{"id":"CVE-2022-35940","aliases":["BIT-tensorflow-2022-35940","EUVD-2022-6976","GHSA-x989-q2pq-4q5x","PYSEC-2026-1047","PYSEC-2026-3259","PYSEC-2026-3381","openSUSE-SU-2024:12355-1"],"status":"published","title":"Int overflow in `RaggedRangeOp` in Tensoflow","description":"TensorFlow is an open source platform for machine learning. The `RaggedRangOp` function takes an argument `limits` that is eventually used to construct a `TensorShape` as an `int64`. If `limits` is a very large float, it can overflow when converted to an `int64`. This triggers an `InvalidArgument` but also throws an abort signal that crashes the program. We have patched the issue in GitHub commit 37cefa91bee4eace55715eeef43720b958a01192. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.","severity":{"version":"3.1","score":5.9,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"medium","assessor":"cna","from":"cve"},"epss":{"day":"2026-11-09","score":0.00701,"percentile":0.53491,"model":"v2026.06.15"},"facts":{"in_kev":false,"known_exploited":false,"public_exploit":false,"fix_available":true},"cwes":["CWE-190"],"published":"2022-09-16T19:45:20Z","modified":"2026-10-28T10:27:05Z","fixes":[{"ecosystem":"PyPI","package":"tensorflow","fixed_in":["2.7.2","2.8.1","2.9.1"],"sources":["ghsa","osv"]},{"ecosystem":"PyPI","package":"tensorflow-cpu","fixed_in":["2.7.2","2.8.1","2.9.1"],"sources":["ghsa","osv"]},{"ecosystem":"PyPI","package":"tensorflow-gpu","fixed_in":["2.7.2","2.8.1","2.9.1"],"sources":["ghsa","osv"]},{"ecosystem":"Bitnami","package":"tensorflow","fixed_in":["2.7.2","2.8.1","2.9.1"],"sources":["osv"]}],"affected":[{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"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","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.9.0"},{"fixed":"2.9.1"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"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-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.9.0"},{"fixed":"2.9.1"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"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":"ghsa","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.9.0"},{"fixed":"2.9.1"}]}]},{"source":"osv","ecosystem":"Bitnami","package":"tensorflow","ranges":[{"type":"SEMVER","events":[{"introduced":"2.7.0"},{"fixed":"2.7.2"},{"introduced":"2.8.0"},{"fixed":"2.8.1"},{"introduced":"2.9.0"},{"fixed":"2.9.1"}]}]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.7.2"}]}],"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","2.6.4","2.6.5","2.7.0","2.7.0rc0","2.7.0rc1","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","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.9.0"},{"fixed":"2.9.1"}]}],"versions":["2.9.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.7.2"}]}],"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","2.6.4","2.6.5","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-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.9.0"},{"fixed":"2.9.1"}]}],"versions":["2.9.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.7.2"}]}],"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","2.6.4","2.6.5","2.7.0","2.7.0rc0","2.7.0rc1","2.7.1"]},{"source":"osv","ecosystem":"Py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Party Advisory","advisory","web"]},{"url":"https://github.com/tensorflow/tensorflow/commit/37cefa91bee4eace55715eeef43720b958a01192","tags":["x_refsource_MISC","x_transferred","Patch","Third Party Advisory","advisory","fix","web"]},{"url":"https://github.com/tensorflow/tensorflow/blob/0b6b491d21d6a4eb5fbab1cca565bc1e94ca9543/tensorflow/core/kernels/ragged_range_op.cc#L74-L88","tags":["x_refsource_MISC","x_transferred","Third Party Advisory","advisory","web"]},{"url":"https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0","tags":["web"]},{"url":"https://nvd.nist.gov/vuln/detail/CVE-2022-35940","tags":["web","advisory"]},{"url":"https://github.com/advisories/GHSA-x989-q2pq-4q5x","tags":["advisory"]},{"url":"https://github.com/CVEProject/cvelistV5/tree/main/cves/2022/35xxx/CVE-2022-35940.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"]},{"url":"","tags":["advisory"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35934","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35935","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35937","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35938","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35939","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35940","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35941","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35952","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35959","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35960","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35963","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35964","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35965","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35966","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35967","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35968","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35969","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35970","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35971","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35972","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35973","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35974","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35979","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35981","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35982","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35983","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35984","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35985","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35986","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35987","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35988","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35989","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35990","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35991","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35992","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35993","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35994","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35995","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35996","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35997","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35998","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-35999","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36000","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36001","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36002","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36003","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36004","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36005","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36011","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36012","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36013","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36014","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36015","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36016","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36017","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36018","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36019","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36026","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-36027","tags":["web"]}],"sources":{"cve":[{"id":"CVE-2022-35940","title":"Int overflow in `RaggedRangeOp` in Tensoflow","description":"TensorFlow is an open source platform for machine learning. The `RaggedRangOp` function takes an argument `limits` that is eventually used to construct a `TensorShape` as an `int64`. If `limits` is a very large float, it can overflow when converted to an `int64`. This triggers an `InvalidArgument` but also throws an abort signal that crashes the program. We have patched the issue in GitHub commit 37cefa91bee4eace55715eeef43720b958a01192. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.","status":"published","published":"2022-09-16T19:45:20Z","modified":"2025-04-23T17:04:04.792Z","cvss":[{"version":"3.1","score":5.9,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"medium","assessor":"cna"}],"cwes":["CWE-190"],"updated_at":"2026-11-02T14:34:39.935681Z"}],"euvd":[{"id":"EUVD-2022-6976","description":"TensorFlow is an open source platform for machine learning. The `RaggedRangOp` function takes an argument `limits` that is eventually used to construct a `TensorShape` as an `int64`. If `limits` is a very large float, it can overflow when converted to an `int64`. This triggers an `InvalidArgument` but also throws an abort signal that crashes the program. We have patched the issue in GitHub commit 37cefa91bee4eace55715eeef43720b958a01192. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.","status":"published","published":"2022-09-16T19:45:20Z","modified":"2025-04-23T17:04:04Z","cvss":[{"version":"3.1","score":5.9,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"medium"}],"updated_at":"2026-11-02T20:52:10.906327Z"}],"ghsa":[{"id":"GHSA-x989-q2pq-4q5x","title":"TensorFlow vulnerable to Int overflow in `RaggedRangeOp`","description":"### Impact\nThe [`RaggedRangOp`](https://github.com/tensorflow/tensorflow/blob/0b6b491d21d6a4eb5fbab1cca565bc1e94ca9543/tensorflow/core/kernels/ragged_range_op.cc#L74-L88) function takes an argument `limits` that is eventually used to construct a `TensorShape` as an `int64`. If `limits` is a very large float, it can overflow when converted to an `int64`. This triggers an `InvalidArgument` but also throws an abort signal that crashes the program.\n```python\nimport tensorflow as tf\ntf.raw_ops.RaggedRange(starts=[1.1,0.1],limits=[10.0,1e20],deltas=[1,1])\n```\n\n### Patches\nWe have patched the issue in GitHub commit [37cefa91bee4eace55715eeef43720b958a01192](https://github.com/tensorflow/tensorflow/commit/37cefa91bee4eace55715eeef43720b958a01192).\n\nThe fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.\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 Jingyi Shi.","status":"published","published":"2022-09-16T22:12:41Z","modified":"2023-01-28T05:03:11Z","cvss":[{"version":"3.1","score":5.9,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"medium"}],"cwes":["CWE-190"],"updated_at":"2026-11-02T14:36:24.277749Z"}],"nvd":[{"id":"CVE-2022-35940","description":"TensorFlow is an open source platform for machine learning. The `RaggedRangOp` function takes an argument `limits` that is eventually used to construct a `TensorShape` as an `int64`. If `limits` is a very large float, it can overflow when converted to an `int64`. This triggers an `InvalidArgument` but also throws an abort signal that crashes the program. We have patched the issue in GitHub commit 37cefa91bee4eace55715eeef43720b958a01192. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.","status":"published","published":"2022-09-16T20:15:10.307Z","modified":"2026-06-17T04:52:34.047Z","cvss":[{"version":"3.1","score":5.9,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/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-190"],"updated_at":"2026-11-02T14:07:28.118799Z"}],"osv":[{"id":"CVE-2022-35940","title":"Int overflow in `RaggedRangeOp` in Tensoflow","description":"TensorFlow is an open source platform for machine learning. The `RaggedRangOp` function takes an argument `limits` that is eventually used to construct a `TensorShape` as an `int64`. If `limits` is a very large float, it can overflow when converted to an `int64`. This triggers an `InvalidArgument` but also throws an abort signal that crashes the program. We have patched the issue in GitHub commit 37cefa91bee4eace55715eeef43720b958a01192. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.","status":"published","published":"2022-09-16T19:45:20Z","modified":"2026-10-28T10:27:05.471531726Z","cvss":[{"version":"3.1","score":5.9,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"medium"}],"cwes":["CWE-190"],"updated_at":"2026-11-02T15:44:26.195407Z"},{"id":"GHSA-x989-q2pq-4q5x","title":"TensorFlow vulnerable to Int overflow in `RaggedRangeOp`","description":"### Impact\nThe [`RaggedRangOp`](https://github.com/tensorflow/tensorflow/blob/0b6b491d21d6a4eb5fbab1cca565bc1e94ca9543/tensorflow/core/kernels/ragged_range_op.cc#L74-L88) function takes an argument `limits` that is eventually used to construct a `TensorShape` as an `int64`. If `limits` is a very large float, it can overflow when converted to an `int64`. This triggers an `InvalidArgument` but also throws an abort signal that crashes the program.\n```python\nimport tensorflow as tf\ntf.raw_ops.RaggedRange(starts=[1.1,0.1],limits=[10.0,1e20],deltas=[1,1])\n```\n\n### Patches\nWe have patched the issue in GitHub commit [37cefa91bee4eace55715eeef43720b958a01192](https://github.com/tensorflow/tensorflow/commit/37cefa91bee4eace55715eeef43720b958a01192).\n\nThe fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.\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 Jingyi Shi.","status":"published","published":"2022-09-16T22:12:41Z","modified":"2026-07-13T16:43:21.603978969Z","cvss":[{"version":"3.1","score":5.9,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"medium"}],"cwes":["CWE-190"],"updated_at":"2026-11-02T15:46:59.835583Z"},{"id":"PYSEC-2026-1047","title":"TensorFlow vulnerable to Int overflow in `RaggedRangeOp`","description":"### Impact\nThe [`RaggedRangOp`](https://github.com/tensorflow/tensorflow/blob/0b6b491d21d6a4eb5fbab1cca565bc1e94ca9543/tensorflow/core/kernels/ragged_range_op.cc#L74-L88) function takes an argument `limits` that is eventually used to construct a `TensorShape` as an `int64`. If `limits` is a very large float, it can overflow when converted to an `int64`. This triggers an `InvalidArgument` but also throws an abort signal that crashes the program.\n```python\nimport tensorflow as tf\ntf.raw_ops.RaggedRange(starts=[1.1,0.1],limits=[10.0,1e20],deltas=[1,1])\n```\n\n### Patches\nWe have patched the issue in GitHub commit [37cefa91bee4eace55715eeef43720b958a01192](https://github.com/tensorflow/tensorflow/commit/37cefa91bee4eace55715eeef43720b958a01192).\n\nThe fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.\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 Jingyi Shi.","status":"published","published":"2026-07-07T10:17:20.354916Z","modified":"2026-07-13T16:43:21.603978969Z","cvss":[{"version":"3.1","score":5.9,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"medium"}],"updated_at":"2026-11-02T15:52:54.622769Z"},{"id":"PYSEC-2026-3259","title":"TensorFlow vulnerable to Int overflow in `RaggedRangeOp`","description":"### Impact\nThe [`RaggedRangOp`](https://github.com/tensorflow/tensorflow/blob/0b6b491d21d6a4eb5fbab1cca565bc1e94ca9543/tensorflow/core/kernels/ragged_range_op.cc#L74-L88) function takes an argument `limits` that is eventually used to construct a `TensorShape` as an `int64`. If `limits` is a very large float, it can overflow when converted to an `int64`. This triggers an `InvalidArgument` but also throws an abort signal that crashes the program.\n```python\nimport tensorflow as tf\ntf.raw_ops.RaggedRange(starts=[1.1,0.1],limits=[10.0,1e20],deltas=[1,1])\n```\n\n### Patches\nWe have patched the issue in GitHub commit [37cefa91bee4eace55715eeef43720b958a01192](https://github.com/tensorflow/tensorflow/commit/37cefa91bee4eace55715eeef43720b958a01192).\n\nThe fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.\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 Jingyi Shi.","status":"published","published":"2026-07-13T14:19:45.406256Z","modified":"2026-07-13T16:43:21.603978969Z","cvss":[{"version":"3.1","score":5.9,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"medium"}],"updated_at":"2026-11-02T15:52:56.847083Z"},{"id":"PYSEC-2026-3381","title":"TensorFlow vulnerable to Int overflow in `RaggedRangeOp`","description":"### Impact\nThe [`RaggedRangOp`](https://github.com/tensorflow/tensorflow/blob/0b6b491d21d6a4eb5fbab1cca565bc1e94ca9543/tensorflow/core/kernels/ragged_range_op.cc#L74-L88) function takes an argument `limits` that is eventually used to construct a `TensorShape` as an `int64`. If `limits` is a very large float, it can overflow when converted to an `int64`. This triggers an `InvalidArgument` but also throws an abort signal that crashes the program.\n```python\nimport tensorflow as tf\ntf.raw_ops.RaggedRange(starts=[1.1,0.1],limits=[10.0,1e20],deltas=[1,1])\n```\n\n### Patches\nWe have patched the issue in GitHub commit [37cefa91bee4eace55715eeef43720b958a01192](https://github.com/tensorflow/tensorflow/commit/37cefa91bee4eace55715eeef43720b958a01192).\n\nThe fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.\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 Jingyi Shi.","status":"published","published":"2026-07-13T14:19:45.507685Z","modified":"2026-07-13T16:43:21.603978969Z","cvss":[{"version":"3.1","score":5.9,"vector":"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H","level":"medium"}],"updated_at":"2026-11-02T15:52:56.847083Z"},{"id":"BIT-tensorflow-2022-35940","title":"Int overflow in `RaggedRangeOp` in Tensoflow","description":"TensorFlow is an open source platform for machine learning. The `RaggedRangOp` function takes an argument `limits` that is eventually used to construct a `TensorShape` as an `int64`. If `limits` is a very large float, it can overflow when converted to an `int64`. This triggers an `InvalidArgument` but also throws an abort signal that crashes the program. We have patched the issue in GitHub commit 37cefa91bee4eace55715eeef43720b958a01192. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.","status":"published","published":"2024-03-06T11:14:05.071Z","modified":"2026-09-08T08:48:20.452024261Z","updated_at":"2026-11-02T15:28:35.51001Z"},{"id":"openSUSE-SU-2024:12355-1","title":"tensorflow-lite-2.10.0-1.1 on GA media","description":"These are all security issues fixed in the tensorflow-lite-2.10.0-1.1 package on the GA media of openSUSE Tumbleweed.","status":"published","published":"2024-06-15T00:00:00Z","modified":"2026-02-04T02:37:03.870689Z","updated_at":"2026-11-02T16:58:35.751245Z"}]}}