Interpreter crash from `tf.io.decode_raw`
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 · NVD. Fix status from CNA and GitHub. Impact type from CWE-787 and the CVSS impact.
Summary
TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.io.decode_raw` produces incorrect results and crashes the Python interpreter when combining `fixed_length` and wider datatypes. The implementation of the padded version(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc) is buggy due to a confusion about pointer arithmetic rules. First, the code computes(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L61) the width of each output element by dividing the `fixed_length` value to the size of the type argument. The `fixed_length` argument is also used to determine the size needed for the output tensor(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L63-L79). This is followed by reencoding code(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L85-L94). The erroneous code is the last line above: it is moving the `out_data` pointer by `fixed_length * sizeof(T)` bytes whereas it only copied at most `fixed_length` bytes from the input. This results in parts of the input not being decoded into the output. Furthermore, because the pointer advance is far wider than desired, this quickly leads to writing to outside the bounds of the backing data. This OOB write leads to interpreter crash in the reproducer mentioned here, but more severe attacks can be mounted too, given that this gadget allows writing to periodically placed locations in memory. 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-8pmx-p244-g88h |
| — | tensorflow (PyPI) | 2.2.0 to before 2.2.3 | 2.2.3 | Patch available | GHSA-8pmx-p244-g88h |
| — | tensorflow (PyPI) | 2.3.0 to before 2.3.3 | 2.3.3 | Patch available | GHSA-8pmx-p244-g88h |
| — | tensorflow (PyPI) | 2.4.0 to before 2.4.2 | 2.4.2 | Patch available | GHSA-8pmx-p244-g88h |
| — | tensorflow-cpu (PyPI) | before 2.1.4 | 2.1.4 | Patch available | GHSA-8pmx-p244-g88h |
| — | tensorflow-cpu (PyPI) | 2.2.0 to before 2.2.3 | 2.2.3 | Patch available | GHSA-8pmx-p244-g88h |
| — | tensorflow-cpu (PyPI) | 2.3.0 to before 2.3.3 | 2.3.3 | Patch available | GHSA-8pmx-p244-g88h |
| — | tensorflow-cpu (PyPI) | 2.4.0 to before 2.4.2 | 2.4.2 | Patch available | GHSA-8pmx-p244-g88h |
| — | tensorflow-gpu (PyPI) | before 2.1.4 | 2.1.4 | Patch available | GHSA-8pmx-p244-g88h |
| — | tensorflow-gpu (PyPI) | 2.2.0 to before 2.2.3 | 2.2.3 | Patch available | GHSA-8pmx-p244-g88h |
| — | tensorflow-gpu (PyPI) | 2.3.0 to before 2.3.3 | 2.3.3 | Patch available | GHSA-8pmx-p244-g88h |
| — | tensorflow-gpu (PyPI) | 2.4.0 to before 2.4.2 | 2.4.2 | Patch available | GHSA-8pmx-p244-g88h |
- 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-8pmx-p244-g88h
- tensorflow (PyPI) Vendor— Affected 2.2.0 to before 2.2.3 Fixed in 2.2.3 Patch available GHSA-8pmx-p244-g88h
- tensorflow (PyPI) Vendor— Affected 2.3.0 to before 2.3.3 Fixed in 2.3.3 Patch available GHSA-8pmx-p244-g88h
- tensorflow (PyPI) Vendor— Affected 2.4.0 to before 2.4.2 Fixed in 2.4.2 Patch available GHSA-8pmx-p244-g88h
- tensorflow-cpu (PyPI) Vendor— Affected before 2.1.4 Fixed in 2.1.4 Patch available GHSA-8pmx-p244-g88h
- tensorflow-cpu (PyPI) Vendor— Affected 2.2.0 to before 2.2.3 Fixed in 2.2.3 Patch available GHSA-8pmx-p244-g88h
- tensorflow-cpu (PyPI) Vendor— Affected 2.3.0 to before 2.3.3 Fixed in 2.3.3 Patch available GHSA-8pmx-p244-g88h
- tensorflow-cpu (PyPI) Vendor— Affected 2.4.0 to before 2.4.2 Fixed in 2.4.2 Patch available GHSA-8pmx-p244-g88h
- tensorflow-gpu (PyPI) Vendor— Affected before 2.1.4 Fixed in 2.1.4 Patch available GHSA-8pmx-p244-g88h
- tensorflow-gpu (PyPI) Vendor— Affected 2.2.0 to before 2.2.3 Fixed in 2.2.3 Patch available GHSA-8pmx-p244-g88h
- tensorflow-gpu (PyPI) Vendor— Affected 2.3.0 to before 2.3.3 Fixed in 2.3.3 Patch available GHSA-8pmx-p244-g88h
- tensorflow-gpu (PyPI) Vendor— Affected 2.4.0 to before 2.4.2 Fixed in 2.4.2 Patch available GHSA-8pmx-p244-g88h
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-8pmx-p244-g88h tensorflow (PyPI) Fixed in 2.1.4 Advisory →
- Fix · GHSA-8pmx-p244-g88h tensorflow (PyPI) Fixed in 2.2.3 Advisory →
- Fix · GHSA-8pmx-p244-g88h tensorflow (PyPI) Fixed in 2.3.3 Advisory →
- Fix · GHSA-8pmx-p244-g88h tensorflow (PyPI) Fixed in 2.4.2 Advisory →
- Fix · GHSA-8pmx-p244-g88h tensorflow-cpu (PyPI) Fixed in 2.1.4 Advisory →
- Fix · GHSA-8pmx-p244-g88h tensorflow-cpu (PyPI) Fixed in 2.2.3 Advisory →
- Fix · GHSA-8pmx-p244-g88h tensorflow-cpu (PyPI) Fixed in 2.3.3 Advisory →
- Fix · GHSA-8pmx-p244-g88h tensorflow-cpu (PyPI) Fixed in 2.4.2 Advisory →
- Fix · GHSA-8pmx-p244-g88h tensorflow-gpu (PyPI) Fixed in 2.1.4 Advisory →
- Fix · GHSA-8pmx-p244-g88h tensorflow-gpu (PyPI) Fixed in 2.2.3 Advisory →
- Fix · GHSA-8pmx-p244-g88h tensorflow-gpu (PyPI) Fixed in 2.3.3 Advisory →
- Fix · GHSA-8pmx-p244-g88h tensorflow-gpu (PyPI) Fixed in 2.4.2 Advisory →
Timeline
- 2026-10-02 Threatist record created from CVE-2021-29614
- 2026-10-03 Alias added: GHSA-8pmx-p244-g88h
References
Other 4
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-542.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-740.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-251.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-2021-29614 · CVE Program
- CVE-2021-29614 · NVD
- FIRST EPSS
- GHSA-8pmx-p244-g88h · GitHub Advisory Database · CC BY 4.0
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