GHSA-7v94-64hj-m82h is a medium-severity (CVSS 5.5) CWE-369 vulnerability in tensorflow. A fix is available for tensorflow — see the affected versions and patch details below.
EPSS Exploitation Probability
Probability of exploitation in the next 30 days, from FIRST.org EPSS.
How urgent is this, really
GHSA-7v94-64hj-m82h by exploitation likelihood (EPSS) against impact (CVSS). Outside the shaded patch-first corner.
Where this sits among everything scored
Of 385,738 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Counts from FIRST.org, log-scaled.
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 implementation of ParallelConcat misses some input validation and can produce a division by 0:
import tensorflow as tf
@tf.function
def test():
y = tf.raw_ops.ParallelConcat(values=[['tf']],shape=0)
return y
test()
Patches
We have patched the issue in GitHub commit f2c3931113eaafe9ef558faaddd48e00a6606235.
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 | all versions | 2.4.4pip install --upgrade 'tensorflow-cpu==2.4.4' |
| 🐍PyPI | tensorflow-cpu | ≥ 2.5.0&&< 2.5.2 | 2.5.2pip install --upgrade 'tensorflow-cpu==2.5.2' |
| 🐍PyPI | tensorflow-cpu | ≥ 2.6.0&&< 2.6.1 | 2.6.1pip install --upgrade 'tensorflow-cpu==2.6.1' |
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 GHSA-7v94-64hj-m82h is resolved across your whole dependency graph.
Workarounds
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.
Frequently Asked Questions
Is GHSA-7v94-64hj-m82h in your dependencies?
Find it across PyPI, including transitive dependencies.