Use after free in boosted trees creation in TensorFlow
Key facts
- Attack vector
- Local
- Privileges required
- Low
- 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 · CNA. Fix status from CNA and GitHub. Impact type from CWE-416 and the CVSS impact.
Summary
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.BoostedTreesCreateEnsemble` can result in a use after free error if an attacker supplies specially crafted arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/boosted_trees/resource_ops.cc#L55) uses a reference counted resource and decrements the refcount if the initialization fails, as it should. However, when the code was written, the resource was represented as a naked pointer but later refactoring has changed it to be a smart pointer. Thus, when the pointer leaves the scope, a subsequent `free`-ing of the resource occurs, but this fails to take into account that the refcount has already reached 0, thus the resource has been already freed. During this double-free process, members of the resource object are accessed for cleanup but they are invalid as the entire resource has been freed. We have patched the issue in GitHub commit 5ecec9c6fbdbc6be03295685190a45e7eee726ab. 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-m7fm-4jfh-jrg6 |
| — | tensorflow (PyPI) | 2.4.0 to before 2.4.3 | 2.4.3 | Patch available | GHSA-m7fm-4jfh-jrg6 |
| — | tensorflow (PyPI) | 2.5.0 to before 2.5.1 | 2.5.1 | Patch available | GHSA-m7fm-4jfh-jrg6 |
| — | tensorflow-cpu (PyPI) | before 2.3.4 | 2.3.4 | Patch available | GHSA-m7fm-4jfh-jrg6 |
| — | tensorflow-cpu (PyPI) | 2.4.0 to before 2.4.3 | 2.4.3 | Patch available | GHSA-m7fm-4jfh-jrg6 |
| — | tensorflow-cpu (PyPI) | 2.5.0 to before 2.5.1 | 2.5.1 | Patch available | GHSA-m7fm-4jfh-jrg6 |
| — | tensorflow-gpu (PyPI) | before 2.3.4 | 2.3.4 | Patch available | GHSA-m7fm-4jfh-jrg6 |
| — | tensorflow-gpu (PyPI) | 2.4.0 to before 2.4.3 | 2.4.3 | Patch available | GHSA-m7fm-4jfh-jrg6 |
| — | tensorflow-gpu (PyPI) | 2.5.0 to before 2.5.1 | 2.5.1 | Patch available | GHSA-m7fm-4jfh-jrg6 |
- 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-m7fm-4jfh-jrg6
- tensorflow (PyPI) Vendor— Affected 2.4.0 to before 2.4.3 Fixed in 2.4.3 Patch available GHSA-m7fm-4jfh-jrg6
- tensorflow (PyPI) Vendor— Affected 2.5.0 to before 2.5.1 Fixed in 2.5.1 Patch available GHSA-m7fm-4jfh-jrg6
- tensorflow-cpu (PyPI) Vendor— Affected before 2.3.4 Fixed in 2.3.4 Patch available GHSA-m7fm-4jfh-jrg6
- tensorflow-cpu (PyPI) Vendor— Affected 2.4.0 to before 2.4.3 Fixed in 2.4.3 Patch available GHSA-m7fm-4jfh-jrg6
- tensorflow-cpu (PyPI) Vendor— Affected 2.5.0 to before 2.5.1 Fixed in 2.5.1 Patch available GHSA-m7fm-4jfh-jrg6
- tensorflow-gpu (PyPI) Vendor— Affected before 2.3.4 Fixed in 2.3.4 Patch available GHSA-m7fm-4jfh-jrg6
- tensorflow-gpu (PyPI) Vendor— Affected 2.4.0 to before 2.4.3 Fixed in 2.4.3 Patch available GHSA-m7fm-4jfh-jrg6
- tensorflow-gpu (PyPI) Vendor— Affected 2.5.0 to before 2.5.1 Fixed in 2.5.1 Patch available GHSA-m7fm-4jfh-jrg6
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-m7fm-4jfh-jrg6 tensorflow (PyPI) Fixed in 2.3.4 Advisory →
- Fix · GHSA-m7fm-4jfh-jrg6 tensorflow (PyPI) Fixed in 2.4.3 Advisory →
- Fix · GHSA-m7fm-4jfh-jrg6 tensorflow (PyPI) Fixed in 2.5.1 Advisory →
- Fix · GHSA-m7fm-4jfh-jrg6 tensorflow-cpu (PyPI) Fixed in 2.3.4 Advisory →
- Fix · GHSA-m7fm-4jfh-jrg6 tensorflow-cpu (PyPI) Fixed in 2.4.3 Advisory →
- Fix · GHSA-m7fm-4jfh-jrg6 tensorflow-cpu (PyPI) Fixed in 2.5.1 Advisory →
- Fix · GHSA-m7fm-4jfh-jrg6 tensorflow-gpu (PyPI) Fixed in 2.3.4 Advisory →
- Fix · GHSA-m7fm-4jfh-jrg6 tensorflow-gpu (PyPI) Fixed in 2.4.3 Advisory →
- Fix · GHSA-m7fm-4jfh-jrg6 tensorflow-gpu (PyPI) Fixed in 2.5.1 Advisory →
Timeline
- 2026-10-02 Threatist record created from CVE-2021-37652
- 2026-10-03 Alias added: GHSA-m7fm-4jfh-jrg6
References
Advisory 2
Other 4
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-565.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-763.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-274.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-2021-37652 · CVE Program
- CVE-2021-37652 · NVD
- FIRST EPSS
- GHSA-m7fm-4jfh-jrg6 · GitHub Advisory Database · CC BY 4.0
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