{"id":"CVE-2022-41883","aliases":["BIT-tensorflow-2022-41883","EUVD-2022-7448","GHSA-w58w-79xv-6vcj","PYSEC-2026-1042","PYSEC-2026-3251","PYSEC-2026-3376"],"status":"published","title":"Out of bounds segmentation fault due to unequal op inputs in Tensorflow","description":"TensorFlow is an open source platform for machine learning. When ops that have specified input sizes receive a differing number of inputs, the executor will crash. We have patched the issue in GitHub commit f5381e0e10b5a61344109c1b7c174c68110f7629. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.","severity":{"version":"3.1","score":6.8,"vector":"CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:L/I:L/A:H","level":"medium","assessor":"cna","from":"cve"},"epss":{"day":"2026-11-09","score":0.00384,"percentile":0.32723,"model":"v2026.06.15"},"facts":{"in_kev":false,"known_exploited":false,"public_exploit":false,"fix_available":true},"cwes":["CWE-125"],"published":"2022-11-18T00:00:00Z","modified":"2026-10-28T10:28:28Z","fixes":[{"ecosystem":"PyPI","package":"tensorflow","fixed_in":["2.10.1"],"sources":["ghsa","osv"]},{"ecosystem":"PyPI","package":"tensorflow-cpu","fixed_in":["2.10.1"],"sources":["ghsa","osv"]},{"ecosystem":"PyPI","package":"tensorflow-gpu","fixed_in":["2.10.1"],"sources":["ghsa","osv"]},{"ecosystem":"Bitnami","package":"tensorflow","fixed_in":["2.10.1"],"sources":["osv"]}],"affected":[{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.10.0"},{"last_affected":"2.10.0"},{"fixed":"2.10.1"}]}],"versions":["2.10.0"]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.10.0"},{"last_affected":"2.10.0"},{"fixed":"2.10.1"}]}],"versions":["2.10.0"]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.10.0"},{"last_affected":"2.10.0"},{"fixed":"2.10.1"}]}],"versions":["2.10.0"]},{"source":"osv","ecosystem":"Bitnami","package":"tensorflow","ranges":[{"type":"SEMVER","events":[{"introduced":"2.10.0"},{"fixed":"2.10.1"}]}]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.10.0"},{"fixed":"2.10.1"}]}],"versions":["2.10.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.10.0"},{"fixed":"2.10.1"}]}],"versions":["2.10.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.10.0"},{"fixed":"2.10.1"}]}],"versions":["2.10.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.10.0"},{"fixed":"2.10.1"}]}],"versions":["2.10.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.10.0"},{"fixed":"2.10.1"}]}],"versions":["2.10.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.10.0"},{"fixed":"2.10.1"}]}],"versions":["2.10.0"]}],"products":[{"vendor":"google","product":"tensorflow"},{"vendor":"tensorflow","product":"tensorflow"}],"references":[{"url":"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-w58w-79xv-6vcj","tags":["x_transferred","Exploit","Patch","Third Party Advisory","advisory","web"]},{"url":"https://github.com/tensorflow/tensorflow/commit/f5381e0e10b5a61344109c1b7c174c68110f7629","tags":["x_transferred","Patch","Third Party Advisory","advisory","fix","web"]},{"url":"https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/dynamic_stitch_op.cc","tags":["x_transferred","Third Party Advisory","advisory","web"]},{"url":"https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ops/data_flow_ops.cc","tags":["x_transferred","Third Party Advisory","advisory","web"]},{"url":"https://nvd.nist.gov/vuln/detail/CVE-2022-41883","tags":["web","advisory"]},{"url":"https://github.com/advisories/GHSA-w58w-79xv-6vcj","tags":["advisory"]},{"url":"https://github.com/CVEProject/cvelistV5/tree/main/cves/2022/41xxx/CVE-2022-41883.json","tags":["advisory"]},{"url":"https://github.com/tensorflow/tensorflow","tags":["package"]},{"url":"https://pypi.org/project/tensorflow-gpu","tags":["package"]},{"url":"https://pypi.org/project/tensorflow","tags":["package"]},{"url":"https://pypi.org/project/tensorflow-cpu","tags":["package"]}],"sources":{"cve":[{"id":"CVE-2022-41883","title":"Out of bounds segmentation fault due to unequal op inputs in Tensorflow","description":"TensorFlow is an open source platform for machine learning. When ops that have specified input sizes receive a differing number of inputs, the executor will crash. We have patched the issue in GitHub commit f5381e0e10b5a61344109c1b7c174c68110f7629. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.","status":"published","published":"2022-11-18T00:00:00Z","modified":"2025-04-22T16:07:05.864Z","cvss":[{"version":"3.1","score":6.8,"vector":"CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:L/I:L/A:H","level":"medium","assessor":"cna"}],"cwes":["CWE-125"],"updated_at":"2026-11-02T14:34:28.038197Z"}],"euvd":[{"id":"EUVD-2022-7448","description":"TensorFlow is an open source platform for machine learning. When ops that have specified input sizes receive a differing number of inputs, the executor will crash. We have patched the issue in GitHub commit f5381e0e10b5a61344109c1b7c174c68110f7629. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.","status":"published","published":"2022-11-18T00:00:00Z","modified":"2025-04-22T16:07:05Z","cvss":[{"version":"3.1","score":6.8,"vector":"CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:L/I:L/A:H","level":"medium"}],"updated_at":"2026-11-02T20:52:16.784071Z"}],"ghsa":[{"id":"GHSA-w58w-79xv-6vcj","title":"Out of bounds segmentation fault due to unequal op inputs in Tensorflow","description":"### Impact\n [`tf.raw_ops.DynamicStitch`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/dynamic_stitch_op.cc) specifies input sizes when it is [registered](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ops/data_flow_ops.cc). \n```cpp\nREGISTER_OP(\"DynamicStitch\")\n    .Input(\"indices: N * int32\")\n    .Input(\"data: N * T\")\n    .Output(\"merged: T\")\n    .Attr(\"N : int \u003e= 1\")\n    .Attr(\"T : type\")\n    .SetShapeFn(DynamicStitchShapeFunction);\n```\nWhen it receives a differing number of inputs, such as when it is called with an `indices` size 1 and a `data` size 2, it will crash.\n```python\nimport tensorflow as tf\n\n# indices = 1*[tf.random.uniform([1,2], dtype=tf.dtypes.int32, maxval=100)]\nindices = [tf.constant([[0, 1]]),]\n\n# data = 2*[tf.random.uniform([1,2], dtype=tf.dtypes.float32, maxval=100)]\ndata = [tf.constant([[5, 6]]), tf.constant([[7, 8]])]\n\ntf.raw_ops.DynamicStitch(\n    indices=indices, \n    data=data)\n```\n\n### Patches\nWe have patched the issue in GitHub commit [f5381e0e10b5a61344109c1b7c174c68110f7629](https://github.com/tensorflow/tensorflow/commit/f5381e0e10b5a61344109c1b7c174c68110f7629).\n\nThe fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1 as this is also affected.\n\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\n### Attribution\nThis vulnerability has been reported by Zizhuang Deng of IIE, UCAS\n","status":"published","published":"2022-11-21T20:39:20Z","modified":"2023-02-01T05:03:59Z","cvss":[{"version":"3.1","score":6.8,"vector":"CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:L/I:L/A:H","level":"medium"}],"cwes":["CWE-125"],"updated_at":"2026-11-02T14:36:32.120868Z"}],"nvd":[{"id":"CVE-2022-41883","description":"TensorFlow is an open source platform for machine learning. When ops that have specified input sizes receive a differing number of inputs, the executor will crash. We have patched the issue in GitHub commit f5381e0e10b5a61344109c1b7c174c68110f7629. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.","status":"published","published":"2022-11-18T21:15:10.923Z","modified":"2026-06-17T05:03:59.447Z","cvss":[{"version":"3.1","score":6.8,"vector":"CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:L/I:L/A:H","level":"medium","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"}],"cwes":["CWE-125"],"updated_at":"2026-11-02T14:07:32.395456Z"}],"osv":[{"id":"CVE-2022-41883","title":"Out of bounds segmentation fault due to unequal op inputs in Tensorflow","description":"TensorFlow is an open source platform for machine learning. When ops that have specified input sizes receive a differing number of inputs, the executor will crash. We have patched the issue in GitHub commit f5381e0e10b5a61344109c1b7c174c68110f7629. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.","status":"published","published":"2022-11-18T00:00:00Z","modified":"2026-10-28T10:28:28.768527936Z","cvss":[{"version":"3.1","score":6.8,"vector":"CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:L/I:L/A:H","level":"medium"}],"cwes":["CWE-125"],"updated_at":"2026-11-02T15:44:27.186787Z"},{"id":"GHSA-w58w-79xv-6vcj","title":"Out of bounds segmentation fault due to unequal op inputs in Tensorflow","description":"### Impact\n [`tf.raw_ops.DynamicStitch`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/dynamic_stitch_op.cc) specifies input sizes when it is [registered](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ops/data_flow_ops.cc). \n```cpp\nREGISTER_OP(\"DynamicStitch\")\n    .Input(\"indices: N * int32\")\n    .Input(\"data: N * T\")\n    .Output(\"merged: T\")\n    .Attr(\"N : int \u003e= 1\")\n    .Attr(\"T : type\")\n    .SetShapeFn(DynamicStitchShapeFunction);\n```\nWhen it receives a differing number of inputs, such as when it is called with an `indices` size 1 and a `data` size 2, it will crash.\n```python\nimport tensorflow as tf\n\n# indices = 1*[tf.random.uniform([1,2], dtype=tf.dtypes.int32, maxval=100)]\nindices = [tf.constant([[0, 1]]),]\n\n# data = 2*[tf.random.uniform([1,2], dtype=tf.dtypes.float32, maxval=100)]\ndata = [tf.constant([[5, 6]]), tf.constant([[7, 8]])]\n\ntf.raw_ops.DynamicStitch(\n    indices=indices, \n    data=data)\n```\n\n### Patches\nWe have patched the issue in GitHub commit [f5381e0e10b5a61344109c1b7c174c68110f7629](https://github.com/tensorflow/tensorflow/commit/f5381e0e10b5a61344109c1b7c174c68110f7629).\n\nThe fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1 as this is also affected.\n\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\n### Attribution\nThis vulnerability has been reported by Zizhuang Deng of IIE, UCAS\n","status":"published","published":"2022-11-21T20:39:20Z","modified":"2026-07-13T16:42:49.026599256Z","cvss":[{"version":"3.1","score":6.8,"vector":"CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:L/I:L/A:H","level":"medium"}],"cwes":["CWE-125"],"updated_at":"2026-11-02T15:46:58.04805Z"},{"id":"PYSEC-2026-1042","title":"Out of bounds segmentation fault due to unequal op inputs in Tensorflow","description":"### Impact\n [`tf.raw_ops.DynamicStitch`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/dynamic_stitch_op.cc) specifies input sizes when it is [registered](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ops/data_flow_ops.cc). \n```cpp\nREGISTER_OP(\"DynamicStitch\")\n    .Input(\"indices: N * int32\")\n    .Input(\"data: N * T\")\n    .Output(\"merged: T\")\n    .Attr(\"N : int \u003e= 1\")\n    .Attr(\"T : type\")\n    .SetShapeFn(DynamicStitchShapeFunction);\n```\nWhen it receives a differing number of inputs, such as when it is called with an `indices` size 1 and a `data` size 2, it will crash.\n```python\nimport tensorflow as tf\n\n# indices = 1*[tf.random.uniform([1,2], dtype=tf.dtypes.int32, maxval=100)]\nindices = [tf.constant([[0, 1]]),]\n\n# data = 2*[tf.random.uniform([1,2], dtype=tf.dtypes.float32, maxval=100)]\ndata = [tf.constant([[5, 6]]), tf.constant([[7, 8]])]\n\ntf.raw_ops.DynamicStitch(\n    indices=indices, \n    data=data)\n```\n\n### Patches\nWe have patched the issue in GitHub commit [f5381e0e10b5a61344109c1b7c174c68110f7629](https://github.com/tensorflow/tensorflow/commit/f5381e0e10b5a61344109c1b7c174c68110f7629).\n\nThe fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1 as this is also affected.\n\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\n### Attribution\nThis vulnerability has been reported by Zizhuang Deng of IIE, UCAS\n","status":"published","published":"2026-07-07T10:17:23.489934Z","modified":"2026-07-13T16:42:49.026599256Z","cvss":[{"version":"3.1","score":6.8,"vector":"CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:L/I:L/A:H","level":"medium"}],"updated_at":"2026-11-02T15:52:54.622769Z"},{"id":"PYSEC-2026-3251","title":"Out of bounds segmentation fault due to unequal op inputs in Tensorflow","description":"### Impact\n [`tf.raw_ops.DynamicStitch`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/dynamic_stitch_op.cc) specifies input sizes when it is [registered](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ops/data_flow_ops.cc). \n```cpp\nREGISTER_OP(\"DynamicStitch\")\n    .Input(\"indices: N * int32\")\n    .Input(\"data: N * T\")\n    .Output(\"merged: T\")\n    .Attr(\"N : int \u003e= 1\")\n    .Attr(\"T : type\")\n    .SetShapeFn(DynamicStitchShapeFunction);\n```\nWhen it receives a differing number of inputs, such as when it is called with an `indices` size 1 and a `data` size 2, it will crash.\n```python\nimport tensorflow as tf\n\n# indices = 1*[tf.random.uniform([1,2], dtype=tf.dtypes.int32, maxval=100)]\nindices = [tf.constant([[0, 1]]),]\n\n# data = 2*[tf.random.uniform([1,2], dtype=tf.dtypes.float32, maxval=100)]\ndata = [tf.constant([[5, 6]]), tf.constant([[7, 8]])]\n\ntf.raw_ops.DynamicStitch(\n    indices=indices, \n    data=data)\n```\n\n### Patches\nWe have patched the issue in GitHub commit [f5381e0e10b5a61344109c1b7c174c68110f7629](https://github.com/tensorflow/tensorflow/commit/f5381e0e10b5a61344109c1b7c174c68110f7629).\n\nThe fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1 as this is also affected.\n\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\n### Attribution\nThis vulnerability has been reported by Zizhuang Deng of IIE, UCAS\n","status":"published","published":"2026-07-13T14:19:51.352532Z","modified":"2026-07-13T16:42:49.026599256Z","cvss":[{"version":"3.1","score":6.8,"vector":"CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:L/I:L/A:H","level":"medium"}],"updated_at":"2026-11-02T15:52:56.429374Z"},{"id":"PYSEC-2026-3376","title":"Out of bounds segmentation fault due to unequal op inputs in Tensorflow","description":"### Impact\n [`tf.raw_ops.DynamicStitch`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/dynamic_stitch_op.cc) specifies input sizes when it is [registered](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ops/data_flow_ops.cc). \n```cpp\nREGISTER_OP(\"DynamicStitch\")\n    .Input(\"indices: N * int32\")\n    .Input(\"data: N * T\")\n    .Output(\"merged: T\")\n    .Attr(\"N : int \u003e= 1\")\n    .Attr(\"T : type\")\n    .SetShapeFn(DynamicStitchShapeFunction);\n```\nWhen it receives a differing number of inputs, such as when it is called with an `indices` size 1 and a `data` size 2, it will crash.\n```python\nimport tensorflow as tf\n\n# indices = 1*[tf.random.uniform([1,2], dtype=tf.dtypes.int32, maxval=100)]\nindices = [tf.constant([[0, 1]]),]\n\n# data = 2*[tf.random.uniform([1,2], dtype=tf.dtypes.float32, maxval=100)]\ndata = [tf.constant([[5, 6]]), tf.constant([[7, 8]])]\n\ntf.raw_ops.DynamicStitch(\n    indices=indices, \n    data=data)\n```\n\n### Patches\nWe have patched the issue in GitHub commit [f5381e0e10b5a61344109c1b7c174c68110f7629](https://github.com/tensorflow/tensorflow/commit/f5381e0e10b5a61344109c1b7c174c68110f7629).\n\nThe fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1 as this is also affected.\n\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\n### Attribution\nThis vulnerability has been reported by Zizhuang Deng of IIE, UCAS\n","status":"published","published":"2026-07-13T14:19:51.457784Z","modified":"2026-07-13T16:42:49.026599256Z","cvss":[{"version":"3.1","score":6.8,"vector":"CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:L/I:L/A:H","level":"medium"}],"updated_at":"2026-11-02T15:52:56.847083Z"},{"id":"BIT-tensorflow-2022-41883","title":"Out of bounds segmentation fault due to unequal op inputs in Tensorflow","description":"TensorFlow is an open source platform for machine learning. When ops that have specified input sizes receive a differing number of inputs, the executor will crash. We have patched the issue in GitHub commit f5381e0e10b5a61344109c1b7c174c68110f7629. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.","status":"published","published":"2024-03-06T11:11:35.699Z","modified":"2026-09-08T08:48:20.615315559Z","updated_at":"2026-11-02T15:28:35.51001Z"}]}}