt;p&gt;See the changelog for details.
Workarounds&lt;/p&gt;
&lt;p&gt;If you absolutely can&amp;#39;t upgrade, you can work around this risk using a validator to catch these values, brief demo:&lt;/p&gt;
&lt;p&gt;from datetime import date
from pydantic import BaseModel, validator&lt;/p&gt;
&lt;p&gt;class DemoModel(BaseModel):
    date_of_birth: date&lt;/p&gt;
&lt;p&gt;@validator(&amp;#39;date_of_birth&amp;#39;, pre=True)
    def skip_infinite_values(cls, v):
        try:
            seconds = float(v)
        except (ValueError, TypeError):
            return v
        else:
            if seconds == float(&amp;#39;inf&amp;#39;):
                return date.max
            elif seconds == float(&amp;#39;-inf&amp;#39;):
                return date.min
            else:
                return seconds&lt;/p&gt;
&lt;p&gt;Note: this is not an ideal solution (in particular you&amp;#39;ll need a slightly different function for datetimes), instead of a hack like this you should upgrade pydantic.&lt;/p&gt;
&lt;p&gt;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 requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic.
References&lt;/p&gt;
&lt;p&gt;This was fixed in commit 7e83fdd.&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/brew-pydantic-cve-2021-29510</guid>
    </item>
    <item>
      <title>CVE-2021-29510 — Use of "infinity" as an input to datetime and date fields causes infinite loop in pydantic</title>
      <link>https://cve.radiocsirt.org/vuln/cve-2021-29510</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; samuelcolvin pydantic&lt;/p&gt;
&lt;p&gt;Pydantic is a data validation and settings management using Python type hinting. In affected versions passing either `&amp;#39;infinity&amp;#39;`, `&amp;#39;inf&amp;#39;` or `float(&amp;#39;inf&amp;#39;)` (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&amp;#39;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&amp;#39;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.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; samuelcolvin pydantic&lt;/p&gt;
&lt;p&gt;Pydantic is a data validation and settings management using Python type hinting. In affected versions passing either `&amp;#39;infinity&amp;#39;`, `&amp;#39;inf&amp;#39;` or `float(&amp;#39;inf&amp;#39;)` (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&amp;#39;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&amp;#39;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.&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/cve-2021-29510</guid>
    </item>
    <item>
      <title>GHSA-5jqp-qgf6-3pvh — Use of "infinity" as an input to datetime and date fields causes infinite loop in pydantic</title>
      <link>https://cve.radiocsirt.org/vuln/ghsa-5jqp-qgf6-3pvh</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: pydantic&lt;/p&gt;
&lt;p&gt;Impact&lt;/p&gt;
&lt;p&gt;Passing either &amp;#39;infinity&amp;#39;, &amp;#39;inf&amp;#39; or float(&amp;#39;inf&amp;#39;) (or their negatives) to datetime or date fields causes validation to run forever with 100% CPU usage (on one CPU).
Patches&lt;/p&gt;
&lt;p&gt;Pydantic is be patched with fixes available in the following versions:&lt;/p&gt;
&lt;p&gt;v1.8.2
    v1.7.4
    v1.6.2&lt;/p&gt;
&lt;p&gt;All these versions are available on pypi, and will be available on conda-forge soon.&lt;/p&gt;
&lt;p&gt;See the changelog for details.
Workarounds&lt;/p&gt;
&lt;p&gt;If you absolutely can&amp;#39;t upgrade, you can work around this risk using a validator to catch these values, brief demo:&lt;/p&gt;
&lt;p&gt;from datetime import date
from pydantic import BaseModel, validator&lt;/p&gt;
&lt;p&gt;class DemoModel(BaseModel):
    date_of_birth: date&lt;/p&gt;
&lt;p&gt;@validator(&amp;#39;date_of_birth&amp;#39;, pre=True)
    def skip_infinite_values(cls, v):
        try:
            seconds = float(v)
        except (ValueError, TypeError):
            return v
        else:
            if seconds == float(&amp;#39;inf&amp;#39;):
                return date.max
            elif seconds == float(&amp;#39;-inf&amp;#39;):
                return date.min
            else:
                return seconds&lt;/p&gt;
&lt;p&gt;Note: this is not an ideal solution (in particular you&amp;#39;ll need a slightly different function for datetimes), instead of a hack like this you should upgrade pydantic.&lt;/p&gt;
&lt;p&gt;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 requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic.
References&lt;/p&gt;
&lt;p&gt;This was fixed in commit 7e83fdd.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: pydantic&lt;/p&gt;
&lt;p&gt;Impact&lt;/p&gt;
&lt;p&gt;Passing either &amp;#39;infinity&amp;#39;, &amp;#39;inf&amp;#39; or float(&amp;#39;inf&amp;#39;) (or their negatives) to datetime or date fields causes validation to run forever with 100% CPU usage (on one CPU).
Patches&lt;/p&gt;
&lt;p&gt;Pydantic is be patched with fixes available in the following versions:&lt;/p&gt;
&lt;p&gt;v1.8.2
    v1.7.4
    v1.6.2&lt;/p&gt;
&lt;p&gt;All these versions are available on pypi, and will be available on conda-forge soon.&lt;/p&gt;
&lt;p&gt;See the changelog for details.
Workarounds&lt;/p&gt;
&lt;p&gt;If you absolutely can&amp;#39;t upgrade, you can work around this risk using a validator to catch these values, brief demo:&lt;/p&gt;
&lt;p&gt;from datetime import date
from pydantic import BaseModel, validator&lt;/p&gt;
&lt;p&gt;class DemoModel(BaseModel):
    date_of_birth: date&lt;/p&gt;
&lt;p&gt;@validator(&amp;#39;date_of_birth&amp;#39;, pre=True)
    def skip_infinite_values(cls, v):
        try:
            seconds = float(v)
        except (ValueError, TypeError):
            return v
        else:
            if seconds == float(&amp;#39;inf&amp;#39;):
                return date.max
            elif seconds == float(&amp;#39;-inf&amp;#39;):
                return date.min
            else:
                return seconds&lt;/p&gt;
&lt;p&gt;Note: this is not an ideal solution (in particular you&amp;#39;ll need a slightly different function for datetimes), instead of a hack like this you should upgrade pydantic.&lt;/p&gt;
&lt;p&gt;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 requesting a back-port, and we will endeavour to release a patch for earlier versions of pydantic.
References&lt;/p&gt;
&lt;p&gt;This was fixed in commit 7e83fdd.&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/ghsa-5jqp-qgf6-3pvh</guid>
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