{"id":"CVE-2022-29203","aliases":["BIT-tensorflow-2022-29203","EUVD-2022-4388","GHSA-jjm6-4vf7-cjh4","PYSEC-2026-1012","PYSEC-2026-3207","PYSEC-2026-3344"],"status":"published","title":"Integer overflow in `SpaceToBatchND` 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, the implementation of `tf.raw_ops.SpaceToBatchND` (in all backends such as XLA and handwritten kernels) is vulnerable to an integer overflow: The result of this integer overflow is used to allocate the output tensor, hence we get a denial of service via a `CHECK`-failure (assertion failure), as in TFSA-2021-198. 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":"2026-11-10","score":0.00341,"percentile":0.2782,"model":"v2026.06.15"},"facts":{"in_kev":false,"known_exploited":false,"public_exploit":false,"fix_available":true},"cwes":["CWE-190"],"published":"2022-05-20T22:50:11Z","modified":"2026-10-28T10:28:11Z","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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Party Advisory","advisory","web"]},{"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-jjm6-4vf7-cjh4","tags":["x_refsource_CONFIRM","x_transferred","Exploit","Patch","Third Party Advisory","advisory","web"]},{"url":"https://github.com/tensorflow/tensorflow/commit/acd56b8bcb72b163c834ae4f18469047b001fadf","tags":["x_refsource_MISC","x_transferred","Patch","Third Party Advisory","advisory","fix","web"]},{"url":"https://nvd.nist.gov/vuln/detail/CVE-2022-29203","tags":["web","advisory"]},{"url":"https://github.com/advisories/GHSA-jjm6-4vf7-cjh4","tags":["advisory"]},{"url":"https://github.com/CVEProject/cvelistV5/tree/main/cves/2022/29xxx/CVE-2022-29203.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-2022-29203","title":"Integer overflow in `SpaceToBatchND` 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, the implementation of `tf.raw_ops.SpaceToBatchND` (in all backends such as XLA and handwritten kernels) is vulnerable to an integer overflow: The result of this integer overflow is used to allocate the output tensor, hence we get a denial of service via a `CHECK`-failure (assertion failure), as in TFSA-2021-198. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.","status":"published","published":"2022-05-20T22:50:11Z","modified":"2025-04-22T17:58:03.254Z","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-190"],"updated_at":"2026-11-02T14:34:36.270817Z"}],"euvd":[{"id":"EUVD-2022-4388","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, the implementation of `tf.raw_ops.SpaceToBatchND` (in all backends such as XLA and handwritten kernels) is vulnerable to an integer overflow: The result of this integer overflow is used to allocate the output tensor, hence we get a denial of service via a `CHECK`-failure (assertion failure), as in TFSA-2021-198. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.","status":"published","published":"2022-05-20T22:50:11Z","modified":"2025-04-22T17:58:03Z","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-jjm6-4vf7-cjh4","title":"Integer overflow in `SpaceToBatchND`","description":"### Impact\nThe implementation of `tf.raw_ops.SpaceToBatchND` (in all backends such as XLA and handwritten kernels) is vulnerable to an integer overflow:\n\n```python\nimport tensorflow as tf\n\ninput = tf.constant(-3.5e+35, shape=[10,19,22], dtype=tf.float32)\nblock_shape = tf.constant(-1879048192, shape=[2], dtype=tf.int64)\npaddings = tf.constant(0, shape=[2,2], dtype=tf.int32)\ntf.raw_ops.SpaceToBatchND(input=input, block_shape=block_shape, paddings=paddings)\n```\n\nThe result of this integer overflow is used to allocate the output tensor, hence we get a denial of service via a `CHECK`-failure (assertion failure), as in [TFSA-2021-198](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md).\n\n### Patches\nWe have patched the issue in GitHub commit [acd56b8bcb72b163c834ae4f18469047b001fadf](https://github.com/tensorflow/tensorflow/commit/acd56b8bcb72b163c834ae4f18469047b001fadf).\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 Neophytos Christou from Secure Systems Lab at Brown University.\n","status":"published","published":"2022-05-24T22:11:56Z","modified":"2023-01-27T05:02:06Z","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-190"],"updated_at":"2026-11-02T14:36:17.04874Z"}],"nvd":[{"id":"CVE-2022-29203","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, the implementation of `tf.raw_ops.SpaceToBatchND` (in all backends such as XLA and handwritten kernels) is vulnerable to an integer overflow: The result of this integer overflow is used to allocate the output tensor, hence we get a denial of service via a `CHECK`-failure (assertion failure), as in TFSA-2021-198. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.","status":"published","published":"2022-05-20T23:15:44.543Z","modified":"2026-06-17T04:39:48.787Z","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-190"],"updated_at":"2026-11-02T14:07:21.261605Z"}],"osv":[{"id":"CVE-2022-29203","title":"Integer overflow in `SpaceToBatchND` 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, the implementation of `tf.raw_ops.SpaceToBatchND` (in all backends such as XLA and handwritten kernels) is vulnerable to an integer overflow: The result of this integer overflow is used to allocate the output tensor, hence we get a denial of service via a `CHECK`-failure (assertion failure), as in TFSA-2021-198. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.","status":"published","published":"2022-05-20T22:50:11Z","modified":"2026-10-28T10:28:11.342183426Z","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-190"],"updated_at":"2026-11-02T15:44:25.164673Z"},{"id":"GHSA-jjm6-4vf7-cjh4","title":"Integer overflow in `SpaceToBatchND`","description":"### Impact\nThe implementation of `tf.raw_ops.SpaceToBatchND` (in all backends such as XLA and handwritten kernels) is vulnerable to an integer overflow:\n\n```python\nimport tensorflow as tf\n\ninput = tf.constant(-3.5e+35, shape=[10,19,22], dtype=tf.float32)\nblock_shape = tf.constant(-1879048192, shape=[2], dtype=tf.int64)\npaddings = tf.constant(0, shape=[2,2], dtype=tf.int32)\ntf.raw_ops.SpaceToBatchND(input=input, block_shape=block_shape, paddings=paddings)\n```\n\nThe result of this integer overflow is used to allocate the output tensor, hence we get a denial of service via a `CHECK`-failure (assertion failure), as in [TFSA-2021-198](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md).\n\n### Patches\nWe have patched the issue in GitHub commit [acd56b8bcb72b163c834ae4f18469047b001fadf](https://github.com/tensorflow/tensorflow/commit/acd56b8bcb72b163c834ae4f18469047b001fadf).\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 Neophytos Christou from Secure Systems Lab at Brown University.\n","status":"published","published":"2022-05-24T22:11:56Z","modified":"2026-07-13T16:43:39.306303684Z","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-190"],"updated_at":"2026-11-02T15:46:50.687609Z"},{"id":"PYSEC-2026-1012","title":"Integer overflow in `SpaceToBatchND`","description":"### Impact\nThe implementation of `tf.raw_ops.SpaceToBatchND` (in all backends such as XLA and handwritten kernels) is vulnerable to an integer overflow:\n\n```python\nimport tensorflow as tf\n\ninput = tf.constant(-3.5e+35, shape=[10,19,22], dtype=tf.float32)\nblock_shape = tf.constant(-1879048192, shape=[2], dtype=tf.int64)\npaddings = tf.constant(0, shape=[2,2], dtype=tf.int32)\ntf.raw_ops.SpaceToBatchND(input=input, block_shape=block_shape, paddings=paddings)\n```\n\nThe result of this integer overflow is used to allocate the output tensor, hence we get a denial of service via a `CHECK`-failure (assertion failure), as in [TFSA-2021-198](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md).\n\n### Patches\nWe have patched the issue in GitHub commit [acd56b8bcb72b163c834ae4f18469047b001fadf](https://github.com/tensorflow/tensorflow/commit/acd56b8bcb72b163c834ae4f18469047b001fadf).\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 Neophytos Christou from Secure Systems Lab at Brown University.\n","status":"published","published":"2026-07-06T08:03:29.714798Z","modified":"2026-07-13T16:43:39.306303684Z","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":"2026-11-02T15:52:54.622769Z"},{"id":"PYSEC-2026-3207","title":"Integer overflow in `SpaceToBatchND`","description":"### Impact\nThe implementation of `tf.raw_ops.SpaceToBatchND` (in all backends such as XLA and handwritten kernels) is vulnerable to an integer overflow:\n\n```python\nimport tensorflow as tf\n\ninput = tf.constant(-3.5e+35, shape=[10,19,22], dtype=tf.float32)\nblock_shape = tf.constant(-1879048192, shape=[2], dtype=tf.int64)\npaddings = tf.constant(0, shape=[2,2], dtype=tf.int32)\ntf.raw_ops.SpaceToBatchND(input=input, block_shape=block_shape, paddings=paddings)\n```\n\nThe result of this integer overflow is used to allocate the output tensor, hence we get a denial of service via a `CHECK`-failure (assertion failure), as in [TFSA-2021-198](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md).\n\n### Patches\nWe have patched the issue in GitHub commit [acd56b8bcb72b163c834ae4f18469047b001fadf](https://github.com/tensorflow/tensorflow/commit/acd56b8bcb72b163c834ae4f18469047b001fadf).\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 Neophytos Christou from Secure Systems Lab at Brown University.\n","status":"published","published":"2026-07-09T16:49:49.393877Z","modified":"2026-07-13T16:43:39.306303684Z","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-2026-3344","title":"Integer overflow in `SpaceToBatchND`","description":"### Impact\nThe implementation of `tf.raw_ops.SpaceToBatchND` (in all backends such as XLA and handwritten kernels) is vulnerable to an integer overflow:\n\n```python\nimport tensorflow as tf\n\ninput = tf.constant(-3.5e+35, shape=[10,19,22], dtype=tf.float32)\nblock_shape = tf.constant(-1879048192, shape=[2], dtype=tf.int64)\npaddings = tf.constant(0, shape=[2,2], dtype=tf.int32)\ntf.raw_ops.SpaceToBatchND(input=input, block_shape=block_shape, paddings=paddings)\n```\n\nThe result of this integer overflow is used to allocate the output tensor, hence we get a denial of service via a `CHECK`-failure (assertion failure), as in [TFSA-2021-198](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md).\n\n### Patches\nWe have patched the issue in GitHub commit [acd56b8bcb72b163c834ae4f18469047b001fadf](https://github.com/tensorflow/tensorflow/commit/acd56b8bcb72b163c834ae4f18469047b001fadf).\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 Neophytos Christou from Secure Systems Lab at Brown University.\n","status":"published","published":"2026-07-09T16:49:49.477614Z","modified":"2026-07-13T16:43:39.306303684Z","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":"BIT-tensorflow-2022-29203","title":"Integer overflow in `SpaceToBatchND` 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, the implementation of `tf.raw_ops.SpaceToBatchND` (in all backends such as XLA and handwritten kernels) is vulnerable to an integer overflow: The result of this integer overflow is used to allocate the output tensor, hence we get a denial of service via a `CHECK`-failure (assertion failure), as in TFSA-2021-198. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.","status":"published","published":"2024-03-06T11:14:26.405Z","modified":"2026-09-08T08:48:20.195067722Z","updated_at":"2026-11-02T15:28:35.51001Z"}]}}