{"id":"CVE-2020-5215","aliases":["BIT-tensorflow-2020-5215","EUVD-2020-0219","GHSA-977j-xj7q-2jr9","PYSEC-2020-258","PYSEC-2020-303","PYSEC-2020-338"],"status":"published","title":"Segmentation faultin TensorFlow when converting a Python string to tf.float16","description":"In TensorFlow before 1.15.2 and 2.0.1, converting a string (from Python) to a tf.float16 value results in a segmentation fault in eager mode as the format checks for this use case are only in the graph mode. This issue can lead to denial of service in inference/training where a malicious attacker can send a data point which contains a string instead of a tf.float16 value. Similar effects can be obtained by manipulating saved models and checkpoints whereby replacing a scalar tf.float16 value with a scalar string will trigger this issue due to automatic conversions. This can be easily reproduced by tf.constant(\"hello\", tf.float16), if eager execution is enabled. This issue is patched in TensorFlow 1.15.1 and 2.0.1 with this vulnerability patched. TensorFlow 2.1.0 was released after we fixed the issue, thus it is not affected. Users are encouraged to switch to TensorFlow 1.15.1, 2.0.1 or 2.1.0.","severity":{"version":"3.1","score":5,"vector":"CVSS:3.1/AV:L/AC:H/PR:L/UI:R/S:C/C:L/I:L/A:L","level":"medium","assessor":"cna","from":"cve"},"epss":{"day":"2026-11-09","score":0.00588,"percentile":0.48412,"model":"v2026.06.15"},"facts":{"in_kev":false,"known_exploited":false,"public_exploit":false,"fix_available":true},"cwes":["CWE-20","CWE-754"],"published":"2020-01-28T21:20:15Z","modified":"2026-10-20T14:14:08Z","fixes":[{"ecosystem":"PyPI","package":"tensorflow","fixed_in":["1.15.2","2.0.1"],"sources":["ghsa","osv"]},{"ecosystem":"PyPI","package":"tensorflow-cpu","fixed_in":["1.15.2","2.0.1"],"sources":["ghsa","osv"]},{"ecosystem":"PyPI","package":"tensorflow-gpu","fixed_in":["1.15.2","2.0.1"],"sources":["ghsa","osv"]},{"ecosystem":"Bitnami","package":"tensorflow","fixed_in":["1.15.2","2.0.1"],"sources":["osv"]}],"affected":[{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.15.2"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.0.0"},{"last_affected":"2.0.0"},{"fixed":"2.0.1"}]}],"versions":["2.0.0"]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.15.2"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.0.0"},{"last_affected":"2.0.0"},{"fixed":"2.0.1"}]}],"versions":["2.0.0"]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.15.2"}]}]},{"source":"ghsa","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.0.0"},{"last_affected":"2.0.0"},{"fixed":"2.0.1"}]}],"versions":["2.0.0"]},{"source":"osv","ecosystem":"Bitnami","package":"tensorflow","ranges":[{"type":"SEMVER","events":[{"introduced":"0"},{"fixed":"1.15.2"},{"introduced":"2.0.0"},{"fixed":"2.0.1"}]}]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.15.2"}]}],"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","1.2.0","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"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.0.0"},{"fixed":"2.0.1"}]}],"versions":["2.0.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.15.2"}]}],"versions":["1.15.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.0.0"},{"fixed":"2.0.1"}]}],"versions":["2.0.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.15.2"}]}],"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","1.2.0","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"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"2.0.0"},{"fixed":"2.0.1"}]}],"versions":["2.0.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow","ranges":[{"type":"GIT","events":[{"introduced":"0"},{"fixed":"5ac1b9e24ff6afc465756edf845d2e9660bd34bf"}]},{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.15.2"},{"introduced":"2.0.0"},{"fixed":"2.0.1"}]}],"versions":["0.12.0","0.12.0rc0","0.12.0rc1","0.12.1","1.0.0","1.0.1","1.1.0","1.1.0rc0","1.1.0rc1","1.1.0rc2","1.10.0","1.10.0rc0","1.10.0rc1","1.10.1","1.11.0","1.11.0rc0","1.11.0rc1","1.11.0rc2","1.12.0","1.12.0rc0","1.12.0rc1","1.12.0rc2","1.12.2","1.12.3","1.13.0rc0","1.13.0rc1","1.13.0rc2","1.13.1","1.13.2","1.14.0","1.14.0rc0","1.14.0rc1","1.15.0","1.15.0rc0","1.15.0rc1","1.15.0rc2","1.15.0rc3","1.2.0","1.2.0rc0","1.2.0rc1","1.2.0rc2","1.2.1","1.3.0","1.3.0rc0","1.3.0rc1","1.3.0rc2","1.4.0","1.4.0rc0","1.4.0rc1","1.4.1","1.5.0","1.5.0rc0","1.5.0rc1","1.5.1","1.6.0","1.6.0rc0","1.6.0rc1","1.7.0","1.7.0rc0","1.7.0rc1","1.7.1","1.8.0","1.8.0rc0","1.8.0rc1","1.9.0","1.9.0rc0","1.9.0rc1","1.9.0rc2","2.0.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-cpu","ranges":[{"type":"GIT","events":[{"introduced":"0"},{"fixed":"5ac1b9e24ff6afc465756edf845d2e9660bd34bf"}]},{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.15.2"},{"introduced":"2.0.0"},{"fixed":"2.0.1"}]}],"versions":["1.15.0"]},{"source":"osv","ecosystem":"PyPI","package":"tensorflow-gpu","ranges":[{"type":"GIT","events":[{"introduced":"0"},{"fixed":"5ac1b9e24ff6afc465756edf845d2e9660bd34bf"}]},{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.15.2"},{"introduced":"2.0.0"},{"fixed":"2.0.1"}]}],"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","1.2.0","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"]}],"products":[{"vendor":"google","product":"tensorflow"},{"vendor":"tensorflow","product":"tensorflow"}],"references":[{"url":"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-977j-xj7q-2jr9","tags":["x_refsource_CONFIRM","x_transferred","Exploit","Patch","Third Party Advisory","advisory","fix","web"]},{"url":"https://github.com/tensorflow/tensorflow/commit/5ac1b9e24ff6afc465756edf845d2e9660bd34bf","tags":["x_refsource_MISC","x_transferred","Patch","fix","web"]},{"url":"https://github.com/tensorflow/tensorflow/releases/tag/v1.15.2","tags":["x_refsource_MISC","x_transferred","Release Notes","article","advisory","web"]},{"url":"https://github.com/tensorflow/tensorflow/releases/tag/v2.0.1","tags":["x_refsource_MISC","x_transferred","Release Notes","article","advisory","web"]},{"url":"https://nvd.nist.gov/vuln/detail/CVE-2020-5215","tags":["web","advisory"]},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-303.yaml","tags":["web"]},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-338.yaml","tags":["web"]},{"url":"https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-258.yaml","tags":["web"]},{"url":"https://github.com/advisories/GHSA-977j-xj7q-2jr9"},{"url":"https://github.com/tensorflow/tensorflow","tags":["package"]}],"sources":{"cve":[{"id":"CVE-2020-5215","title":"Segmentation faultin TensorFlow when converting a Python string to tf.float16","description":"In TensorFlow before 1.15.2 and 2.0.1, converting a string (from Python) to a tf.float16 value results in a segmentation fault in eager mode as the format checks for this use case are only in the graph mode. This issue can lead to denial of service in inference/training where a malicious attacker can send a data point which contains a string instead of a tf.float16 value. Similar effects can be obtained by manipulating saved models and checkpoints whereby replacing a scalar tf.float16 value with a scalar string will trigger this issue due to automatic conversions. This can be easily reproduced by tf.constant(\"hello\", tf.float16), if eager execution is enabled. This issue is patched in TensorFlow 1.15.1 and 2.0.1 with this vulnerability patched. TensorFlow 2.1.0 was released after we fixed the issue, thus it is not affected. Users are encouraged to switch to TensorFlow 1.15.1, 2.0.1 or 2.1.0.","status":"published","published":"2020-01-28T21:20:15Z","modified":"2024-08-04T08:22:09.071Z","cvss":[{"version":"3.1","score":5,"vector":"CVSS:3.1/AV:L/AC:H/PR:L/UI:R/S:C/C:L/I:L/A:L","level":"medium","assessor":"cna"}],"cwes":["CWE-754"],"updated_at":"2026-11-02T14:35:47.56691Z"}],"euvd":[{"id":"EUVD-2020-0219","description":"In TensorFlow before 1.15.2 and 2.0.1, converting a string (from Python) to a tf.float16 value results in a segmentation fault in eager mode as the format checks for this use case are only in the graph mode. This issue can lead to denial of service in inference/training where a malicious attacker can send a data point which contains a string instead of a tf.float16 value. Similar effects can be obtained by manipulating saved models and checkpoints whereby replacing a scalar tf.float16 value with a scalar string will trigger this issue due to automatic conversions. This can be easily reproduced by tf.constant(\"hello\", tf.float16), if eager execution is enabled. This issue is patched in TensorFlow 1.15.1 and 2.0.1 with this vulnerability patched. TensorFlow 2.1.0 was released after we fixed the issue, thus it is not affected. Users are encouraged to switch to TensorFlow 1.15.1, 2.0.1 or 2.1.0.","status":"published","published":"2020-01-28T21:20:15Z","modified":"2024-08-04T08:22:09Z","cvss":[{"version":"3.1","score":5,"vector":"CVSS:3.1/AV:L/AC:H/PR:L/UI:R/S:C/C:L/I:L/A:L","level":"medium"}],"updated_at":"2026-11-03T03:08:07.28588Z"}],"ghsa":[{"id":"GHSA-977j-xj7q-2jr9","title":"Segmentation faultin TensorFlow when converting a Python string to `tf.float16`","description":"### Impact\n\nConverting a string (from Python) to a `tf.float16` value results in a segmentation fault in eager mode as the format checks for this use case are only in the graph mode.\n\nThis issue can lead to denial of service in inference/training where a malicious attacker can send a data point which contains a string instead of a `tf.float16` value.\n\nSimilar effects can be obtained by manipulating saved models and checkpoints whereby replacing a scalar `tf.float16` value with a scalar string will trigger this issue due to automatic conversions.\n\nThis can be easily reproduced by `tf.constant(\"hello\", tf.float16)`, if eager execution is enabled.\n\n### Patches\nWe have patched the vulnerability in GitHub commit [5ac1b9](https://github.com/tensorflow/tensorflow/commit/5ac1b9e24ff6afc465756edf845d2e9660bd34bf).\n\nWe are additionally releasing TensorFlow 1.15.1 and 2.0.1 with this vulnerability patched.\n\nTensorFlow 2.1.0 was released after we fixed the issue, thus it is not affected.\n\nWe encourage users to switch to TensorFlow 1.15.1, 2.0.1 or 2.1.0.\n\n### For more information\n\nPlease consult [`SECURITY.md`](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.","status":"published","published":"2020-01-28T21:32:29Z","modified":"2024-10-30T21:27:17Z","cvss":[{"version":"4.0","score":1,"vector":"CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:P/VC:L/VI:L/VA:L/SC:L/SI:L/SA:L","level":"low"},{"version":"3.1","score":5,"vector":"CVSS:3.1/AV:L/AC:H/PR:L/UI:R/S:C/C:L/I:L/A:L","level":"medium"}],"cwes":["CWE-754"],"updated_at":"2026-11-02T14:38:14.769863Z"}],"nvd":[{"id":"CVE-2020-5215","description":"In TensorFlow before 1.15.2 and 2.0.1, converting a string (from Python) to a tf.float16 value results in a segmentation fault in eager mode as the format checks for this use case are only in the graph mode. This issue can lead to denial of service in inference/training where a malicious attacker can send a data point which contains a string instead of a tf.float16 value. Similar effects can be obtained by manipulating saved models and checkpoints whereby replacing a scalar tf.float16 value with a scalar string will trigger this issue due to automatic conversions. This can be easily reproduced by tf.constant(\"hello\", tf.float16), if eager execution is enabled. This issue is patched in TensorFlow 1.15.1 and 2.0.1 with this vulnerability patched. TensorFlow 2.1.0 was released after we fixed the issue, thus it is not affected. Users are encouraged to switch to TensorFlow 1.15.1, 2.0.1 or 2.1.0.","status":"published","published":"2020-01-28T22:15:11.09Z","modified":"2026-06-17T03:21:02.443Z","cvss":[{"version":"3.1","score":5,"vector":"CVSS:3.1/AV:L/AC:H/PR:L/UI:R/S:C/C:L/I:L/A:L","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"},{"version":"2.0","score":4.3,"vector":"AV:N/AC:M/Au:N/C:N/I:N/A:P","level":"medium","assessor":"primary"}],"cwes":["CWE-754","CWE-20"],"updated_at":"2026-11-02T14:05:53.837808Z"}],"osv":[{"id":"CVE-2020-5215","description":"In TensorFlow before 1.15.2 and 2.0.1, converting a string (from Python) to a tf.float16 value results in a segmentation fault in eager mode as the format checks for this use case are only in the graph mode. This issue can lead to denial of service in inference/training where a malicious attacker can send a data point which contains a string instead of a tf.float16 value. Similar effects can be obtained by manipulating saved models and checkpoints whereby replacing a scalar tf.float16 value with a scalar string will trigger this issue due to automatic conversions. This can be easily reproduced by tf.constant(\"hello\", tf.float16), if eager execution is enabled. This issue is patched in TensorFlow 1.15.1 and 2.0.1 with this vulnerability patched. TensorFlow 2.1.0 was released after we fixed the issue, thus it is not affected. Users are encouraged to switch to TensorFlow 1.15.1, 2.0.1 or 2.1.0.","status":"published","published":"2020-01-28T22:15:11.09Z","modified":"2026-10-20T14:14:08.228115545Z","cvss":[{"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"}],"updated_at":"2026-11-02T15:44:16.936975Z"},{"id":"GHSA-977j-xj7q-2jr9","title":"Segmentation faultin TensorFlow when converting a Python string to `tf.float16`","description":"### Impact\n\nConverting a string (from Python) to a `tf.float16` value results in a segmentation fault in eager mode as the format checks for this use case are only in the graph mode.\n\nThis issue can lead to denial of service in inference/training where a malicious attacker can send a data point which contains a string instead of a `tf.float16` value.\n\nSimilar effects can be obtained by manipulating saved models and checkpoints whereby replacing a scalar `tf.float16` value with a scalar string will trigger this issue due to automatic conversions.\n\nThis can be easily reproduced by `tf.constant(\"hello\", tf.float16)`, if eager execution is enabled.\n\n### Patches\nWe have patched the vulnerability in GitHub commit [5ac1b9](https://github.com/tensorflow/tensorflow/commit/5ac1b9e24ff6afc465756edf845d2e9660bd34bf).\n\nWe are additionally releasing TensorFlow 1.15.1 and 2.0.1 with this vulnerability patched.\n\nTensorFlow 2.1.0 was released after we fixed the issue, thus it is not affected.\n\nWe encourage users to switch to TensorFlow 1.15.1, 2.0.1 or 2.1.0.\n\n### For more information\n\nPlease consult [`SECURITY.md`](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.","status":"published","published":"2020-01-28T21:32:29Z","modified":"2026-09-10T03:48:42.393454171Z","cvss":[{"version":"3.1","score":5,"vector":"CVSS:3.1/AV:L/AC:H/PR:L/UI:R/S:C/C:L/I:L/A:L","level":"medium"},{"version":"4.0","score":1,"vector":"CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:P/VC:L/VI:L/VA:L/SC:L/SI:L/SA:L","level":"low"}],"cwes":["CWE-754"],"updated_at":"2026-11-02T15:46:43.524801Z"},{"id":"BIT-tensorflow-2020-5215","title":"Segmentation faultin TensorFlow when converting a Python string to tf.float16","description":"In TensorFlow before 1.15.2 and 2.0.1, converting a string (from Python) to a tf.float16 value results in a segmentation fault in eager mode as the format checks for this use case are only in the graph mode. This issue can lead to denial of service in inference/training where a malicious attacker can send a data point which contains a string instead of a tf.float16 value. Similar effects can be obtained by manipulating saved models and checkpoints whereby replacing a scalar tf.float16 value with a scalar string will trigger this issue due to automatic conversions. This can be easily reproduced by tf.constant(\"hello\", tf.float16), if eager execution is enabled. This issue is patched in TensorFlow 1.15.1 and 2.0.1 with this vulnerability patched. TensorFlow 2.1.0 was released after we fixed the issue, thus it is not affected. Users are encouraged to switch to TensorFlow 1.15.1, 2.0.1 or 2.1.0.","status":"published","published":"2024-03-06T11:20:11.097Z","modified":"2026-09-08T08:48:19.886493108Z","updated_at":"2026-11-02T15:28:35.51001Z"},{"id":"PYSEC-2020-258","description":"In TensorFlow before 1.15.2 and 2.0.1, converting a string (from Python) to a tf.float16 value results in a segmentation fault in eager mode as the format checks for this use case are only in the graph mode. This issue can lead to denial of service in inference/training where a malicious attacker can send a data point which contains a string instead of a tf.float16 value. Similar effects can be obtained by manipulating saved models and checkpoints whereby replacing a scalar tf.float16 value with a scalar string will trigger this issue due to automatic conversions. This can be easily reproduced by tf.constant(\"hello\", tf.float16), if eager execution is enabled. This issue is patched in TensorFlow 1.15.1 and 2.0.1 with this vulnerability patched. TensorFlow 2.1.0 was released after we fixed the issue, thus it is not affected. Users are encouraged to switch to TensorFlow 1.15.1, 2.0.1 or 2.1.0.","status":"published","published":"2020-01-28T22:15:00Z","modified":"2023-12-06T01:00:35.702294Z","updated_at":"2026-11-02T15:52:52.192131Z"},{"id":"PYSEC-2020-303","description":"In TensorFlow before 1.15.2 and 2.0.1, converting a string (from Python) to a tf.float16 value results in a segmentation fault in eager mode as the format checks for this use case are only in the graph mode. This issue can lead to denial of service in inference/training where a malicious attacker can send a data point which contains a string instead of a tf.float16 value. Similar effects can be obtained by manipulating saved models and checkpoints whereby replacing a scalar tf.float16 value with a scalar string will trigger this issue due to automatic conversions. This can be easily reproduced by tf.constant(\"hello\", tf.float16), if eager execution is enabled. This issue is patched in TensorFlow 1.15.1 and 2.0.1 with this vulnerability patched. TensorFlow 2.1.0 was released after we fixed the issue, thus it is not affected. Users are encouraged to switch to TensorFlow 1.15.1, 2.0.1 or 2.1.0.","status":"published","published":"2020-01-28T22:15:00Z","modified":"2023-12-06T01:00:35.702294Z","updated_at":"2026-11-02T15:52:52.682031Z"},{"id":"PYSEC-2020-338","description":"In TensorFlow before 1.15.2 and 2.0.1, converting a string (from Python) to a tf.float16 value results in a segmentation fault in eager mode as the format checks for this use case are only in the graph mode. This issue can lead to denial of service in inference/training where a malicious attacker can send a data point which contains a string instead of a tf.float16 value. Similar effects can be obtained by manipulating saved models and checkpoints whereby replacing a scalar tf.float16 value with a scalar string will trigger this issue due to automatic conversions. This can be easily reproduced by tf.constant(\"hello\", tf.float16), if eager execution is enabled. This issue is patched in TensorFlow 1.15.1 and 2.0.1 with this vulnerability patched. TensorFlow 2.1.0 was released after we fixed the issue, thus it is not affected. Users are encouraged to switch to TensorFlow 1.15.1, 2.0.1 or 2.1.0.","status":"published","published":"2020-01-28T22:15:00Z","modified":"2023-12-06T01:00:35.702294Z","updated_at":"2026-11-02T15:52:52.682031Z"}]}}