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Fencer Vulns
medium 5.0

CVE-2020-5215 json

Segmentation faultin TensorFlow when converting a Python string to tf.float16

published 2020-01-28 6 y ago modified 2026-09-10 1 mo ago also BIT-tensorflow-2020-5215 , EUVD-2020-0219 , GHSA-977j-xj7q-2jr9 , PYSEC-2020-258 , PYSEC-2020-303 , PYSEC-2020-338

cvss
5.0
version 3.1, CNA
cisa kev
Not listed
not in CISA's catalog
epss
0.6%
EPSS 0.6% chance of exploitation in 30 days, percentile 48%
public exploits
0
none known

Summary

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.

Patch / fix

  • pypi tensorflow 1.15.2, 2.0.1
  • pypi tensorflow-cpu 1.15.2, 2.0.1
  • pypi tensorflow-gpu 1.15.2, 2.0.1
  • bitnami tensorflow 1.15.2, 2.0.1
  • google tensorflow 1.15.2, 2.0.1

Exploit prediction

0.59% chance of exploitation in the next 30 days, higher than 48% of all scored CVEs (FIRST EPSS, 2026-11-08).

Exploits and checks

  • github.com https://github.com/tensorflow/tensorflow/security/advisories/GHSA-977j-xj7q-2jr9 referenced PoC, tagged "exploit" by a source, unverified

CVSS scores

assigned by version score vector
CNA 3.1 5.0 CVSS:3.1/AV:L/AC:H/PR:L/UI:R/S:C/C:L/I:L/A:L
GitHub 3.1 5.0 CVSS:3.1/AV:L/AC:H/PR:L/UI:R/S:C/C:L/I:L/A:L
NVD 3.1 7.5 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
NVD 2.0 4.3 AV:N/AC:M/Au:N/C:N/I:N/A:P
OSV 3.1 7.5 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

Affected packages

ecosystem package affected fixed in
pypi tensorflow
<1.15.2
>=2.0.0, <2.0.1
1.15.2
2.0.1
pypi tensorflow-cpu
<1.15.2
>=2.0.0, <2.0.1
1.15.2
2.0.1
pypi tensorflow-gpu
<1.15.2
>=2.0.0, <2.0.1
1.15.2
2.0.1
bitnami tensorflow
<1.15.2
>=2.0.0, <2.0.1
1.15.2
2.0.1

Affected products

  • TensorFlow TensorFlow

Classification

Weakness
  • CWE-754 Improper Check for Unusual or Exceptional Conditions
  • CWE-20 Improper Input Validation

References

Sources

Fencer Vulns keeps one entry per vulnerability: the CVE id wins, then GHSA, and records that alias each other are merged, except that two CVEs always keep separate entries. The same data is available as JSON.