Heap OOB in nested `tf.map_fn` with `RaggedTensor`s in TensorFlow
Key facts
- Attack vector
- Local
- Privileges required
- Low
- User interaction
- None
- Attack complexity
- Low
- Impact type
- —
- Confidentiality · integrity · availability
- High · High · High
- Fix status
- Fixed
Attack profile from CVSS 3.1 · NVD. Fix status from CNA and GitHub.
Summary
TensorFlow is an end-to-end open source platform for machine learning. In affected versions it is possible to nest a `tf.map_fn` within another `tf.map_fn` call. However, if the input tensor is a `RaggedTensor` and there is no function signature provided, code assumes the output is a fully specified tensor and fills output buffer with uninitialized contents from the heap. The `t` and `z` outputs should be identical, however this is not the case. The last row of `t` contains data from the heap which can be used to leak other memory information. The bug lies in the conversion from a `Variant` tensor to a `RaggedTensor`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/ragged_tensor_from_variant_op.cc#L177-L190) does not check that all inner shapes match and this results in the additional dimensions. The same implementation can result in data loss, if input tensor is tweaked. We have patched the issue in GitHub commit 4e2565483d0ffcadc719bd44893fb7f609bb5f12. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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 | 2.5.0 to before 2.5.1; 2.4.0 to before 2.4.3; before 2.3.4 | 2.5.1, 2.4.3, 2.3.4 | Patch available | CNA | |
| — | tensorflow (PyPI) | before 2.3.4 | 2.3.4 | Patch available | GHSA-g8wg-cjwc-xhhp |
| — | tensorflow (PyPI) | 2.4.0 to before 2.4.3 | 2.4.3 | Patch available | GHSA-g8wg-cjwc-xhhp |
| — | tensorflow (PyPI) | 2.5.0 to before 2.5.1 | 2.5.1 | Patch available | GHSA-g8wg-cjwc-xhhp |
| — | tensorflow-cpu (PyPI) | before 2.3.4 | 2.3.4 | Patch available | GHSA-g8wg-cjwc-xhhp |
| — | tensorflow-cpu (PyPI) | 2.4.0 to before 2.4.3 | 2.4.3 | Patch available | GHSA-g8wg-cjwc-xhhp |
| — | tensorflow-cpu (PyPI) | 2.5.0 to before 2.5.1 | 2.5.1 | Patch available | GHSA-g8wg-cjwc-xhhp |
| — | tensorflow-gpu (PyPI) | before 2.3.4 | 2.3.4 | Patch available | GHSA-g8wg-cjwc-xhhp |
| — | tensorflow-gpu (PyPI) | 2.4.0 to before 2.4.3 | 2.4.3 | Patch available | GHSA-g8wg-cjwc-xhhp |
| — | tensorflow-gpu (PyPI) | 2.5.0 to before 2.5.1 | 2.5.1 | Patch available | GHSA-g8wg-cjwc-xhhp |
- tensorflow VendorGoogle Affected 2.5.0 to before 2.5.1; 2.4.0 to before 2.4.3; before 2.3.4 Fixed in 2.5.1, 2.4.3, 2.3.4 Patch available CNA
- tensorflow (PyPI) Vendor— Affected before 2.3.4 Fixed in 2.3.4 Patch available GHSA-g8wg-cjwc-xhhp
- tensorflow (PyPI) Vendor— Affected 2.4.0 to before 2.4.3 Fixed in 2.4.3 Patch available GHSA-g8wg-cjwc-xhhp
- tensorflow (PyPI) Vendor— Affected 2.5.0 to before 2.5.1 Fixed in 2.5.1 Patch available GHSA-g8wg-cjwc-xhhp
- tensorflow-cpu (PyPI) Vendor— Affected before 2.3.4 Fixed in 2.3.4 Patch available GHSA-g8wg-cjwc-xhhp
- tensorflow-cpu (PyPI) Vendor— Affected 2.4.0 to before 2.4.3 Fixed in 2.4.3 Patch available GHSA-g8wg-cjwc-xhhp
- tensorflow-cpu (PyPI) Vendor— Affected 2.5.0 to before 2.5.1 Fixed in 2.5.1 Patch available GHSA-g8wg-cjwc-xhhp
- tensorflow-gpu (PyPI) Vendor— Affected before 2.3.4 Fixed in 2.3.4 Patch available GHSA-g8wg-cjwc-xhhp
- tensorflow-gpu (PyPI) Vendor— Affected 2.4.0 to before 2.4.3 Fixed in 2.4.3 Patch available GHSA-g8wg-cjwc-xhhp
- tensorflow-gpu (PyPI) Vendor— Affected 2.5.0 to before 2.5.1 Fixed in 2.5.1 Patch available GHSA-g8wg-cjwc-xhhp
CPE configurations NVD · 5
| CPE | Versions | Role | Vendor |
|---|---|---|---|
| cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:* | 2.3.0 to before 2.3.4; 2.4.0 to before 2.4.3 | Vulnerable | |
| cpe:2.3:a:google:tensorflow:2.5.0:*:*:*:*:*:*:* | 2.5.0 | Vulnerable | |
| cpe:2.3:a:google:tensorflow:2.6.0:rc0:*:*:*:*:*:* | 2.6.0 rc0 | Vulnerable | |
| cpe:2.3:a:google:tensorflow:2.6.0:rc1:*:*:*:*:*:* | 2.6.0 rc1 | Vulnerable | |
| cpe:2.3:a:google:tensorflow:2.6.0:rc2:*:*:*:*:*:* | 2.6.0 rc2 | Vulnerable |
- cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:* Versions 2.3.0 to before 2.3.4; 2.4.0 to before 2.4.3 Vulnerable ·Google
- cpe:2.3:a:google:tensorflow:2.5.0:*:*:*:*:*:*:* Versions 2.5.0 Vulnerable ·Google
- cpe:2.3:a:google:tensorflow:2.6.0:rc0:*:*:*:*:*:* Versions 2.6.0 rc0 Vulnerable ·Google
- cpe:2.3:a:google:tensorflow:2.6.0:rc1:*:*:*:*:*:* Versions 2.6.0 rc1 Vulnerable ·Google
- cpe:2.3:a:google:tensorflow:2.6.0:rc2:*:*:*:*:*:* Versions 2.6.0 rc2 Vulnerable ·Google
Remediation
- Fix · CNA tensorflow (tensorflow) Fixed in 2.5.1, 2.4.3, 2.3.4
- Fix · GHSA-g8wg-cjwc-xhhp tensorflow (PyPI) Fixed in 2.3.4 Advisory →
- Fix · GHSA-g8wg-cjwc-xhhp tensorflow (PyPI) Fixed in 2.4.3 Advisory →
- Fix · GHSA-g8wg-cjwc-xhhp tensorflow (PyPI) Fixed in 2.5.1 Advisory →
- Fix · GHSA-g8wg-cjwc-xhhp tensorflow-cpu (PyPI) Fixed in 2.3.4 Advisory →
- Fix · GHSA-g8wg-cjwc-xhhp tensorflow-cpu (PyPI) Fixed in 2.4.3 Advisory →
- Fix · GHSA-g8wg-cjwc-xhhp tensorflow-cpu (PyPI) Fixed in 2.5.1 Advisory →
- Fix · GHSA-g8wg-cjwc-xhhp tensorflow-gpu (PyPI) Fixed in 2.3.4 Advisory →
- Fix · GHSA-g8wg-cjwc-xhhp tensorflow-gpu (PyPI) Fixed in 2.4.3 Advisory →
- Fix · GHSA-g8wg-cjwc-xhhp tensorflow-gpu (PyPI) Fixed in 2.5.1 Advisory →
Timeline
- 2026-10-02 Threatist record created from CVE-2021-37679
- 2026-10-03 Alias added: GHSA-g8wg-cjwc-xhhp
References
Advisory 2
Other 4
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-592.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-790.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-301.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-2021-37679 · CVE Program
- CVE-2021-37679 · NVD
- FIRST EPSS
- GHSA-g8wg-cjwc-xhhp · GitHub Advisory Database · CC BY 4.0
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