Data corruption in tensorflow-lite
Key facts
- Attack vector
- Network
- Privileges required
- None
- User interaction
- None
- Attack complexity
- Low
- Impact type
- Code execution
- Confidentiality · integrity · availability
- High · High · High
- Fix status
- Fixed
Attack profile from CVSS 3.1 · NVD. Fix status from CNA and GitHub. Impact type from CWE-787 and the CVSS impact.
Summary
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 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 | before 1.15.4; 2.0.0 to before 2.0.3; 2.1.0 to before 2.1.2; 2.2.0 to before 2.2.1; 2.3.0 to before 2.3.1 | 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 | Patch available | CNA | |
| — | tensorflow (PyPI) | before 1.15.4 | 1.15.4 | Patch available | GHSA-mxjj-953w-2c2v |
| — | tensorflow (PyPI) | 2.0.0 to before 2.0.3 | 2.0.3 | Patch available | GHSA-mxjj-953w-2c2v |
| — | tensorflow (PyPI) | 2.1.0 to before 2.1.2 | 2.1.2 | Patch available | GHSA-mxjj-953w-2c2v |
| — | tensorflow (PyPI) | 2.2.0 to before 2.2.1 | 2.2.1 | Patch available | GHSA-mxjj-953w-2c2v |
| — | tensorflow (PyPI) | 2.3.0 to before 2.3.1 | 2.3.1 | Patch available | GHSA-mxjj-953w-2c2v |
| — | tensorflow-cpu (PyPI) | before 1.15.4 | 1.15.4 | Patch available | GHSA-mxjj-953w-2c2v |
| — | tensorflow-cpu (PyPI) | 2.0.0 to before 2.0.3 | 2.0.3 | Patch available | GHSA-mxjj-953w-2c2v |
| — | tensorflow-cpu (PyPI) | 2.1.0 to before 2.1.2 | 2.1.2 | Patch available | GHSA-mxjj-953w-2c2v |
| — | tensorflow-cpu (PyPI) | 2.2.0 to before 2.2.1 | 2.2.1 | Patch available | GHSA-mxjj-953w-2c2v |
| — | tensorflow-cpu (PyPI) | 2.3.0 to before 2.3.1 | 2.3.1 | Patch available | GHSA-mxjj-953w-2c2v |
| — | tensorflow-gpu (PyPI) | before 1.15.4 | 1.15.4 | Patch available | GHSA-mxjj-953w-2c2v |
| — | tensorflow-gpu (PyPI) | 2.0.0 to before 2.0.3 | 2.0.3 | Patch available | GHSA-mxjj-953w-2c2v |
| — | tensorflow-gpu (PyPI) | 2.1.0 to before 2.1.2 | 2.1.2 | Patch available | GHSA-mxjj-953w-2c2v |
| — | tensorflow-gpu (PyPI) | 2.2.0 to before 2.2.1 | 2.2.1 | Patch available | GHSA-mxjj-953w-2c2v |
| — | tensorflow-gpu (PyPI) | 2.3.0 to before 2.3.1 | 2.3.1 | Patch available | GHSA-mxjj-953w-2c2v |
- tensorflow VendorGoogle Affected before 1.15.4; 2.0.0 to before 2.0.3; 2.1.0 to before 2.1.2; 2.2.0 to before 2.2.1; 2.3.0 to before 2.3.1 Fixed in 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 Patch available CNA
- tensorflow (PyPI) Vendor— Affected before 1.15.4 Fixed in 1.15.4 Patch available GHSA-mxjj-953w-2c2v
- tensorflow (PyPI) Vendor— Affected 2.0.0 to before 2.0.3 Fixed in 2.0.3 Patch available GHSA-mxjj-953w-2c2v
- tensorflow (PyPI) Vendor— Affected 2.1.0 to before 2.1.2 Fixed in 2.1.2 Patch available GHSA-mxjj-953w-2c2v
- tensorflow (PyPI) Vendor— Affected 2.2.0 to before 2.2.1 Fixed in 2.2.1 Patch available GHSA-mxjj-953w-2c2v
- tensorflow (PyPI) Vendor— Affected 2.3.0 to before 2.3.1 Fixed in 2.3.1 Patch available GHSA-mxjj-953w-2c2v
- tensorflow-cpu (PyPI) Vendor— Affected before 1.15.4 Fixed in 1.15.4 Patch available GHSA-mxjj-953w-2c2v
- tensorflow-cpu (PyPI) Vendor— Affected 2.0.0 to before 2.0.3 Fixed in 2.0.3 Patch available GHSA-mxjj-953w-2c2v
- tensorflow-cpu (PyPI) Vendor— Affected 2.1.0 to before 2.1.2 Fixed in 2.1.2 Patch available GHSA-mxjj-953w-2c2v
- tensorflow-cpu (PyPI) Vendor— Affected 2.2.0 to before 2.2.1 Fixed in 2.2.1 Patch available GHSA-mxjj-953w-2c2v
- tensorflow-cpu (PyPI) Vendor— Affected 2.3.0 to before 2.3.1 Fixed in 2.3.1 Patch available GHSA-mxjj-953w-2c2v
- tensorflow-gpu (PyPI) Vendor— Affected before 1.15.4 Fixed in 1.15.4 Patch available GHSA-mxjj-953w-2c2v
- tensorflow-gpu (PyPI) Vendor— Affected 2.0.0 to before 2.0.3 Fixed in 2.0.3 Patch available GHSA-mxjj-953w-2c2v
- tensorflow-gpu (PyPI) Vendor— Affected 2.1.0 to before 2.1.2 Fixed in 2.1.2 Patch available GHSA-mxjj-953w-2c2v
- tensorflow-gpu (PyPI) Vendor— Affected 2.2.0 to before 2.2.1 Fixed in 2.2.1 Patch available GHSA-mxjj-953w-2c2v
- tensorflow-gpu (PyPI) Vendor— Affected 2.3.0 to before 2.3.1 Fixed in 2.3.1 Patch available GHSA-mxjj-953w-2c2v
Remediation
- Fix · CNA tensorflow (tensorflow) Fixed in 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1
- Fix · GHSA-mxjj-953w-2c2v tensorflow (PyPI) Fixed in 1.15.4 Advisory →
- Fix · GHSA-mxjj-953w-2c2v tensorflow (PyPI) Fixed in 2.0.3 Advisory →
- Fix · GHSA-mxjj-953w-2c2v tensorflow (PyPI) Fixed in 2.1.2 Advisory →
- Fix · GHSA-mxjj-953w-2c2v tensorflow (PyPI) Fixed in 2.2.1 Advisory →
- Fix · GHSA-mxjj-953w-2c2v tensorflow (PyPI) Fixed in 2.3.1 Advisory →
- Fix · GHSA-mxjj-953w-2c2v tensorflow-cpu (PyPI) Fixed in 1.15.4 Advisory →
- Fix · GHSA-mxjj-953w-2c2v tensorflow-cpu (PyPI) Fixed in 2.0.3 Advisory →
- Fix · GHSA-mxjj-953w-2c2v tensorflow-cpu (PyPI) Fixed in 2.1.2 Advisory →
- Fix · GHSA-mxjj-953w-2c2v tensorflow-cpu (PyPI) Fixed in 2.2.1 Advisory →
- Fix · GHSA-mxjj-953w-2c2v tensorflow-cpu (PyPI) Fixed in 2.3.1 Advisory →
- Fix · GHSA-mxjj-953w-2c2v tensorflow-gpu (PyPI) Fixed in 1.15.4 Advisory →
- Fix · GHSA-mxjj-953w-2c2v tensorflow-gpu (PyPI) Fixed in 2.0.3 Advisory →
- Fix · GHSA-mxjj-953w-2c2v tensorflow-gpu (PyPI) Fixed in 2.1.2 Advisory →
- Fix · GHSA-mxjj-953w-2c2v tensorflow-gpu (PyPI) Fixed in 2.2.1 Advisory →
- Fix · GHSA-mxjj-953w-2c2v tensorflow-gpu (PyPI) Fixed in 2.3.1 Advisory →
Fixed in the same release
Records fixed by the same vendor advisory or release, as the CNA lists them.
- Advisory ·
tensorflow — openSUSE-SU-2020:1766
16 records Highest priority Priority MEDIUM 6 MEDIUM, 10 LOW
Other records, highest priority first
- TI-2020-11977 Data leak in TensorflowPriority MEDIUM 44
- TI-2020-11979 Segfault and data corruption in tensorflow-litePriority MEDIUM 41
- TI-2020-11978 Denial of Service in TensorflowPriority MEDIUM 41
Timeline
- 2026-10-02 Threatist record created from CVE-2020-15208
- 2026-10-03 Alias added: GHSA-mxjj-953w-2c2v
References
Advisory 3
Other 4
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-288.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-323.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-131.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-2020-15208 · CVE Program
- CVE-2020-15208 · NVD
- FIRST EPSS
- GHSA-mxjj-953w-2c2v · GitHub Advisory Database · CC BY 4.0
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