{"id":"CVE-2021-29510","aliases":["DEBIAN-CVE-2021-29510","EUVD-2021-0206","GHSA-5jqp-qgf6-3pvh","PYSEC-2021-47","UBUNTU-CVE-2021-29510","USN-6553-1","openSUSE-SU-2024:11254-1","openSUSE-SU-2024:13869-1","openSUSE-SU-2026:11424-1"],"status":"published","title":"Use of \"infinity\" as an input to datetime and date fields causes infinite loop in pydantic","description":"Pydantic is a data validation and settings management using Python type hinting. In affected versions 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.","severity":{"version":"3.1","score":3.3,"vector":"CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:L","level":"low","assessor":"cna","from":"cve"},"epss":{"day":"2026-11-11","score":0.00975,"percentile":0.62528,"model":"v2026.06.15"},"facts":{"in_kev":false,"known_exploited":false,"public_exploit":false,"fix_available":true},"cwes":["CWE-835"],"published":"2021-05-13T18:55:11Z","modified":"2026-10-23T18:03:08Z","fixes":[{"ecosystem":"PyPI","package":"pydantic","fixed_in":["1.6.2","1.8.2","1.7.4"],"sources":["ghsa","osv"]},{"ecosystem":"Debian:12","package":"pydantic","fixed_in":["1.7.4-1"],"sources":["osv"]},{"ecosystem":"Debian:13","package":"pydantic","fixed_in":["1.7.4-1"],"sources":["osv"]},{"ecosystem":"Debian:14","package":"pydantic","fixed_in":["1.7.4-1"],"sources":["osv"]},{"ecosystem":"Ubuntu:Pro:20.04:LTS","package":"pydantic","fixed_in":["1.2-1ubuntu0.1~esm1"],"sources":["osv"]}],"affected":[{"source":"ghsa","ecosystem":"PyPI","package":"pydantic","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.6.2"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"pydantic","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"1.8"},{"fixed":"1.8.2"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"pydantic","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"1.7"},{"fixed":"1.7.4"}]}]},{"source":"osv","ecosystem":"Debian:12","package":"pydantic","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.7.4-1"}]}]},{"source":"osv","ecosystem":"Debian:13","package":"pydantic","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.7.4-1"}]}]},{"source":"osv","ecosystem":"Debian:14","package":"pydantic","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.7.4-1"}]}]},{"source":"osv","ecosystem":"PyPI","package":"pydantic","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.6.2"}]}],"versions":["0.0.1","0.0.2","0.0.3","0.0.4","0.0.5","0.0.6","0.0.7","0.0.8","0.1","0.10","0.11","0.11.1","0.11.2","0.12","0.12.1","0.13","0.13.1","0.14","0.15","0.16","0.16.1","0.17","0.18","0.18.1","0.18.2","0.19","0.2","0.2.1","0.20","0.20.1","0.20a1","0.21","0.22","0.23","0.24","0.25","0.26","0.27","0.27a1","0.28","0.29","0.3","0.30","0.30.1","0.31","0.31.1","0.32","0.32.1","0.32.2","0.4","0.5","0.6","0.6.1","0.6.2","0.6.3","0.6.4","0.7","0.7.1","0.8","0.9","0.9.1","1.0","1.0b1","1.0b2","1.1","1.1.1","1.2","1.3","1.4","1.5","1.5.1","1.6","1.6.1"]},{"source":"osv","ecosystem":"PyPI","package":"pydantic","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"1.8"},{"fixed":"1.8.2"}]}],"versions":["1.8","1.8.1"]},{"source":"osv","ecosystem":"PyPI","package":"pydantic","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"1.7"},{"fixed":"1.7.4"}]}],"versions":["1.7","1.7.1","1.7.2","1.7.3"]},{"source":"osv","ecosystem":"PyPI","package":"pydantic","ranges":[{"type":"GIT","events":[{"introduced":"0"},{"fixed":"7e83fdd2563ffac081db7ecdf1affa65ef38c468"}]},{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.6.2"},{"introduced":"1.7"},{"fixed":"1.7.4"},{"introduced":"1.8"},{"fixed":"1.8.2"}]}],"versions":["0.0.1","0.0.2","0.0.3","0.0.4","0.0.5","0.0.6","0.0.7","0.0.8","0.1","0.10","0.11","0.11.1","0.11.2","0.12","0.12.1","0.13","0.13.1","0.14","0.15","0.16","0.16.1","0.17","0.18","0.18.1","0.18.2","0.19","0.2","0.2.1","0.20","0.20.1","0.20a1","0.21","0.22","0.23","0.24","0.25","0.26","0.27","0.27a1","0.28","0.29","0.3","0.30","0.30.1","0.31","0.31.1","0.32","0.32.1","0.32.2","0.4","0.5","0.6","0.6.1","0.6.2","0.6.3","0.6.4","0.7","0.7.1","0.8","0.9","0.9.1","1.0","1.0b1","1.0b2","1.1","1.1.1","1.2","1.3","1.4","1.5","1.5.1","1.6","1.6.1","1.7","1.7.1","1.7.2","1.7.3","1.8","1.8.1","v1.6.1","v1.8.1","v1.8","v1.7.2","v1.7.1","v1.7","v1.6","v1.5.1","v1.5","v1.4","v1.3","v1.2","v1.1","v1.0","v1.0b2","v1.0b1","v0.32","v0.31.1","v0.31","v0.30.1","v0.30","v0.29","v0.28","v0.27","v0.26","v0.25","v0.24","v0.23","v0.22","v0.21","v0.20.1","v0.20","v0.20a1","v0.19","v0.18.2","v0.18.1","v0.18","V0.17","v0.16.1","v0.16","v0.15","v0.14","v0.13.1","v0.13","v0.12.1","v0.12","v0.11.2","v0.11.1","v0.11","v0.10","v0.9.1","v0.9","v0.8","v0.7.1","v0.7","v0.6.4","v0.6.3","v0.6.2","v0.6.1","v0.6","v0.5","v0.4","v0.3","v0.2.1","v0.2","v0.1","v0.0.8","v0.0.7","v0.0.6","v0.0.5","v0.0.4","v0.0.3","v0.0.2"]},{"source":"osv","ecosystem":"Ubuntu:Pro:20.04:LTS","package":"pydantic","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.2-1ubuntu0.1~esm1"}]}],"versions":["0.30.1-1","1.2-1"]},{"source":"osv","ecosystem":"Ubuntu:Pro:20.04:LTS","package":"pydantic","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.2-1ubuntu0.1~esm1"}]}],"versions":["0.30.1-1","1.2-1"]},{"source":"osv","ecosystem":"openSUSE:Tumbleweed","package":"python-pydantic","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.13.4-2.1"}]}],"bundled":2}],"products":[{"vendor":"fedoraproject","product":"fedora"},{"vendor":"pydantic","product":"pydantic"},{"vendor":"samuelcolvin","product":"pydantic"}],"references":[{"url":"https://github.com/samuelcolvin/pydantic/security/advisories/GHSA-5jqp-qgf6-3pvh","tags":["x_refsource_CONFIRM","x_transferred","Mitigation","Patch","Third Party Advisory","fix","web","advisory"]},{"url":"https://github.com/samuelcolvin/pydantic/commit/7e83fdd2563ffac081db7ecdf1affa65ef38c468","tags":["x_refsource_MISC","x_transferred","Patch","Third Party Advisory","fix","web"]},{"url":"https://lists.fedoraproject.org/archives/list/package-announce%40lists.fedoraproject.org/message/UMKAJX4O6IGBBCE32CO2G7PZQCCQSBLV/","tags":["vendor-advisory","x_refsource_FEDORA","x_transferred","web"]},{"url":"https://lists.fedoraproject.org/archives/list/package-announce%40lists.fedoraproject.org/message/S2HT266L6Q7H6ICP7DFGXOGBJHNNKMKB/","tags":["vendor-advisory","x_refsource_FEDORA","x_transferred","web"]},{"url":"https://lists.fedoraproject.org/archives/list/package-announce%40lists.fedoraproject.org/message/UEFWM7DYKD2ZHE7R5YT5EQWJPV4ZKYRB/","tags":["vendor-advisory","x_refsource_FEDORA","x_transferred","web"]},{"url":"https://nvd.nist.gov/vuln/detail/CVE-2021-29510","tags":["advisory"]},{"url":"https://github.com/pydantic/pydantic/commit/1c24f1d74ba95ea985b50bdc001ce96c813229aa","tags":["web"]},{"url":"https://github.com/pydantic/pydantic/commit/80e0dd3f752bef145dce12f160d262bb40ec8d47","tags":["web"]},{"url":"https://github.com/pydantic/pydantic/commit/bdde15b7b947c94ca00fd6eb92da8db390a13520","tags":["web"]},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/pydantic/PYSEC-2021-47.yaml","tags":["web"]},{"url":"https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/S2HT266L6Q7H6ICP7DFGXOGBJHNNKMKB","tags":["web"]},{"url":"https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/UEFWM7DYKD2ZHE7R5YT5EQWJPV4ZKYRB","tags":["web"]},{"url":"https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/UMKAJX4O6IGBBCE32CO2G7PZQCCQSBLV","tags":["web"]},{"url":"https://github.com/advisories/GHSA-5jqp-qgf6-3pvh"},{"url":"https://security-tracker.debian.org/tracker/CVE-2021-29510","tags":["advisory"]},{"url":"https://github.com/pydantic/pydantic","tags":["package"]},{"url":"https://ubuntu.com/security/CVE-2021-29510","tags":["report"]},{"url":"https://ubuntu.com/security/notices/USN-6553-1","tags":["advisory"]},{"url":"https://www.cve.org/CVERecord?id=CVE-2021-29510","tags":["report"]},{"url":"","tags":["advisory"]},{"url":"https://www.suse.com/security/cve/CVE-2021-29510","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2024-3772","tags":["web"]}],"sources":{"cve":[{"id":"CVE-2021-29510","title":"Use of \"infinity\" as an input to datetime and date fields causes infinite loop in pydantic","description":"Pydantic is a data validation and settings management using Python type hinting. In affected versions 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.","status":"published","published":"2021-05-13T18:55:11Z","modified":"2024-08-03T22:11:05.442Z","cvss":[{"version":"3.1","score":3.3,"vector":"CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:L","level":"low","assessor":"cna"}],"cwes":["CWE-835"],"updated_at":"2026-11-02T14:33:06.32268Z"}],"euvd":[{"id":"EUVD-2021-0206","description":"Pydantic is a data validation and settings management using Python type hinting. In affected versions 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.","status":"published","published":"2021-05-13T18:55:11Z","modified":"2024-08-03T22:11:05Z","cvss":[{"version":"3.1","score":3.3,"vector":"CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:L","level":"low"}],"updated_at":"2026-11-03T03:24:44.540278Z"}],"ghsa":[{"id":"GHSA-5jqp-qgf6-3pvh","title":"Use of \"infinity\" as an input to datetime and date fields causes infinite loop in pydantic","description":"Impact\n\nPassing 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).\nPatches\n\nPydantic is be patched with fixes available in the following versions:\n\n    v1.8.2\n    v1.7.4\n    v1.6.2\n\nAll these versions are available on pypi, and will be available on conda-forge soon.\n\nSee the changelog for details.\nWorkarounds\n\nIf you absolutely can't upgrade, you can work around this risk using a validator to catch these values, brief demo:\n\nfrom datetime import date\nfrom pydantic import BaseModel, validator\n\nclass DemoModel(BaseModel):\n    date_of_birth: date\n\n    @validator('date_of_birth', pre=True)\n    def skip_infinite_values(cls, v):\n        try:\n            seconds = float(v)\n        except (ValueError, TypeError):\n            return v\n        else:\n            if seconds == float('inf'):\n                return date.max\n            elif seconds == float('-inf'):\n                return date.min\n            else:\n                return seconds\n\nNote: 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.\n\nIf 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.\nReferences\n\nThis was fixed in commit 7e83fdd.","status":"published","published":"2021-05-13T20:23:17Z","modified":"2026-06-09T13:01:02Z","cvss":[{"version":"4.0","score":5.3,"vector":"CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N","level":"medium"},{"version":"3.1","score":3.3,"vector":"CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:L","level":"low"}],"cwes":["CWE-835"],"updated_at":"2026-11-02T14:40:24.856614Z"}],"nvd":[{"id":"CVE-2021-29510","description":"Pydantic is a data validation and settings management using Python type hinting. In affected versions 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.","status":"published","published":"2021-05-13T19:15:08.023Z","modified":"2026-06-17T03:47:48.193Z","cvss":[{"version":"3.1","score":3.3,"vector":"CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:L","level":"low","assessor":"secondary"},{"version":"3.1","score":7.5,"vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"high","assessor":"primary"},{"version":"2.0","score":5,"vector":"AV:N/AC:L/Au:N/C:N/I:N/A:P","level":"medium","assessor":"primary"}],"cwes":["CWE-835"],"updated_at":"2026-11-02T14:06:53.343329Z"}],"osv":[{"id":"CVE-2021-29510","description":"Pydantic is a data validation and settings management using Python type hinting. In affected versions 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.","status":"published","published":"2021-05-13T19:15:08.023Z","modified":"2026-10-20T10:55:15.024628687Z","cvss":[{"version":"3.1","score":7.5,"vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"high"}],"updated_at":"2026-11-02T15:44:19.129331Z"},{"id":"DEBIAN-CVE-2021-29510","description":"Pydantic is a data validation and settings management using Python type hinting. In affected versions 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.","status":"published","published":"2021-05-13T19:15:08.023Z","modified":"2026-10-23T18:03:08.788482172Z","cvss":[{"version":"3.1","score":7.5,"vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"high"}],"updated_at":"2026-11-02T15:45:34.94143Z"},{"id":"GHSA-5jqp-qgf6-3pvh","title":"Use of \"infinity\" as an input to datetime and date fields causes infinite loop in pydantic","description":"Impact\n\nPassing 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).\nPatches\n\nPydantic is be patched with fixes available in the following versions:\n\n    v1.8.2\n    v1.7.4\n    v1.6.2\n\nAll these versions are available on pypi, and will be available on conda-forge soon.\n\nSee the changelog for details.\nWorkarounds\n\nIf you absolutely can't upgrade, you can work around this risk using a validator to catch these values, brief demo:\n\nfrom datetime import date\nfrom pydantic import BaseModel, validator\n\nclass DemoModel(BaseModel):\n    date_of_birth: date\n\n    @validator('date_of_birth', pre=True)\n    def skip_infinite_values(cls, v):\n        try:\n            seconds = float(v)\n        except (ValueError, TypeError):\n            return v\n        else:\n            if seconds == float('inf'):\n                return date.max\n            elif seconds == float('-inf'):\n                return date.min\n            else:\n                return seconds\n\nNote: 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.\n\nIf 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.\nReferences\n\nThis was fixed in commit 7e83fdd.","status":"published","published":"2021-05-13T20:23:17Z","modified":"2026-07-08T06:29:37.05196977Z","cvss":[{"version":"3.1","score":3.3,"vector":"CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:L","level":"low"},{"version":"4.0","score":5.3,"vector":"CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N","level":"medium"}],"cwes":["CWE-835"],"updated_at":"2026-11-02T15:46:38.553953Z"},{"id":"UBUNTU-CVE-2021-29510","description":"Pydantic is a data validation and settings management using Python type hinting. In affected versions 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.","status":"published","published":"2021-05-13T19:15:00Z","modified":"2026-02-04T03:13:40.268935Z","cvss":[{"version":"3.1","score":3.3,"vector":"CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:L","level":"low"},{"version":"3.1","score":7.5,"vector":"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"high"}],"updated_at":"2026-11-02T15:54:26.779273Z"},{"id":"openSUSE-SU-2024:11254-1","title":"python36-pydantic-1.8.2-1.2 on GA media","description":"These are all security issues fixed in the python36-pydantic-1.8.2-1.2 package on the GA media of openSUSE Tumbleweed.","status":"published","published":"2024-06-15T00:00:00Z","modified":"2026-02-04T03:07:29.043237Z","updated_at":"2026-11-02T16:58:34.894275Z"},{"id":"openSUSE-SU-2024:13869-1","title":"python310-pydantic-2.6.4-2.1 on GA media","description":"These are all security issues fixed in the python310-pydantic-2.6.4-2.1 package on the GA media of openSUSE Tumbleweed.","status":"published","published":"2024-06-15T00:00:00Z","modified":"2026-02-04T03:11:59.509582Z","updated_at":"2026-11-02T16:58:36.662953Z"},{"id":"openSUSE-SU-2026:11424-1","title":"python313-pydantic-2.13.4-2.1 on GA media","description":"These are all security issues fixed in the python313-pydantic-2.13.4-2.1 package on the GA media of openSUSE Tumbleweed.","status":"published","published":"2026-08-01T00:00:00Z","modified":"2026-08-02T11:45:08.021742428Z","updated_at":"2026-11-02T16:58:39.516824Z"},{"id":"PYSEC-2021-47","description":"Pydantic is a data validation and settings management using Python type hinting. In affected versions 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.","status":"published","published":"2021-05-13T19:15:00Z","modified":"2026-06-08T11:15:47.381921256Z","updated_at":"2026-11-02T15:52:53.119977Z"},{"id":"USN-6553-1","title":"pydantic vulnerability","description":"Nina Jensen discovered that Pydantic incorrectly handled user input in the\ndate and datetime fields. An attacker could possibly use this issue to\ncause a denial of service via application crash. (CVE-2021-29510)\n","status":"published","published":"2023-12-12T17:47:24Z","modified":"2026-02-10T04:43:27Z","updated_at":"2026-11-02T16:58:17.305935Z"}]}}