GHSA-7fvx-3jfc-2cpc is a high-severity (CVSS 7.3) Out-of-bounds Read 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-7fvx-3jfc-2cpc by exploitation likelihood (EPSS) against impact (CVSS). Outside the shaded patch-first corner.
Where this sits among everything scored
Of 385,386 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
An attacker can trigger a read from outside of bounds of heap allocated data by sending invalid arguments to tf.raw_ops.ResourceScatterUpdate:
import tensorflow as tf
v = tf.Variable([b'vvv'])
tf.raw_ops.ResourceScatterUpdate(
resource=v.handle,
indices=[0],
updates=['1', '2', '3', '4', '5'])
The implementation has an incomplete validation of the relationship between the shapes of indices and updates: instead of checking that the shape of indices is a prefix of the shape of updates (so that broadcasting can happen), code only checks that the number of elements in these two tensors are in a divisibility relationship.
Patches
We have patched the issue in GitHub commit 01cff3f986259d661103412a20745928c727326f.
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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 | all versions | 2.3.4pip install --upgrade 'tensorflow==2.3.4' |
| 🐍PyPI | tensorflow | ≥ 2.4.0&&< 2.4.3 | 2.4.3pip install --upgrade 'tensorflow==2.4.3' |
| 🐍PyPI | tensorflow | ≥ 2.5.0&&< 2.5.1 | 2.5.1pip install --upgrade 'tensorflow==2.5.1' |
| 🐍PyPI | tensorflow-cpu | all versions | 2.3.4pip install --upgrade 'tensorflow-cpu==2.3.4' |
| 🐍PyPI | tensorflow-cpu | ≥ 2.4.0&&< 2.4.3 | 2.4.3pip install --upgrade 'tensorflow-cpu==2.4.3' |
| 🐍PyPI | tensorflow-cpu | ≥ 2.5.0&&< 2.5.1 | 2.5.1pip install --upgrade 'tensorflow-cpu==2.5.1' |
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 2.3.4 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-7fvx-3jfc-2cpc is resolved across your whole dependency graph.
Workarounds
Constrain what reaches the vulnerable code: limit the size and shape of untrusted input, isolate the affected component in a sandboxed or least-privileged process, and enable the platform's memory-safety mitigations (ASLR, stack protector, hardened allocator) so an out-of-bounds access is more likely to fail closed than to be exploitable.
Frequently Asked Questions
Is GHSA-7fvx-3jfc-2cpc in your dependencies?
Find it across PyPI, including transitive dependencies.