{"id":"CVE-2022-29207","aliases":["BIT-tensorflow-2022-29207","EUVD-2022-2670","GHSA-5wpj-c6f7-24x8","PYSEC-2026-3112","PYSEC-2026-3280","PYSEC-2026-955"],"status":"published","title":"Undefined behavior when users supply invalid resource handles in TensorFlow","description":"TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, multiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid. In graph mode, it would have been impossible to perform these API calls, but migration to TF 2.x eager mode opened up this vulnerability. If the resource handle is empty, then a reference is bound to a null pointer inside TensorFlow codebase (various codepaths). This is undefined behavior. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.","severity":{"version":"3.1","score":5.5,"vector":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H","level":"medium","assessor":"cna","from":"cve"},"epss":{"day":"2026-11-09","score":0.00325,"percentile":0.25757,"model":"v2026.06.15"},"facts":{"in_kev":false,"known_exploited":false,"public_exploit":false,"fix_available":true},"cwes":["CWE-20","CWE-475"],"published":"2022-05-20T22:10:12Z","modified":"2026-10-28T10:28:44Z","fixes":[{"ecosystem":"PyPI","package":"tensorflow","fixed_in":["2.6.4","2.7.2","2.8.1"],"sources":["ghsa","osv"]},{"ecosystem":"PyPI","package":"tensorflow-cpu","fixed_in":["2.6.4","2.7.2","2.8.1"],"sources":["ghsa","osv"]},{"ecosystem":"PyPI","package":"tensorflow-gpu","fixed_in":["2.6.4","2.7.2","2.8.1"],"sources":["ghsa","osv"]},{"ecosystem":"Bitnami","package":"tensorflow","fixed_in":["2.6.4","2.7.2","2.8.1"],"sources":["osv"]}],"affected":[{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.6.4"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.7.0"},{"fixed":"2.7.2"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.8.0"},{"fixed":"2.8.1"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.6.4"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.7.0"},{"fixed":"2.7.2"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.8.0"},{"fixed":"2.8.1"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.6.4"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.7.0"},{"fixed":"2.7.2"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.8.0"},{"fixed":"2.8.1"}]}]},{"source":"osv","ecosystem":"Bitnami","package":"tensorflow","ranges":[{"type":"SEMVER","events":[{"introduced":"0"},{"fixed":"2.6.4"},{"introduced":"2.7.0"},{"fixed":"2.7.2"},{"introduced":"2.8.0"},{"fixed":"2.8.1"}]}]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.6.4"}]}],"versions":["0.12.0","0.12.1","1.0.0","1.0.1","1.1.0","1.10.0","1.10.1","1.11.0","1.12.0","1.12.2","1.12.3","1.13.1","1.13.2","1.14.0","1.15.0","1.15.2","1.15.3","1.15.4","1.15.5","1.2.0","1.2.1","1.3.0","1.4.0","1.4.1","1.5.0","1.5.1","1.6.0","1.7.0","1.7.1","1.8.0","1.9.0","2.0.0","2.0.1","2.0.2","2.0.3","2.0.4","2.1.0","2.1.1","2.1.2","2.1.3","2.1.4","2.2.0","2.2.1","2.2.2","2.2.3","2.3.0","2.3.1","2.3.2","2.3.3","2.3.4","2.4.0","2.4.1","2.4.2","2.4.3","2.4.4","2.5.0","2.5.1","2.5.2","2.5.3","2.6.0","2.6.0rc0","2.6.0rc1","2.6.0rc2","2.6.1","2.6.2","2.6.3"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.7.0"},{"fixed":"2.7.2"}]}],"versions":["2.7.0","2.7.1"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.8.0"},{"fixed":"2.8.1"}]}],"versions":["2.8.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.6.4"}]}],"versions":["1.15.0","2.1.0","2.1.1","2.1.2","2.1.3","2.1.4","2.2.0","2.2.1","2.2.2","2.2.3","2.3.0","2.3.1","2.3.2","2.3.3","2.3.4","2.4.0","2.4.1","2.4.2","2.4.3","2.4.4","2.5.0","2.5.1","2.5.2","2.5.3","2.6.0","2.6.1","2.6.2","2.6.3"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.7.0"},{"fixed":"2.7.2"}]}],"versions":["2.7.0","2.7.1"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.8.0"},{"fixed":"2.8.1"}]}],"versions":["2.8.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.6.4"}]}],"versions":["0.12.0","0.12.1","1.0.0","1.0.1","1.1.0","1.10.0","1.10.1","1.11.0","1.12.0","1.12.2","1.12.3","1.13.1","1.13.2","1.14.0","1.15.0","1.15.2","1.15.3","1.15.4","1.15.5","1.2.0","1.2.1","1.3.0","1.4.0","1.4.1","1.5.0","1.5.1","1.6.0","1.7.0","1.7.1","1.8.0","1.9.0","2.0.0","2.0.1","2.0.2","2.0.3","2.0.4","2.1.0","2.1.1","2.1.2","2.1.3","2.1.4","2.2.0","2.2.1","2.2.2","2.2.3","2.3.0","2.3.1","2.3.2","2.3.3","2.3.4","2.4.0","2.4.1","2.4.2","2.4.3","2.4.4","2.5.0","2.5.1","2.5.2","2.5.3","2.6.0","2.6.1","2.6.2","2.6.3"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.7.0"},{"fixed":"2.7.2"}]}],"versions":["2.7.0","2.7.1"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.8.0"},{"fixed":"2.8.1"}]}],"versions":["2.8.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.6.4"},{"introduced":"2.7.0"},{"fixed":"2.7.2"},{"introduced":"2.8.0"},{"fixed":"2.8.1"}]}],"versions":["0.12.0","0.12.1","1.0.0","1.0.1","1.1.0","1.10.0","1.10.1","1.11.0","1.12.0","1.12.2","1.12.3","1.13.1","1.13.2","1.14.0","1.15.0","1.15.2","1.15.3","1.15.4","1.15.5","1.2.0","1.2.1","1.3.0","1.4.0","1.4.1","1.5.0","1.5.1","1.6.0","1.7.0","1.7.1","1.8.0","1.9.0","2.0.0","2.0.1","2.0.2","2.0.3","2.0.4","2.1.0","2.1.1","2.1.2","2.1.3","2.1.4","2.2.0","2.2.1","2.2.2","2.2.3","2.3.0","2.3.1","2.3.2","2.3.3","2.3.4","2.4.0","2.4.1","2.4.2","2.4.3","2.4.4","2.5.0","2.5.1","2.5.2","2.5.3","2.6.0","2.6.0rc0","2.6.0rc1","2.6.0rc2","2.6.1","2.6.2","2.6.3","2.7.0","2.7.1","2.8.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.6.4"},{"introduced":"2.7.0"},{"fixed":"2.7.2"},{"introduced":"2.8.0"},{"fixed":"2.8.1"}]}],"versions":["1.15.0","2.1.0","2.1.1","2.1.2","2.1.3","2.1.4","2.2.0","2.2.1","2.2.2","2.2.3","2.3.0","2.3.1","2.3.2","2.3.3","2.3.4","2.4.0","2.4.1","2.4.2","2.4.3","2.4.4","2.5.0","2.5.1","2.5.2","2.5.3","2.6.0","2.6.1","2.6.2","2.6.3","2.7.0","2.7.1","2.8.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.6.4"},{"introduced":"2.7.0"},{"fixed":"2.7.2"},{"introduced":"2.8.0"},{"fixed":"2.8.1"}]}],"versions":["0.12.0","0.12.1","1.0.0","1.0.1","1.1.0","1.10.0","1.10.1","1.11.0","1.12.0","1.12.2","1.12.3","1.13.1","1.13.2","1.14.0","1.15.0","1.15.2","1.15.3","1.15.4","1.15.5","1.2.0","1.2.1","1.3.0","1.4.0","1.4.1","1.5.0","1.5.1","1.6.0","1.7.0","1.7.1","1.8.0","1.9.0","2.0.0","2.0.1","2.0.2","2.0.3","2.0.4","2.1.0","2.1.1","2.1.2","2.1.3","2.1.4","2.2.0","2.2.1","2.2.2","2.2.3","2.3.0","2.3.1","2.3.2","2.3.3","2.3.4","2.4.0","2.4.1","2.4.2","2.4.3","2.4.4","2.5.0","2.5.1","2.5.2","2.5.3","2.6.0","2.6.1","2.6.2","2.6.3","2.7.0","2.7.1","2.8.0"]}],"products":[{"vendor":"google","product":"tensorflow"},{"vendor":"tensorflow","product":"tensorflow"}],"references":[{"url":"https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4","tags":["x_refsource_MISC","x_transferred","Release Notes","Third Party Advisory","advisory","web"]},{"url":"https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2","tags":["x_refsource_MISC","x_transferred","Release Notes","Third Party Advisory","advisory","web"]},{"url":"https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1","tags":["x_refsource_MISC","x_transferred","Release Notes","Third Party Advisory","advisory","web"]},{"url":"https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0","tags":["x_refsource_MISC","x_transferred","Release Notes","Third Party Advisory","advisory","web"]},{"url":"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5wpj-c6f7-24x8","tags":["x_refsource_CONFIRM","x_transferred","Exploit","Patch","Third Party Advisory","advisory","web"]},{"url":"https://github.com/tensorflow/tensorflow/commit/a5b89cd68c02329d793356bda85d079e9e69b4e7","tags":["x_refsource_MISC","x_transferred","Patch","Third Party Advisory","advisory","fix","web"]},{"url":"https://github.com/tensorflow/tensorflow/commit/dbdd98c37bc25249e8f288bd30d01e118a7b4498","tags":["x_refsource_MISC","x_transferred","Patch","Third Party Advisory","advisory","fix","web"]},{"url":"https://nvd.nist.gov/vuln/detail/CVE-2022-29207","tags":["web","advisory"]},{"url":"https://github.com/advisories/GHSA-5wpj-c6f7-24x8","tags":["advisory"]},{"url":"https://github.com/CVEProject/cvelistV5/tree/main/cves/2022/29xxx/CVE-2022-29207.json","tags":["advisory"]},{"url":"https://github.com/tensorflow/tensorflow","tags":["package"]},{"url":"https://pypi.org/project/tensorflow","tags":["package"]},{"url":"https://pypi.org/project/tensorflow-cpu","tags":["package"]},{"url":"https://pypi.org/project/tensorflow-gpu","tags":["package"]}],"sources":{"cve":[{"id":"CVE-2022-29207","title":"Undefined behavior when users supply invalid resource handles in TensorFlow","description":"TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, multiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid. In graph mode, it would have been impossible to perform these API calls, but migration to TF 2.x eager mode opened up this vulnerability. If the resource handle is empty, then a reference is bound to a null pointer inside TensorFlow codebase (various codepaths). This is undefined behavior. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.","status":"published","published":"2022-05-20T22:10:12Z","modified":"2025-04-22T17:58:48.272Z","cvss":[{"version":"3.1","score":5.5,"vector":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H","level":"medium","assessor":"cna"}],"cwes":["CWE-20","CWE-475"],"updated_at":"2026-11-02T14:34:36.270817Z"}],"euvd":[{"id":"EUVD-2022-2670","description":"TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, multiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid. In graph mode, it would have been impossible to perform these API calls, but migration to TF 2.x eager mode opened up this vulnerability. If the resource handle is empty, then a reference is bound to a null pointer inside TensorFlow codebase (various codepaths). This is undefined behavior. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.","status":"published","published":"2022-05-20T22:10:12Z","modified":"2025-04-22T17:58:48Z","cvss":[{"version":"3.1","score":5.5,"vector":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H","level":"medium"}],"updated_at":"2026-11-02T20:52:15.540112Z"}],"ghsa":[{"id":"GHSA-5wpj-c6f7-24x8","title":"Undefined behavior when users supply invalid resource handles","description":"### Impact\nMultiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid:\n\n```python\nimport tensorflow as tf\n\ntf.raw_ops.QueueIsClosedV2(handle=[])\n```\n\n```python\nimport tensorflow as tf\n\ntf.summary.flush(writer=())\n```\n  \nIn graph mode, it would have been impossible to perform these API calls, but migration to TF 2.x eager mode opened up this vulnerability. If the resource handle is empty, then a reference is bound to a null pointer inside TensorFlow codebase (various codepaths). This is undefined behavior.\n\n### Patches\nWe have patched the issue in GitHub commit [a5b89cd68c02329d793356bda85d079e9e69b4e7](https://github.com/tensorflow/tensorflow/commit/a5b89cd68c02329d793356bda85d079e9e69b4e7) and GitHub commit [dbdd98c37bc25249e8f288bd30d01e118a7b4498](https://github.com/tensorflow/tensorflow/commit/dbdd98c37bc25249e8f288bd30d01e118a7b4498).\n\nThe fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range.\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis vulnerability has been reported by Hong Jin from Singapore Management University.","status":"published","published":"2022-05-24T22:13:59Z","modified":"2023-01-27T05:01:57Z","cvss":[{"version":"3.1","score":5.5,"vector":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H","level":"medium"}],"cwes":["CWE-20","CWE-475"],"updated_at":"2026-11-02T14:36:17.04874Z"}],"nvd":[{"id":"CVE-2022-29207","description":"TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, multiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid. In graph mode, it would have been impossible to perform these API calls, but migration to TF 2.x eager mode opened up this vulnerability. If the resource handle is empty, then a reference is bound to a null pointer inside TensorFlow codebase (various codepaths). This is undefined behavior. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.","status":"published","published":"2022-05-20T22:16:40.997Z","modified":"2026-06-17T04:39:49.437Z","cvss":[{"version":"3.1","score":5.5,"vector":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H","level":"medium","assessor":"secondary"},{"version":"3.1","score":5.5,"vector":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H","level":"medium","assessor":"primary"},{"version":"2.0","score":2.1,"vector":"AV:L/AC:L/Au:N/C:N/I:N/A:P","level":"low","assessor":"primary"}],"cwes":["CWE-20","CWE-475"],"updated_at":"2026-11-02T14:07:20.264424Z"}],"osv":[{"id":"CVE-2022-29207","title":"Undefined behavior when users supply invalid resource handles in TensorFlow","description":"TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, multiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid. In graph mode, it would have been impossible to perform these API calls, but migration to TF 2.x eager mode opened up this vulnerability. If the resource handle is empty, then a reference is bound to a null pointer inside TensorFlow codebase (various codepaths). This is undefined behavior. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.","status":"published","published":"2022-05-20T22:10:12Z","modified":"2026-10-28T10:28:44.698781718Z","cvss":[{"version":"3.1","score":5.5,"vector":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H","level":"medium"}],"cwes":["CWE-20","CWE-475"],"updated_at":"2026-11-02T15:44:25.164673Z"},{"id":"GHSA-5wpj-c6f7-24x8","title":"Undefined behavior when users supply invalid resource handles","description":"### Impact\nMultiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid:\n\n```python\nimport tensorflow as tf\n\ntf.raw_ops.QueueIsClosedV2(handle=[])\n```\n\n```python\nimport tensorflow as tf\n\ntf.summary.flush(writer=())\n```\n  \nIn graph mode, it would have been impossible to perform these API calls, but migration to TF 2.x eager mode opened up this vulnerability. If the resource handle is empty, then a reference is bound to a null pointer inside TensorFlow codebase (various codepaths). This is undefined behavior.\n\n### Patches\nWe have patched the issue in GitHub commit [a5b89cd68c02329d793356bda85d079e9e69b4e7](https://github.com/tensorflow/tensorflow/commit/a5b89cd68c02329d793356bda85d079e9e69b4e7) and GitHub commit [dbdd98c37bc25249e8f288bd30d01e118a7b4498](https://github.com/tensorflow/tensorflow/commit/dbdd98c37bc25249e8f288bd30d01e118a7b4498).\n\nThe fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range.\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis vulnerability has been reported by Hong Jin from Singapore Management University.","status":"published","published":"2022-05-24T22:13:59Z","modified":"2026-07-13T16:43:51.174587703Z","cvss":[{"version":"3.1","score":5.5,"vector":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H","level":"medium"}],"cwes":["CWE-20","CWE-475"],"updated_at":"2026-11-02T15:46:38.911014Z"},{"id":"PYSEC-2026-3112","title":"Undefined behavior when users supply invalid resource handles","description":"### Impact\nMultiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid:\n\n```python\nimport tensorflow as tf\n\ntf.raw_ops.QueueIsClosedV2(handle=[])\n```\n\n```python\nimport tensorflow as tf\n\ntf.summary.flush(writer=())\n```\n  \nIn graph mode, it would have been impossible to perform these API calls, but migration to TF 2.x eager mode opened up this vulnerability. If the resource handle is empty, then a reference is bound to a null pointer inside TensorFlow codebase (various codepaths). This is undefined behavior.\n\n### Patches\nWe have patched the issue in GitHub commit [a5b89cd68c02329d793356bda85d079e9e69b4e7](https://github.com/tensorflow/tensorflow/commit/a5b89cd68c02329d793356bda85d079e9e69b4e7) and GitHub commit [dbdd98c37bc25249e8f288bd30d01e118a7b4498](https://github.com/tensorflow/tensorflow/commit/dbdd98c37bc25249e8f288bd30d01e118a7b4498).\n\nThe fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range.\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis vulnerability has been reported by Hong Jin from Singapore Management University.","status":"published","published":"2026-07-09T16:49:50.12032Z","modified":"2026-07-13T16:43:51.174587703Z","cvss":[{"version":"3.1","score":5.5,"vector":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H","level":"medium"}],"updated_at":"2026-11-02T15:52:56.429374Z"},{"id":"PYSEC-2026-3280","title":"Undefined behavior when users supply invalid resource handles","description":"### Impact\nMultiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid:\n\n```python\nimport tensorflow as tf\n\ntf.raw_ops.QueueIsClosedV2(handle=[])\n```\n\n```python\nimport tensorflow as tf\n\ntf.summary.flush(writer=())\n```\n  \nIn graph mode, it would have been impossible to perform these API calls, but migration to TF 2.x eager mode opened up this vulnerability. If the resource handle is empty, then a reference is bound to a null pointer inside TensorFlow codebase (various codepaths). This is undefined behavior.\n\n### Patches\nWe have patched the issue in GitHub commit [a5b89cd68c02329d793356bda85d079e9e69b4e7](https://github.com/tensorflow/tensorflow/commit/a5b89cd68c02329d793356bda85d079e9e69b4e7) and GitHub commit [dbdd98c37bc25249e8f288bd30d01e118a7b4498](https://github.com/tensorflow/tensorflow/commit/dbdd98c37bc25249e8f288bd30d01e118a7b4498).\n\nThe fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range.\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis vulnerability has been reported by Hong Jin from Singapore Management University.","status":"published","published":"2026-07-09T16:49:50.212007Z","modified":"2026-07-13T16:43:51.174587703Z","cvss":[{"version":"3.1","score":5.5,"vector":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H","level":"medium"}],"updated_at":"2026-11-02T15:52:56.847083Z"},{"id":"PYSEC-2026-955","title":"Undefined behavior when users supply invalid resource handles","description":"### Impact\nMultiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid:\n\n```python\nimport tensorflow as tf\n\ntf.raw_ops.QueueIsClosedV2(handle=[])\n```\n\n```python\nimport tensorflow as tf\n\ntf.summary.flush(writer=())\n```\n  \nIn graph mode, it would have been impossible to perform these API calls, but migration to TF 2.x eager mode opened up this vulnerability. If the resource handle is empty, then a reference is bound to a null pointer inside TensorFlow codebase (various codepaths). This is undefined behavior.\n\n### Patches\nWe have patched the issue in GitHub commit [a5b89cd68c02329d793356bda85d079e9e69b4e7](https://github.com/tensorflow/tensorflow/commit/a5b89cd68c02329d793356bda85d079e9e69b4e7) and GitHub commit [dbdd98c37bc25249e8f288bd30d01e118a7b4498](https://github.com/tensorflow/tensorflow/commit/dbdd98c37bc25249e8f288bd30d01e118a7b4498).\n\nThe fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range.\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis vulnerability has been reported by Hong Jin from Singapore Management University.","status":"published","published":"2026-07-06T08:03:29.955414Z","modified":"2026-07-13T16:43:51.174587703Z","cvss":[{"version":"3.1","score":5.5,"vector":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H","level":"medium"}],"updated_at":"2026-11-02T15:52:58.117212Z"},{"id":"BIT-tensorflow-2022-29207","title":"Undefined behavior when users supply invalid resource handles in TensorFlow","description":"TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, multiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid. In graph mode, it would have been impossible to perform these API calls, but migration to TF 2.x eager mode opened up this vulnerability. If the resource handle is empty, then a reference is bound to a null pointer inside TensorFlow codebase (various codepaths). This is undefined behavior. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.","status":"published","published":"2024-03-06T11:14:21.385Z","modified":"2026-09-08T08:48:20.194964026Z","updated_at":"2026-11-02T15:28:35.51001Z"}]}}