Invalid validation in `SparseMatrixSparseCholesky`
Key facts
- Attack vector
- Local
- Privileges required
- Low
- User interaction
- None
- Attack complexity
- Low
- Impact type
- Denial of service
- 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-476.
Summary
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a null pointer dereference by providing an invalid `permutation` to `tf.raw_ops.SparseMatrixSparseCholesky`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/080f1d9e257589f78b3ffb75debf584168aa6062/tensorflow/core/kernels/sparse/sparse_cholesky_op.cc#L85-L86) fails to properly validate the input arguments. Although `ValidateInputs` is called and there are checks in the body of this function, the code proceeds to the next line in `ValidateInputs` since `OP_REQUIRES`(https://github.com/tensorflow/tensorflow/blob/080f1d9e257589f78b3ffb75debf584168aa6062/tensorflow/core/framework/op_requires.h#L41-L48) is a macro that only exits the current function. Thus, the first validation condition that fails in `ValidateInputs` will cause an early return from that function. However, the caller will continue execution from the next line. The fix is to either explicitly check `context->status()` or to convert `ValidateInputs` to return a `Status`. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
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 2.1.4; 2.2.0 to before 2.2.3; 2.3.0 to before 2.3.3; 2.4.0 to before 2.4.2 | 2.1.4, 2.2.3, 2.3.3, 2.4.2 | Patch available | CNA | |
| — | tensorflow (PyPI) | before 2.1.4 | 2.1.4 | Patch available | GHSA-xcwj-wfcm-m23c |
| — | tensorflow (PyPI) | 2.2.0 to before 2.2.3 | 2.2.3 | Patch available | GHSA-xcwj-wfcm-m23c |
| — | tensorflow (PyPI) | 2.3.0 to before 2.3.3 | 2.3.3 | Patch available | GHSA-xcwj-wfcm-m23c |
| — | tensorflow (PyPI) | 2.4.0 to before 2.4.2 | 2.4.2 | Patch available | GHSA-xcwj-wfcm-m23c |
| — | tensorflow-cpu (PyPI) | before 2.1.4 | 2.1.4 | Patch available | GHSA-xcwj-wfcm-m23c |
| — | tensorflow-cpu (PyPI) | 2.2.0 to before 2.2.3 | 2.2.3 | Patch available | GHSA-xcwj-wfcm-m23c |
| — | tensorflow-cpu (PyPI) | 2.3.0 to before 2.3.3 | 2.3.3 | Patch available | GHSA-xcwj-wfcm-m23c |
| — | tensorflow-cpu (PyPI) | 2.4.0 to before 2.4.2 | 2.4.2 | Patch available | GHSA-xcwj-wfcm-m23c |
| — | tensorflow-gpu (PyPI) | before 2.1.4 | 2.1.4 | Patch available | GHSA-xcwj-wfcm-m23c |
| — | tensorflow-gpu (PyPI) | 2.2.0 to before 2.2.3 | 2.2.3 | Patch available | GHSA-xcwj-wfcm-m23c |
| — | tensorflow-gpu (PyPI) | 2.3.0 to before 2.3.3 | 2.3.3 | Patch available | GHSA-xcwj-wfcm-m23c |
| — | tensorflow-gpu (PyPI) | 2.4.0 to before 2.4.2 | 2.4.2 | Patch available | GHSA-xcwj-wfcm-m23c |
- tensorflow VendorGoogle Affected before 2.1.4; 2.2.0 to before 2.2.3; 2.3.0 to before 2.3.3; 2.4.0 to before 2.4.2 Fixed in 2.1.4, 2.2.3, 2.3.3, 2.4.2 Patch available CNA
- tensorflow (PyPI) Vendor— Affected before 2.1.4 Fixed in 2.1.4 Patch available GHSA-xcwj-wfcm-m23c
- tensorflow (PyPI) Vendor— Affected 2.2.0 to before 2.2.3 Fixed in 2.2.3 Patch available GHSA-xcwj-wfcm-m23c
- tensorflow (PyPI) Vendor— Affected 2.3.0 to before 2.3.3 Fixed in 2.3.3 Patch available GHSA-xcwj-wfcm-m23c
- tensorflow (PyPI) Vendor— Affected 2.4.0 to before 2.4.2 Fixed in 2.4.2 Patch available GHSA-xcwj-wfcm-m23c
- tensorflow-cpu (PyPI) Vendor— Affected before 2.1.4 Fixed in 2.1.4 Patch available GHSA-xcwj-wfcm-m23c
- tensorflow-cpu (PyPI) Vendor— Affected 2.2.0 to before 2.2.3 Fixed in 2.2.3 Patch available GHSA-xcwj-wfcm-m23c
- tensorflow-cpu (PyPI) Vendor— Affected 2.3.0 to before 2.3.3 Fixed in 2.3.3 Patch available GHSA-xcwj-wfcm-m23c
- tensorflow-cpu (PyPI) Vendor— Affected 2.4.0 to before 2.4.2 Fixed in 2.4.2 Patch available GHSA-xcwj-wfcm-m23c
- tensorflow-gpu (PyPI) Vendor— Affected before 2.1.4 Fixed in 2.1.4 Patch available GHSA-xcwj-wfcm-m23c
- tensorflow-gpu (PyPI) Vendor— Affected 2.2.0 to before 2.2.3 Fixed in 2.2.3 Patch available GHSA-xcwj-wfcm-m23c
- tensorflow-gpu (PyPI) Vendor— Affected 2.3.0 to before 2.3.3 Fixed in 2.3.3 Patch available GHSA-xcwj-wfcm-m23c
- tensorflow-gpu (PyPI) Vendor— Affected 2.4.0 to before 2.4.2 Fixed in 2.4.2 Patch available GHSA-xcwj-wfcm-m23c
CPE configurations NVD · 1
| CPE | Versions | Role | Vendor |
|---|---|---|---|
| cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:* | before 2.1.4; 2.2.0 to before 2.2.3; 2.3.0 to before 2.3.3; 2.4.0 to before 2.4.2 | Vulnerable |
- cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:* Versions before 2.1.4; 2.2.0 to before 2.2.3; 2.3.0 to before 2.3.3; 2.4.0 to before 2.4.2 Vulnerable ·Google
Remediation
- Fix · CNA tensorflow (tensorflow) Fixed in 2.1.4, 2.2.3, 2.3.3, 2.4.2
- Fix · GHSA-xcwj-wfcm-m23c tensorflow (PyPI) Fixed in 2.1.4 Advisory →
- Fix · GHSA-xcwj-wfcm-m23c tensorflow (PyPI) Fixed in 2.2.3 Advisory →
- Fix · GHSA-xcwj-wfcm-m23c tensorflow (PyPI) Fixed in 2.3.3 Advisory →
- Fix · GHSA-xcwj-wfcm-m23c tensorflow (PyPI) Fixed in 2.4.2 Advisory →
- Fix · GHSA-xcwj-wfcm-m23c tensorflow-cpu (PyPI) Fixed in 2.1.4 Advisory →
- Fix · GHSA-xcwj-wfcm-m23c tensorflow-cpu (PyPI) Fixed in 2.2.3 Advisory →
- Fix · GHSA-xcwj-wfcm-m23c tensorflow-cpu (PyPI) Fixed in 2.3.3 Advisory →
- Fix · GHSA-xcwj-wfcm-m23c tensorflow-cpu (PyPI) Fixed in 2.4.2 Advisory →
- Fix · GHSA-xcwj-wfcm-m23c tensorflow-gpu (PyPI) Fixed in 2.1.4 Advisory →
- Fix · GHSA-xcwj-wfcm-m23c tensorflow-gpu (PyPI) Fixed in 2.2.3 Advisory →
- Fix · GHSA-xcwj-wfcm-m23c tensorflow-gpu (PyPI) Fixed in 2.3.3 Advisory →
- Fix · GHSA-xcwj-wfcm-m23c tensorflow-gpu (PyPI) Fixed in 2.4.2 Advisory →
Timeline
- 2026-10-02 Threatist record created from CVE-2021-29530
- 2026-10-03 Alias added: GHSA-xcwj-wfcm-m23c
References
Other 4
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-458.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-656.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-167.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-2021-29530 · CVE Program
- CVE-2021-29530 · NVD
- FIRST EPSS
- GHSA-xcwj-wfcm-m23c · GitHub Advisory Database · CC BY 4.0
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