Segmentation faultin TensorFlow when converting a Python string to tf.float16
Key facts
- Attack vector
- Network
- Privileges required
- None
- User interaction
- None
- Attack complexity
- Low
- Impact type
- —
- Confidentiality · integrity · availability
- None · None · High
- Fix status
- Fixed
Attack profile from CVSS 3.1 · NVD. Fix status from CNA and GitHub.
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.
Why it matters now
SSVC decision points
Not available: CISA has not published SSVC decision points for this record.
Affected products
| Vendor | Product | Affected versions | Fixed in | Status | Source |
|---|---|---|---|---|---|
| TensorFlow | before 1.15.2; = 2.0.0 | 1.15.2 | Patch available | CNA | |
| — | tensorflow (PyPI) | before 1.15.2 | 1.15.2 | Patch available | GHSA-977j-xj7q-2jr9 |
| — | tensorflow (PyPI) | 2.0.0 to before 2.0.1 | 2.0.1 | Patch available | GHSA-977j-xj7q-2jr9 |
| — | tensorflow-cpu (PyPI) | before 1.15.2 | 1.15.2 | Patch available | GHSA-977j-xj7q-2jr9 |
| — | tensorflow-cpu (PyPI) | 2.0.0 to before 2.0.1 | 2.0.1 | Patch available | GHSA-977j-xj7q-2jr9 |
| — | tensorflow-gpu (PyPI) | before 1.15.2 | 1.15.2 | Patch available | GHSA-977j-xj7q-2jr9 |
| — | tensorflow-gpu (PyPI) | 2.0.0 to before 2.0.1 | 2.0.1 | Patch available | GHSA-977j-xj7q-2jr9 |
- TensorFlow VendorGoogle Affected before 1.15.2; = 2.0.0 Fixed in 1.15.2 Patch available CNA
- tensorflow (PyPI) Vendor— Affected before 1.15.2 Fixed in 1.15.2 Patch available GHSA-977j-xj7q-2jr9
- tensorflow (PyPI) Vendor— Affected 2.0.0 to before 2.0.1 Fixed in 2.0.1 Patch available GHSA-977j-xj7q-2jr9
- tensorflow-cpu (PyPI) Vendor— Affected before 1.15.2 Fixed in 1.15.2 Patch available GHSA-977j-xj7q-2jr9
- tensorflow-cpu (PyPI) Vendor— Affected 2.0.0 to before 2.0.1 Fixed in 2.0.1 Patch available GHSA-977j-xj7q-2jr9
- tensorflow-gpu (PyPI) Vendor— Affected before 1.15.2 Fixed in 1.15.2 Patch available GHSA-977j-xj7q-2jr9
- tensorflow-gpu (PyPI) Vendor— Affected 2.0.0 to before 2.0.1 Fixed in 2.0.1 Patch available GHSA-977j-xj7q-2jr9
Remediation
- Fix · CNA TensorFlow (TensorFlow) Fixed in 1.15.2
- Fix · GHSA-977j-xj7q-2jr9 tensorflow (PyPI) Fixed in 1.15.2 Advisory →
- Fix · GHSA-977j-xj7q-2jr9 tensorflow (PyPI) Fixed in 2.0.1 Advisory →
- Fix · GHSA-977j-xj7q-2jr9 tensorflow-cpu (PyPI) Fixed in 1.15.2 Advisory →
- Fix · GHSA-977j-xj7q-2jr9 tensorflow-cpu (PyPI) Fixed in 2.0.1 Advisory →
- Fix · GHSA-977j-xj7q-2jr9 tensorflow-gpu (PyPI) Fixed in 1.15.2 Advisory →
- Fix · GHSA-977j-xj7q-2jr9 tensorflow-gpu (PyPI) Fixed in 2.0.1 Advisory →
Timeline
- 2026-10-02 Threatist record created from CVE-2020-5215
- 2026-10-03 Alias added: GHSA-977j-xj7q-2jr9
References
Other 6
- https://github.com/tensorflow/tensorflow/releases/tag/v1.15.2
- https://github.com/tensorflow/tensorflow/releases/tag/v2.0.1
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-303.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-338.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-258.yaml
- https://github.com/tensorflow/tensorflow
More Google Tensorflow vulnerabilities
- TI-2022-20241 FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess in Tensorflow CVSS 3.1CRITICAL 9.8
- TI-2022-07640 Integer overflow in Tensorflow CVSS 3.1CRITICAL 9.8
- TI-2022-07627 Out of bounds read and write in Tensorflow CVSS 3.1HIGH 8.8
- TI-2022-07619 Out of bounds write in Tensorflow CVSS 3.1HIGH 8.8
- TI-2022-07613 Read and Write outside of bounds in TFLite CVSS 3.1HIGH 8.8
- TI-2022-07612 Integer overflow in TFLite CVSS 3.1HIGH 8.8
Sources
- CVE-2020-5215 · CVE Program
- CVE-2020-5215 · NVD
- FIRST EPSS
- GHSA-977j-xj7q-2jr9 · GitHub Advisory Database · CC BY 4.0
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