{"id":"CVE-2021-37661","aliases":["BIT-tensorflow-2021-37661","EUVD-2021-0387","GHSA-gf88-j2mg-cc82","PYSEC-2021-283","PYSEC-2021-574","PYSEC-2021-772","openSUSE-SU-2022:10014-1","openSUSE-SU-2024:12116-1"],"status":"published","title":"Crash caused by integer conversion to unsigned in TensorFlow","description":"TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.","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":"2026-11-12","score":0.00154,"percentile":0.04624,"model":"v2026.06.15"},"facts":{"in_kev":false,"known_exploited":false,"public_exploit":false,"fix_available":true},"cwes":["CWE-681"],"published":"2021-08-12T21:05:17Z","modified":"2026-10-20T14:28:18Z","fixes":[{"ecosystem":"PyPI","package":"tensorflow","fixed_in":["2.3.4","2.4.3","2.5.1"],"sources":["ghsa","osv"]},{"ecosystem":"PyPI","package":"tensorflow-cpu","fixed_in":["2.3.4","2.4.3","2.5.1"],"sources":["ghsa","osv"]},{"ecosystem":"PyPI","package":"tensorflow-gpu","fixed_in":["2.3.4","2.4.3","2.5.1"],"sources":["ghsa","osv"]},{"ecosystem":"Bitnami","package":"tensorflow","fixed_in":["2.3.4","2.4.3","2.5.1"],"sources":["osv"]}],"affected":[{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.3.4"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.4.0"},{"fixed":"2.4.3"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.5.0"},{"last_affected":"2.5.0"},{"fixed":"2.5.1"}]}],"versions":["2.5.0"]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.3.4"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.4.0"},{"fixed":"2.4.3"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.5.0"},{"last_affected":"2.5.0"},{"fixed":"2.5.1"}]}],"versions":["2.5.0"]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.3.4"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.4.0"},{"fixed":"2.4.3"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.5.0"},{"last_affected":"2.5.0"},{"fixed":"2.5.1"}]}],"versions":["2.5.0"]},{"source":"osv","ecosystem":"Bitnami","package":"tensorflow","ranges":[{"type":"SEMVER","events":[{"introduced":"2.3.0"},{"fixed":"2.3.4"},{"introduced":"2.4.0"},{"fixed":"2.4.3"},{"introduced":"2.5.0"},{"fixed":"2.5.1"}]}]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.3.4"}]}],"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"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.4.0"},{"fixed":"2.4.3"}]}],"versions":["2.4.0","2.4.1","2.4.2"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.5.0"},{"fixed":"2.5.1"}]}],"versions":["2.5.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.3.4"}]}],"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"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.4.0"},{"fixed":"2.4.3"}]}],"versions":["2.4.0","2.4.1","2.4.2"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.5.0"},{"fixed":"2.5.1"}]}],"versions":["2.5.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.3.4"}]}],"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"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.4.0"},{"fixed":"2.4.3"}]}],"versions":["2.4.0","2.4.1","2.4.2"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.5.0"},{"fixed":"2.5.1"}]}],"versions":["2.5.0"]},{"source":"osv"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","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37681","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37682","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37683","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37684","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37685","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37686","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37687","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37688","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37689","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37690","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37691","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-37692","tags":["web"]},{"url":"","tags":["advisory"]},{"url":"https://www.suse.com/security/cve/CVE-2020-10531","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15190","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15191","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15194","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15202","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15203","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15204","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15205","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15206","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15207","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15208","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2020-15209","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-22922","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-22923","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-22926","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41195","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41196","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41197","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41198","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41199","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41200","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41201","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41202","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41203","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41204","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41205","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41206","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41207","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41208","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41209","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41210","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41211","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41212","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41213","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41214","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41215","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41216","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41217","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41218","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41219","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41220","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41221","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41222","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41223","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41224","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41225","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41226","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41227","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2021-41228","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21725","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21726","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21727","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21728","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21729","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21730","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21731","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21732","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21733","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21734","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21735","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21736","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21737","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21738","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21739","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21740","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-21741","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23557","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23558","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23559","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23560","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23561","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23562","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23563","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23564","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23565","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23566","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23567","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23568","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23569","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23570","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23571","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23572","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23573","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23574","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23575","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23576","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23577","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23578","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23579","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23580","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23581","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23582","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23583","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23584","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23585","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23586","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23587","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23588","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23589","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23590","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23591","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23594","tags":["web"]},{"url":"https://www.suse.com/security/cve/CVE-2022-23595","tags":["web"]}],"sources":{"cve":[{"id":"CVE-2021-37661","title":"Crash caused by integer conversion to unsigned in TensorFlow","description":"TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.","status":"published","published":"2021-08-12T21:05:17Z","modified":"2024-08-04T01:23:01.463Z","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-681"],"updated_at":"2026-11-02T14:32:58.028461Z"}],"euvd":[{"id":"EUVD-2021-0387","description":"TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.","status":"published","published":"2021-08-12T21:05:17Z","modified":"2024-08-04T01:23:01Z","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":"2026-11-03T03:24:27.254804Z"}],"ghsa":[{"id":"GHSA-gf88-j2mg-cc82","title":"Crash caused by integer conversion to unsigned","description":"### Impact\nAn attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments:\n\n```python\nimport tensorflow as tf\nfrom tensorflow.python.ops import gen_boosted_trees_ops\nimport numpy as np\n\nv= tf.Variable([0.0, 0.0, 0.0, 0.0, 0.0])\ngen_boosted_trees_ops.boosted_trees_create_quantile_stream_resource(\n  quantile_stream_resource_handle = v.handle,\n  epsilon = [74.82224],\n  num_streams = [-49], \n  max_elements = np.int32(586))\n```\n\nThe [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40):\n\n```cc\nclass BoostedTreesQuantileStreamResource : public ResourceBase {\n public:\n  BoostedTreesQuantileStreamResource(const float epsilon,\n                                     const int64 max_elements,\n                                     const int64 num_streams)\n      : are_buckets_ready_(false),\n        epsilon_(epsilon),\n        num_streams_(num_streams),\n        max_elements_(max_elements) {\n    streams_.reserve(num_streams_);\n    ...\n  }\n}\n```\n\nHowever, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library.\n\n### Patches\nWe have patched the issue in GitHub commit [8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992](https://github.com/tensorflow/tensorflow/commit/8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992).\n\nThe fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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":"2021-08-25T14:42:28Z","modified":"2024-11-13T20:54:42Z","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"},{"version":"4.0","score":6.8,"vector":"CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N","level":"medium"}],"cwes":["CWE-681"],"updated_at":"2026-11-02T14:38:17.357217Z"}],"nvd":[{"id":"CVE-2021-37661","description":"TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.","status":"published","published":"2021-08-12T21:15:08.867Z","modified":"2026-06-17T04:00:55.797Z","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-681"],"updated_at":"2026-11-02T14:06:56.943671Z"}],"osv":[{"id":"CVE-2021-37661","description":"TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.","status":"published","published":"2021-08-12T21:15:08.867Z","modified":"2026-10-20T14:28:18.789855892Z","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":"2026-11-02T15:44:20.434873Z"},{"id":"GHSA-gf88-j2mg-cc82","title":"Crash caused by integer conversion to unsigned","description":"### Impact\nAn attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments:\n\n```python\nimport tensorflow as tf\nfrom tensorflow.python.ops import gen_boosted_trees_ops\nimport numpy as np\n\nv= tf.Variable([0.0, 0.0, 0.0, 0.0, 0.0])\ngen_boosted_trees_ops.boosted_trees_create_quantile_stream_resource(\n  quantile_stream_resource_handle = v.handle,\n  epsilon = [74.82224],\n  num_streams = [-49], \n  max_elements = np.int32(586))\n```\n\nThe [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40):\n\n```cc\nclass BoostedTreesQuantileStreamResource : public ResourceBase {\n public:\n  BoostedTreesQuantileStreamResource(const float epsilon,\n                                     const int64 max_elements,\n                                     const int64 num_streams)\n      : are_buckets_ready_(false),\n        epsilon_(epsilon),\n        num_streams_(num_streams),\n        max_elements_(max_elements) {\n    streams_.reserve(num_streams_);\n    ...\n  }\n}\n```\n\nHowever, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library.\n\n### Patches\nWe have patched the issue in GitHub commit [8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992](https://github.com/tensorflow/tensorflow/commit/8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992).\n\nThe fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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":"2021-08-25T14:42:28Z","modified":"2026-07-08T06:27:38.715832426Z","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"},{"version":"4.0","score":6.8,"vector":"CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N","level":"medium"}],"cwes":["CWE-681"],"updated_at":"2026-11-02T15:46:47.822182Z"},{"id":"BIT-tensorflow-2021-37661","title":"Crash caused by integer conversion to unsigned in TensorFlow","description":"TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.","status":"published","published":"2024-03-06T11:17:20.384Z","modified":"2026-09-08T08:48:20.174796551Z","updated_at":"2026-11-02T15:28:35.51001Z"},{"id":"openSUSE-SU-2022:10014-1","title":"Security update for tensorflow2","description":"\nThis update for tensorflow fixes the following issues:\n\n\nUpdate to TF2 2.6.0 which fixes multiple CVEs (boo#1189423).\n\n- Introduction of bazel6.3 and basel-skylib1.0.3 as build\n  dependencies.\n  The latter has been adapted to all a version in its package\n  name (if %set_ver_suffix is set to 1). This allows multiple\n  versions to exist for one product (not installed).\n  NOTE: basel-skylib1.0.3 does not exist in oS:Factory:\n  basel-skylib in oS:Factory - the base version - is 1.0.3.\n","status":"published","published":"2022-06-18T16:01:26Z","modified":"2026-02-04T02:20:34.480131Z","updated_at":"2026-11-02T16:58:32.653274Z"},{"id":"openSUSE-SU-2024:12116-1","title":"tensorflow-lite-2.9.1-1.1 on GA media","description":"These are all security issues fixed in the tensorflow-lite-2.9.1-1.1 package on the GA media of openSUSE Tumbleweed.","status":"published","published":"2024-06-15T00:00:00Z","modified":"2026-02-04T03:04:19.609756Z","updated_at":"2026-11-02T16:58:35.485255Z"},{"id":"PYSEC-2021-283","description":"TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.","status":"published","published":"2021-08-12T21:15:00Z","modified":"2023-12-06T01:01:22.813637Z","updated_at":"2026-11-02T15:52:52.682031Z"},{"id":"PYSEC-2021-574","description":"TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.","status":"published","published":"2021-08-12T21:15:00Z","modified":"2023-12-06T01:01:22.813637Z","updated_at":"2026-11-02T15:52:53.119977Z"},{"id":"PYSEC-2021-772","description":"TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.","status":"published","published":"2021-08-12T21:15:00Z","modified":"2023-12-06T01:01:22.813637Z","updated_at":"2026-11-02T15:52:53.119977Z"}]}}