CVE-2020-5215
CVE-2020-5215 is a medium-severity vulnerability in Google Tensorflow with a CVSS 3.x base score of 5.0. It is not currently listed as actively exploited by CISA, and its EPSS exploit-prediction score is low. The underlying weakness is classified as CWE-20.
Key facts
- Severity: Medium (CVSS 3.x base score 5.0)
- CVSS v2: 4.3
- EPSS exploit prediction: 1% (44th percentile)
- Actively exploited: Not listed in CISA KEV
- Weakness: CWE-20
- Affected product: Google Tensorflow
- Published:
- Last modified:
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.
Frequently asked questions
- What is CVE-2020-5215?
- 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.
- How severe is CVE-2020-5215?
- CVE-2020-5215 has a CVSS 3.x base score of 5.0, rated medium severity. It is exploitable over local access with high attack complexity, requires low privileges and user interaction. Impact on confidentiality is low, integrity low, and availability low.
- Is CVE-2020-5215 being actively exploited?
- It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 1% (44th percentile), an estimate of the probability of exploitation in the next 30 days.
- What products are affected by CVE-2020-5215?
- CVE-2020-5215 affects Google Tensorflow. See the affected-products list for the exact vulnerable versions.
- How do I fix CVE-2020-5215?
- Review the linked vendor and NVD advisories for patched versions and mitigations, then upgrade or apply the recommended workaround.
- When was CVE-2020-5215 published?
- CVE-2020-5215 was published on 2020-01-28 and last updated on 2026-06-17.
References
- https://github.com/tensorflow/tensorflow/commit/5ac1b9e24ff6afc465756edf845d2e9660bd34bf
- https://github.com/tensorflow/tensorflow/releases/tag/v1.15.2
- https://github.com/tensorflow/tensorflow/releases/tag/v2.0.1
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-977j-xj7q-2jr9
Affected products (1)
- cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*
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