Denial of Service in Tensorflow
Key facts
- Attack vector
- Network
- Privileges required
- Low
- User interaction
- None
- Attack complexity
- High
- Impact type
- Denial of service
- Confidentiality · integrity · availability
- None · None · High
- Fix status
- Fixed
Attack profile from CVSS 3.1 · CNA. Fix status from CNA and GitHub. Impact type from CWE-617.
Summary
In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix. However, malicious users can pass in tensors of different rank, resulting in a `CHECK` assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
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 | = 2.3.0 | — | No fix listed | CNA | |
| — | tensorflow (PyPI) | 2.3.0 to before 2.3.1 | 2.3.1 | Patch available | GHSA-qc53-44cj-vfvx |
| — | tensorflow-cpu (PyPI) | 2.3.0 to before 2.3.1 | 2.3.1 | Patch available | GHSA-qc53-44cj-vfvx |
| — | tensorflow-gpu (PyPI) | 2.3.0 to before 2.3.1 | 2.3.1 | Patch available | GHSA-qc53-44cj-vfvx |
- tensorflow VendorGoogle Affected = 2.3.0 Fixed in — No fix listed CNA
- tensorflow (PyPI) Vendor— Affected 2.3.0 to before 2.3.1 Fixed in 2.3.1 Patch available GHSA-qc53-44cj-vfvx
- tensorflow-cpu (PyPI) Vendor— Affected 2.3.0 to before 2.3.1 Fixed in 2.3.1 Patch available GHSA-qc53-44cj-vfvx
- tensorflow-gpu (PyPI) Vendor— Affected 2.3.0 to before 2.3.1 Fixed in 2.3.1 Patch available GHSA-qc53-44cj-vfvx
Remediation
- Fix · GHSA-qc53-44cj-vfvx tensorflow (PyPI) Fixed in 2.3.1 Advisory →
- Fix · GHSA-qc53-44cj-vfvx tensorflow-cpu (PyPI) Fixed in 2.3.1 Advisory →
- Fix · GHSA-qc53-44cj-vfvx tensorflow-gpu (PyPI) Fixed in 2.3.1 Advisory →
Timeline
- 2026-10-02 Threatist record created from CVE-2020-15197
- 2026-10-03 Alias added: GHSA-qc53-44cj-vfvx
References
Advisory 2
Other 4
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-277.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-312.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-120.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-2020-15197 · CVE Program
- CVE-2020-15197 · NVD
- FIRST EPSS
- GHSA-qc53-44cj-vfvx · GitHub Advisory Database · CC BY 4.0
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