The code behind tf.function
API can be made to deadlock when two tf.function
decorated Python functions are mutually recursive:
import tensorflow as tf
@tf.function()
def fun1(num):
if num == 1:
return
print(num)
fun2(num-1)
@tf.function()
def fun2(num):
if num == 0:
return
print(num)
fun1(num-1)
fun1(9)
This occurs due to using a non-reentrant Lock
Python object.
Loading any model which contains mutually recursive functions is vulnerable. An attacker can cause denial of service by causing users to load such models and calling a recursive tf.function
, although this is not a frequent scenario.
We have patched the issue in GitHub commit afac8158d43691661ad083f6dd9e56f327c1dcb7.
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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 members of the Aivul Team from Qihoo 360.
{ "nvd_published_at": "2021-11-05T23:15:00Z", "cwe_ids": [ "CWE-662", "CWE-667" ], "severity": "MODERATE", "github_reviewed": true, "github_reviewed_at": "2021-11-08T22:25:35Z" }