CVE-2021-41213 is a medium-severity (CVSS 5.5) CWE-667 vulnerability in tensorflow. A fix is available for tensorflow — see the affected versions and patch details below.
Deadlock in mutually recursive `tf.function` objects
EPSS Exploitation Probability
Probability of exploitation in the next 30 days, from FIRST.org EPSS.
How urgent is this, really
Where this sits among everything scored
Real-World Exposure
tensorflow🐍tensorflow🐍tensorflow🐍tensorflow-cpu🐍tensorflow-cpu🐍tensorflow-cpu🐍tensorflow-gpu🐍tensorflow-gpu+1 moreReal-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.
Description
Impact
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.
Patches
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.
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 members of the Aivul Team from Qihoo 360.
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | tensorflow | ≥ 2.6.0&&< 2.6.1 | 2.6.1pip install --upgrade 'tensorflow==2.6.1' |
| 🐍PyPI | tensorflow | ≥ 2.5.0&&< 2.5.2 | 2.5.2pip install --upgrade 'tensorflow==2.5.2' |
| 🐍PyPI | tensorflow | all versions | 2.4.4pip install --upgrade 'tensorflow==2.4.4' |
| 🐍PyPI | tensorflow-cpu | ≥ 2.6.0&&< 2.6.1 | 2.6.1pip install --upgrade 'tensorflow-cpu==2.6.1' |
| 🐍PyPI | tensorflow-cpu | ≥ 2.5.0&&< 2.5.2 | 2.5.2pip install --upgrade 'tensorflow-cpu==2.5.2' |
| 🐍PyPI | tensorflow-cpu | all versions | 2.4.4pip install --upgrade 'tensorflow-cpu==2.4.4' |
Affected Products
tensorflowgoogleDetection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for tensorflow, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update tensorflow to 2.6.1 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2021-41213 is resolved across your whole dependency graph.
Workarounds
Cap what an attacker can consume: apply request size, rate and timeout limits in front of the affected component, and run it with memory and CPU limits so exhaustion degrades one worker rather than the whole service.
Frequently Asked Questions
Is CVE-2021-41213 in your dependencies?
Find it across PyPI, including transitive dependencies.