CVE-2021-29579Low· 2.5▾ SunlitHeap buffer overflow in `MaxPoolGrad`
▾ Sunlit zone — Low / medium · no exploitation signal
impact 13.8 · likelihood 0 · exploitation 0
Need a working PoC? Pro members can cast a request and our team develops one — it lands right here.
Exploit-prediction probability, daily snapshots since Jul 8.
Disclosure to exploitation, from the record and what we observed since indexing it.
Disclosed via OSV
Last analysed / modified upstream
0.2%
The implementation of tf.raw_ops.MaxPoolGrad is vulnerable to a heap buffer overflow:
import tensorflow as tf
orig_input = tf.constant([0.0], shape=[1, 1, 1, 1], dtype=tf.float32)
orig_output = tf.constant([0.0], shape=[1, 1, 1, 1], dtype=tf.float32)
grad = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.float32)
ksize = [1, 1, 1, 1]
strides = [1, 1, 1, 1]
padding = "SAME"
tf.raw_ops.MaxPoolGrad(
orig_input=orig_input, orig_output=orig_output, grad=grad, ksize=ksize,
strides=strides, padding=padding, explicit_paddings=[])
The implementation fails to validate that indices used to access elements of input/output arrays are valid:
for (int index = out_start; index < out_end; ++index) {
int input_backprop_index = out_arg_max_flat(index);
FastBoundsCheck(input_backprop_index - in_start, in_end - in_start);
input_backprop_flat(input_backprop_index) += out_backprop_flat(index);
}
Whereas accesses to input_backprop_flat are guarded by FastBoundsCheck, the indexing in out_backprop_flat can result in OOB access.
We have patched the issue in GitHub commit a74768f8e4efbda4def9f16ee7e13cf3922ac5f7.
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.
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
This vulnerability has been reported by Ying Wang and Yakun Zhang of Baidu X-Team.
tensorflow < 2.1.4tensorflow >= 2.2.0, < 2.2.3tensorflow >= 2.3.0, < 2.3.3tensorflow >= 2.4.0, < 2.4.2tensorflow-cpu < 2.1.4tensorflow-cpu >= 2.2.0, < 2.2.3tensorflow-cpu >= 2.3.0, < 2.3.3tensorflow-cpu >= 2.4.0, < 2.4.2tensorflow-gpu < 2.1.4tensorflow-gpu >= 2.2.0, < 2.2.3tensorflow-gpu >= 2.3.0, < 2.3.3tensorflow-gpu >= 2.4.0, < 2.4.2Upgrade to a patched release:
tensorflow 2.1.4tensorflow 2.2.3tensorflow 2.3.3tensorflow 2.4.2tensorflow-cpu 2.1.4tensorflow-cpu 2.2.3tensorflow-cpu 2.3.3tensorflow-cpu 2.4.2tensorflow-gpu 2.1.4tensorflow-gpu 2.2.3tensorflow-gpu 2.3.3tensorflow-gpu 2.4.2Connected by shared product, vendor, weakness, or advisory.
CVE-2021-29541Low· 2.5Null pointer dereference in `StringNGrams`
CVE-2021-29525Low· 2.5Division by 0 in `Conv2DBackpropInput`
CVE-2021-29527Low· 2.5Division by 0 in `QuantizedConv2D`
CVE-2021-29524Low· 2.5Division by 0 in `Conv2DBackpropFilter`
CVE-2020-15207High· 8.7Segfault and data corruption in tensorflow-lite
CVE-2021-29535Low· 2.5Heap buffer overflow in `QuantizedMul`