{"id":"CVE-2021-29601","aliases":["BIT-tensorflow-2021-29601","EUVD-2021-0342","GHSA-9c84-4hx6-xmm4","PYSEC-2021-238","PYSEC-2021-529","PYSEC-2021-727"],"status":"published","title":"Integer overflow in TFLite concatentation","description":"TensorFlow is an end-to-end open source platform for machine learning. The TFLite implementation of concatenation is vulnerable to an integer overflow issue(https://github.com/tensorflow/tensorflow/blob/7b7352a724b690b11bfaae2cd54bc3907daf6285/tensorflow/lite/kernels/concatenation.cc#L70-L76). An attacker can craft a model such that the dimensions of one of the concatenation input overflow the values of `int`. TFLite uses `int` to represent tensor dimensions, whereas TF uses `int64`. Hence, valid TF models can trigger an integer overflow when converted to TFLite format. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.","severity":{"version":"3.1","score":6.3,"vector":"CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:H","level":"medium","assessor":"cna","from":"cve"},"epss":{"day":"2026-11-09","score":0.00192,"percentile":0.08878,"model":"v2026.06.15"},"facts":{"in_kev":false,"known_exploited":false,"public_exploit":false,"fix_available":true},"cwes":["CWE-190"],"published":"2021-05-14T19:21:29Z","modified":"2026-10-20T14:24:43Z","fixes":[{"ecosystem":"PyPI","package":"tensorflow","fixed_in":["2.1.4","2.2.3","2.3.3","2.4.2"],"sources":["ghsa","osv"]},{"ecosystem":"PyPI","package":"tensorflow-cpu","fixed_in":["2.1.4","2.2.3","2.3.3","2.4.2"],"sources":["ghsa","osv"]},{"ecosystem":"PyPI","package":"tensorflow-gpu","fixed_in":["2.1.4","2.2.3","2.3.3","2.4.2"],"sources":["ghsa","osv"]},{"ecosystem":"Bitnami","package":"tensorflow","fixed_in":["2.1.4","2.2.3","2.3.3","2.4.2"],"sources":["osv"]}],"affected":[{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.1.4"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.2.0"},{"fixed":"2.2.3"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.3.0"},{"fixed":"2.3.3"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.4.0"},{"fixed":"2.4.2"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.1.4"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.2.0"},{"fixed":"2.2.3"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.3.0"},{"fixed":"2.3.3"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.4.0"},{"fixed":"2.4.2"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.1.4"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.2.0"},{"fixed":"2.2.3"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.3.0"},{"fixed":"2.3.3"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.4.0"},{"fixed":"2.4.2"}]}]},{"source":"osv","ecosystem":"Bitnami","package":"tensorflow","ranges":[{"type":"SEMVER","events":[{"introduced":"0"},{"fixed":"2.1.4"},{"introduced":"2.2.0"},{"fixed":"2.2.3"},{"introduced":"2.3.0"},{"fixed":"2.3.3"},{"introduced":"2.4.0"},{"fixed":"2.4.2"}]}]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.1.4"}]}],"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"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.2.0"},{"fixed":"2.2.3"}]}],"versions":["2.2.0","2.2.1","2.2.2"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.3.0"},{"fixed":"2.3.3"}]}],"versions":["2.3.0","2.3.1","2.3.2"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.4.0"},{"fixed":"2.4.2"}]}],"versions":["2.4.0","2.4.1"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.1.4"}]}],"versions":["1.15.0","2.1.0","2.1.1","2.1.2","2.1.3"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.2.0"},{"fixed":"2.2.3"}]}],"versions":["2.2.0","2.2.1","2.2.2"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.3.0"},{"fixed":"2.3.3"}]}],"versions":["2.3.0","2.3.1","2.3.2"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.4.0"},{"fixed":"2.4.2"}]}],"versions":["2.4.0","2.4.1"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.1.4"}]}],"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.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Party Advisory","advisory","fix","web"]},{"url":"https://github.com/tensorflow/tensorflow/commit/4253f96a58486ffe84b61c0415bb234a4632ee73","tags":["x_refsource_MISC","x_transferred","Patch","Third Party Advisory","advisory","fix","web"]},{"url":"https://nvd.nist.gov/vuln/detail/CVE-2021-29601","tags":["web","advisory"]},{"url":"https://github.com/tensorflow/tensorflow/blob/7b7352a724b690b11bfaae2cd54bc3907daf6285/tensorflow/lite/kernels/concatenation.cc#L70-L76","tags":["web"]},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-529.yaml","tags":["web"]},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-727.yaml","tags":["web"]},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-238.yaml","tags":["web"]},{"url":"https://github.com/advisories/GHSA-9c84-4hx6-xmm4"},{"url":"https://github.com/tensorflow/tensorflow","tags":["package"]}],"sources":{"cve":[{"id":"CVE-2021-29601","title":"Integer overflow in TFLite concatentation","description":"TensorFlow is an end-to-end open source platform for machine learning. The TFLite implementation of concatenation is vulnerable to an integer overflow issue(https://github.com/tensorflow/tensorflow/blob/7b7352a724b690b11bfaae2cd54bc3907daf6285/tensorflow/lite/kernels/concatenation.cc#L70-L76). An attacker can craft a model such that the dimensions of one of the concatenation input overflow the values of `int`. TFLite uses `int` to represent tensor dimensions, whereas TF uses `int64`. Hence, valid TF models can trigger an integer overflow when converted to TFLite format. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.","status":"published","published":"2021-05-14T19:21:29Z","modified":"2024-08-03T22:11:06.247Z","cvss":[{"version":"3.1","score":6.3,"vector":"CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:H","level":"medium","assessor":"cna"}],"cwes":["CWE-190"],"updated_at":"2026-11-02T14:33:06.658806Z"}],"euvd":[{"id":"EUVD-2021-0342","description":"TensorFlow is an end-to-end open source platform for machine learning. The TFLite implementation of concatenation is vulnerable to an integer overflow issue(https://github.com/tensorflow/tensorflow/blob/7b7352a724b690b11bfaae2cd54bc3907daf6285/tensorflow/lite/kernels/concatenation.cc#L70-L76). An attacker can craft a model such that the dimensions of one of the concatenation input overflow the values of `int`. TFLite uses `int` to represent tensor dimensions, whereas TF uses `int64`. Hence, valid TF models can trigger an integer overflow when converted to TFLite format. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.","status":"published","published":"2021-05-14T19:21:29Z","modified":"2024-08-03T22:11:06Z","cvss":[{"version":"3.1","score":6.3,"vector":"CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:H","level":"medium"}],"updated_at":"2026-11-03T03:24:43.965438Z"}],"ghsa":[{"id":"GHSA-9c84-4hx6-xmm4","title":"Integer overflow in TFLite concatentation","description":"### Impact\nThe TFLite implementation of concatenation is [vulnerable to an integer overflow issue](https://github.com/tensorflow/tensorflow/blob/7b7352a724b690b11bfaae2cd54bc3907daf6285/tensorflow/lite/kernels/concatenation.cc#L70-L76):\n\n```cc\nfor (int d = 0; d \u003c t0-\u003edims-\u003esize; ++d) {\n  if (d == axis) { \n    sum_axis += t-\u003edims-\u003edata[axis]; \n  } else {\n    TF_LITE_ENSURE_EQ(context, t-\u003edims-\u003edata[d], t0-\u003edims-\u003edata[d]);\n  }\n}\n```\n\nAn attacker can craft a model such that the dimensions of one of the concatenation input overflow the values of `int`. TFLite uses `int` to represent tensor dimensions, whereas TF uses `int64`. Hence, valid TF models can trigger an integer overflow when converted to TFLite format.\n\n### Patches\nWe have patched the issue in GitHub commit [4253f96a58486ffe84b61c0415bb234a4632ee73](https://github.com/tensorflow/tensorflow/commit/4253f96a58486ffe84b61c0415bb234a4632ee73).\n\nThe fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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 members of the Aivul Team from Qihoo 360.","status":"published","published":"2021-05-21T14:28:08Z","modified":"2024-11-13T16:08:22Z","cvss":[{"version":"4.0","score":5.8,"vector":"CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:H/VA:H/SC:N/SI:N/SA:N","level":"medium"},{"version":"3.1","score":6.3,"vector":"CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:H","level":"medium"}],"cwes":["CWE-190"],"updated_at":"2026-11-02T14:38:17.357217Z"}],"nvd":[{"id":"CVE-2021-29601","description":"TensorFlow is an end-to-end open source platform for machine learning. The TFLite implementation of concatenation is vulnerable to an integer overflow issue(https://github.com/tensorflow/tensorflow/blob/7b7352a724b690b11bfaae2cd54bc3907daf6285/tensorflow/lite/kernels/concatenation.cc#L70-L76). An attacker can craft a model such that the dimensions of one of the concatenation input overflow the values of `int`. TFLite uses `int` to represent tensor dimensions, whereas TF uses `int64`. Hence, valid TF models can trigger an integer overflow when converted to TFLite format. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.","status":"published","published":"2021-05-14T20:15:15.487Z","modified":"2026-06-17T03:48:00.013Z","cvss":[{"version":"3.1","score":6.3,"vector":"CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:H","level":"medium","assessor":"secondary"},{"version":"3.1","score":7.1,"vector":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H","level":"high","assessor":"primary"},{"version":"2.0","score":3.6,"vector":"AV:L/AC:L/Au:N/C:N/I:P/A:P","level":"low","assessor":"primary"}],"cwes":["CWE-190"],"updated_at":"2026-11-02T14:06:53.343329Z"}],"osv":[{"id":"CVE-2021-29601","description":"TensorFlow is an end-to-end open source platform for machine learning. The TFLite implementation of concatenation is vulnerable to an integer overflow issue(https://github.com/tensorflow/tensorflow/blob/7b7352a724b690b11bfaae2cd54bc3907daf6285/tensorflow/lite/kernels/concatenation.cc#L70-L76). An attacker can craft a model such that the dimensions of one of the concatenation input overflow the values of `int`. TFLite uses `int` to represent tensor dimensions, whereas TF uses `int64`. Hence, valid TF models can trigger an integer overflow when converted to TFLite format. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.","status":"published","published":"2021-05-14T20:15:15.487Z","modified":"2026-10-20T14:24:43.468241084Z","cvss":[{"version":"3.1","score":7.1,"vector":"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H","level":"high"}],"updated_at":"2026-11-02T15:44:19.483607Z"},{"id":"GHSA-9c84-4hx6-xmm4","title":"Integer overflow in TFLite concatentation","description":"### Impact\nThe TFLite implementation of concatenation is [vulnerable to an integer overflow issue](https://github.com/tensorflow/tensorflow/blob/7b7352a724b690b11bfaae2cd54bc3907daf6285/tensorflow/lite/kernels/concatenation.cc#L70-L76):\n\n```cc\nfor (int d = 0; d \u003c t0-\u003edims-\u003esize; ++d) {\n  if (d == axis) { \n    sum_axis += t-\u003edims-\u003edata[axis]; \n  } else {\n    TF_LITE_ENSURE_EQ(context, t-\u003edims-\u003edata[d], t0-\u003edims-\u003edata[d]);\n  }\n}\n```\n\nAn attacker can craft a model such that the dimensions of one of the concatenation input overflow the values of `int`. TFLite uses `int` to represent tensor dimensions, whereas TF uses `int64`. Hence, valid TF models can trigger an integer overflow when converted to TFLite format.\n\n### Patches\nWe have patched the issue in GitHub commit [4253f96a58486ffe84b61c0415bb234a4632ee73](https://github.com/tensorflow/tensorflow/commit/4253f96a58486ffe84b61c0415bb234a4632ee73).\n\nThe fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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 members of the Aivul Team from Qihoo 360.","status":"published","published":"2021-05-21T14:28:08Z","modified":"2026-07-08T06:28:10.739267158Z","cvss":[{"version":"3.1","score":6.3,"vector":"CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:H","level":"medium"},{"version":"4.0","score":5.8,"vector":"CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:H/VA:H/SC:N/SI:N/SA:N","level":"medium"}],"cwes":["CWE-190"],"updated_at":"2026-11-02T15:46:43.524801Z"},{"id":"BIT-tensorflow-2021-29601","title":"Integer overflow in TFLite concatentation","description":"TensorFlow is an end-to-end open source platform for machine learning. The TFLite implementation of concatenation is vulnerable to an integer overflow issue(https://github.com/tensorflow/tensorflow/blob/7b7352a724b690b11bfaae2cd54bc3907daf6285/tensorflow/lite/kernels/concatenation.cc#L70-L76). An attacker can craft a model such that the dimensions of one of the concatenation input overflow the values of `int`. TFLite uses `int` to represent tensor dimensions, whereas TF uses `int64`. Hence, valid TF models can trigger an integer overflow when converted to TFLite format. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.","status":"published","published":"2024-03-06T11:18:18.197Z","modified":"2026-09-08T08:48:22.967965283Z","updated_at":"2026-11-02T15:28:35.51001Z"},{"id":"PYSEC-2021-238","description":"TensorFlow is an end-to-end open source platform for machine learning. The TFLite implementation of concatenation is vulnerable to an integer overflow issue(https://github.com/tensorflow/tensorflow/blob/7b7352a724b690b11bfaae2cd54bc3907daf6285/tensorflow/lite/kernels/concatenation.cc#L70-L76). An attacker can craft a model such that the dimensions of one of the concatenation input overflow the values of `int`. TFLite uses `int` to represent tensor dimensions, whereas TF uses `int64`. Hence, valid TF models can trigger an integer overflow when converted to TFLite format. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.","status":"published","published":"2021-05-14T20:15:00Z","modified":"2023-12-06T01:01:08.700122Z","updated_at":"2026-11-02T15:52:52.682031Z"},{"id":"PYSEC-2021-529","description":"TensorFlow is an end-to-end open source platform for machine learning. The TFLite implementation of concatenation is vulnerable to an integer overflow issue(https://github.com/tensorflow/tensorflow/blob/7b7352a724b690b11bfaae2cd54bc3907daf6285/tensorflow/lite/kernels/concatenation.cc#L70-L76). An attacker can craft a model such that the dimensions of one of the concatenation input overflow the values of `int`. TFLite uses `int` to represent tensor dimensions, whereas TF uses `int64`. Hence, valid TF models can trigger an integer overflow when converted to TFLite format. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.","status":"published","published":"2021-05-14T20:15:00Z","modified":"2023-12-06T01:01:08.700122Z","updated_at":"2026-11-02T15:52:53.119977Z"},{"id":"PYSEC-2021-727","description":"TensorFlow is an end-to-end open source platform for machine learning. The TFLite implementation of concatenation is vulnerable to an integer overflow issue(https://github.com/tensorflow/tensorflow/blob/7b7352a724b690b11bfaae2cd54bc3907daf6285/tensorflow/lite/kernels/concatenation.cc#L70-L76). An attacker can craft a model such that the dimensions of one of the concatenation input overflow the values of `int`. TFLite uses `int` to represent tensor dimensions, whereas TF uses `int64`. Hence, valid TF models can trigger an integer overflow when converted to TFLite format. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.","status":"published","published":"2021-05-14T20:15:00Z","modified":"2023-12-06T01:01:08.700122Z","updated_at":"2026-11-02T15:52:53.119977Z"}]}}