CVE-2021-41213: Deadlock in mutually recursive `tf.function` objects
(updated )
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.
References
- github.com/advisories/GHSA-h67m-xg8f-fxcf
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-622.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-820.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-405.yaml
- github.com/tensorflow/tensorflow
- github.com/tensorflow/tensorflow/commit/afac8158d43691661ad083f6dd9e56f327c1dcb7
- github.com/tensorflow/tensorflow/security/advisories/GHSA-h67m-xg8f-fxcf
- nvd.nist.gov/vuln/detail/CVE-2021-41213
Code Behaviors & Features
Detect and mitigate CVE-2021-41213 with GitLab Dependency Scanning
Secure your software supply chain by verifying that all open source dependencies used in your projects contain no disclosed vulnerabilities. Dependency Scanning using SBOM also detects vulnerabilities from proprietary advisories that this site does not include. Learn more about Dependency Scanning using SBOM →