{"id":"CVE-2022-36015","aliases":["BIT-tensorflow-2022-36015","EUVD-2022-6936","GHSA-rh87-q4vg-m45j","PYSEC-2026-1033","PYSEC-2026-3237","PYSEC-2026-3367","openSUSE-SU-2024:12355-1"],"status":"published","title":"Integer overflow in math ops in TensorFlow","description":"TensorFlow is an open source platform for machine learning. When `RangeSize` receives values that do not fit into an `int64_t`, it crashes. We have patched the issue in GitHub commit 37e64539cd29fcfb814c4451152a60f5d107b0f0. 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":"2022-09-16T21:20:28Z","modified":"2026-10-28T10:27:15Z","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":"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":"PyPI",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Party Advisory","advisory","web"]},{"url":"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rh87-q4vg-m45j","tags":["x_refsource_CONFIRM","x_transferred","Third Party Advisory","advisory","web"]},{"url":"https://github.com/tensorflow/tensorflow/commit/37e64539cd29fcfb814c4451152a60f5d107b0f0","tags":["x_refsource_MISC","x_transferred","Patch","Third Party Advisory","advisory","fix","web"]},{"url":"https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0","tags":["web"]},{"url":"https://nvd.nist.gov/vuln/detail/CVE-2022-36015","tags":["web","advisory"]},{"url":"https://github.com/advisories/GHSA-rh87-q4vg-m45j","tags":["advisory"]},{"url":"https://github.com/CVEProject/cvelistV5/tree/main/cves/2022/36xxx/CVE-2022-36015.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-2022-36015","title":"Integer overflow in math ops in TensorFlow","description":"TensorFlow is an open source platform for machine learning. When `RangeSize` receives values that do not fit into an `int64_t`, it crashes. We have patched the issue in GitHub commit 37e64539cd29fcfb814c4451152a60f5d107b0f0. 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":"2022-09-16T22:55:21Z","modified":"2025-04-23T16:58:53.732Z","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":"2026-11-02T14:34:35.945659Z"}],"euvd":[{"id":"EUVD-2022-6936","description":"TensorFlow is an open source platform for machine learning. When `RangeSize` receives values that do not fit into an `int64_t`, it crashes. We have patched the issue in GitHub commit 37e64539cd29fcfb814c4451152a60f5d107b0f0. 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":"2022-09-16T22:55:21Z","modified":"2025-04-23T16:58:53Z","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":"2026-11-02T20:52:11.440801Z"}],"ghsa":[{"id":"GHSA-rh87-q4vg-m45j","title":"TensorFlow vulnerable to integer overflow in math ops","description":"### Impact\nWhen [`RangeSize`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ops/math_ops.cc) receives values that do not fit into an `int64_t`, it crashes.\n```cpp\n  auto size = (std::is_integral\u003cT\u003e::value\n                   ? ((Eigen::numext::abs(limit - start) +\n                       Eigen::numext::abs(delta) - T(1)) /\n                      Eigen::numext::abs(delta))\n                   : (Eigen::numext::ceil(\n                         Eigen::numext::abs((limit - start) / delta))));\n\n  // This check does not cover all cases.\n  if (size \u003e std::numeric_limits\u003cint64_t\u003e::max()) {\n    return errors::InvalidArgument(\"Requires ((limit - start) / delta) \u003c= \",\n                                   std::numeric_limits\u003cint64_t\u003e::max());\n  }\n\n  c-\u003eset_output(0, c-\u003eVector(static_cast\u003cint64_t\u003e(size)));\n  return Status::OK();\n}\n```\n\n### Patches\nWe have patched the issue in GitHub commit [37e64539cd29fcfb814c4451152a60f5d107b0f0](https://github.com/tensorflow/tensorflow/commit/37e64539cd29fcfb814c4451152a60f5d107b0f0).\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","status":"published","published":"2022-09-16T21:20:28Z","modified":"2023-01-28T05:02:54Z","cwes":["CWE-190"],"updated_at":"2026-11-02T14:36:23.433782Z"}],"nvd":[{"id":"CVE-2022-36015","description":"TensorFlow is an open source platform for machine learning. When `RangeSize` receives values that do not fit into an `int64_t`, it crashes. We have patched the issue in GitHub commit 37e64539cd29fcfb814c4451152a60f5d107b0f0. 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":"2022-09-16T23:15:11.243Z","modified":"2026-06-17T04:52:44.717Z","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-2022-36015","title":"Integer overflow in math ops in TensorFlow","description":"TensorFlow is an open source platform for machine learning. When `RangeSize` receives values that do not fit into an `int64_t`, it crashes. We have patched the issue in GitHub commit 37e64539cd29fcfb814c4451152a60f5d107b0f0. 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":"2022-09-16T22:55:21Z","modified":"2026-10-28T10:27:15.541503457Z","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":"BIT-tensorflow-2022-36015","title":"Integer overflow in math ops in TensorFlow","description":"TensorFlow is an open source platform for machine learning. When `RangeSize` receives values that do not fit into an `int64_t`, it crashes. We have patched the issue in GitHub commit 37e64539cd29fcfb814c4451152a60f5d107b0f0. 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":"2024-03-06T11:12:05.086Z","modified":"2026-09-08T08:48:20.638961675Z","updated_at":"2026-11-02T15:28:35.51001Z"},{"id":"GHSA-rh87-q4vg-m45j","title":"TensorFlow vulnerable to integer overflow in math ops","description":"### Impact\nWhen [`RangeSize`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ops/math_ops.cc) receives values that do not fit into an `int64_t`, it crashes.\n```cpp\n  auto size = (std::is_integral\u003cT\u003e::value\n                   ? ((Eigen::numext::abs(limit - start) +\n                       Eigen::numext::abs(delta) - T(1)) /\n                      Eigen::numext::abs(delta))\n                   : (Eigen::numext::ceil(\n                         Eigen::numext::abs((limit - start) / delta))));\n\n  // This check does not cover all cases.\n  if (size \u003e std::numeric_limits\u003cint64_t\u003e::max()) {\n    return errors::InvalidArgument(\"Requires ((limit - start) / delta) \u003c= \",\n                                   std::numeric_limits\u003cint64_t\u003e::max());\n  }\n\n  c-\u003eset_output(0, c-\u003eVector(static_cast\u003cint64_t\u003e(size)));\n  return Status::OK();\n}\n```\n\n### Patches\nWe have patched the issue in GitHub commit [37e64539cd29fcfb814c4451152a60f5d107b0f0](https://github.com/tensorflow/tensorflow/commit/37e64539cd29fcfb814c4451152a60f5d107b0f0).\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","status":"published","published":"2022-09-16T21:20:28Z","modified":"2026-07-13T16:42:33.109807653Z","cwes":["CWE-190"],"updated_at":"2026-11-02T15:46:55.877614Z"},{"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"},{"id":"PYSEC-2026-1033","title":"TensorFlow vulnerable to integer overflow in math ops","description":"### Impact\nWhen [`RangeSize`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ops/math_ops.cc) receives values that do not fit into an `int64_t`, it crashes.\n```cpp\n  auto size = (std::is_integral\u003cT\u003e::value\n                   ? ((Eigen::numext::abs(limit - start) +\n                       Eigen::numext::abs(delta) - T(1)) /\n                      Eigen::numext::abs(delta))\n                   : (Eigen::numext::ceil(\n                         Eigen::numext::abs((limit - start) / delta))));\n\n  // This check does not cover all cases.\n  if (size \u003e std::numeric_limits\u003cint64_t\u003e::max()) {\n    return errors::InvalidArgument(\"Requires ((limit - start) / delta) \u003c= \",\n                                   std::numeric_limits\u003cint64_t\u003e::max());\n  }\n\n  c-\u003eset_output(0, c-\u003eVector(static_cast\u003cint64_t\u003e(size)));\n  return Status::OK();\n}\n```\n\n### Patches\nWe have patched the issue in GitHub commit [37e64539cd29fcfb814c4451152a60f5d107b0f0](https://github.com/tensorflow/tensorflow/commit/37e64539cd29fcfb814c4451152a60f5d107b0f0).\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","status":"published","published":"2026-07-07T10:17:19.118928Z","modified":"2026-07-13T16:42:33.109807653Z","updated_at":"2026-11-02T15:52:54.622769Z"},{"id":"PYSEC-2026-3237","title":"TensorFlow vulnerable to integer overflow in math ops","description":"### Impact\nWhen [`RangeSize`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ops/math_ops.cc) receives values that do not fit into an `int64_t`, it crashes.\n```cpp\n  auto size = (std::is_integral\u003cT\u003e::value\n                   ? ((Eigen::numext::abs(limit - start) +\n                       Eigen::numext::abs(delta) - T(1)) /\n                      Eigen::numext::abs(delta))\n                   : (Eigen::numext::ceil(\n                         Eigen::numext::abs((limit - start) / delta))));\n\n  // This check does not cover all cases.\n  if (size \u003e std::numeric_limits\u003cint64_t\u003e::max()) {\n    return errors::InvalidArgument(\"Requires ((limit - start) / delta) \u003c= \",\n                                   std::numeric_limits\u003cint64_t\u003e::max());\n  }\n\n  c-\u003eset_output(0, c-\u003eVector(static_cast\u003cint64_t\u003e(size)));\n  return Status::OK();\n}\n```\n\n### Patches\nWe have patched the issue in GitHub commit [37e64539cd29fcfb814c4451152a60f5d107b0f0](https://github.com/tensorflow/tensorflow/commit/37e64539cd29fcfb814c4451152a60f5d107b0f0).\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","status":"published","published":"2026-07-13T14:19:41.491214Z","modified":"2026-07-13T16:42:33.109807653Z","updated_at":"2026-11-02T15:52:56.429374Z"},{"id":"PYSEC-2026-3367","title":"TensorFlow vulnerable to integer overflow in math ops","description":"### Impact\nWhen [`RangeSize`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/ops/math_ops.cc) receives values that do not fit into an `int64_t`, it crashes.\n```cpp\n  auto size = (std::is_integral\u003cT\u003e::value\n                   ? ((Eigen::numext::abs(limit - start) +\n                       Eigen::numext::abs(delta) - T(1)) /\n                      Eigen::numext::abs(delta))\n                   : (Eigen::numext::ceil(\n                         Eigen::numext::abs((limit - start) / delta))));\n\n  // This check does not cover all cases.\n  if (size \u003e std::numeric_limits\u003cint64_t\u003e::max()) {\n    return errors::InvalidArgument(\"Requires ((limit - start) / delta) \u003c= \",\n                                   std::numeric_limits\u003cint64_t\u003e::max());\n  }\n\n  c-\u003eset_output(0, c-\u003eVector(static_cast\u003cint64_t\u003e(size)));\n  return Status::OK();\n}\n```\n\n### Patches\nWe have patched the issue in GitHub commit [37e64539cd29fcfb814c4451152a60f5d107b0f0](https://github.com/tensorflow/tensorflow/commit/37e64539cd29fcfb814c4451152a60f5d107b0f0).\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","status":"published","published":"2026-07-13T14:19:41.584736Z","modified":"2026-07-13T16:42:33.109807653Z","updated_at":"2026-11-02T15:52:56.847083Z"}]}}