GHSA-w74j-v8xh-3w5h is a high-severity (CVSS 7.8) CWE-824 vulnerability in tensorflow. O3 Security confirms whether GHSA-w74j-v8xh-3w5h is actually reachable in your code before you act, and blocks exploitation at runtime until you patch.
Reference binding to nullptr in unicode encoding
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 cause undefined behavior via binding a reference to null pointer in tf.raw_ops.UnicodeEncode:
import tensorflow as tf
from tensorflow.python.ops import gen_string_ops
gen_string_ops.unicode_encode(
input_values=[],
input_splits=[],
output_encoding='UTF-8',
errors='ignore',
replacement_char='a')
The implementation reads the first dimension of the input_splits tensor before validating that this tensor is not empty:
const Tensor& input_splits = context->input(1);
const auto input_splits_flat = input_splits.flat<SPLITS_TYPE>();
TensorShape output_shape({input_splits.dim_size(0) - 1});
Patches
We have patched the issue in GitHub commit 2e0ee46f1a47675152d3d865797a18358881d7a6.
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 | 2.3.4 |
| 🐍PyPI | tensorflow | ≥ 2.4.0&&< 2.4.3 | 2.4.3 |
| 🐍PyPI | tensorflow | ≥ 2.5.0&&< 2.5.1 | 2.5.1 |
| 🐍PyPI | tensorflow-cpu | all versions | 2.3.4 |
| 🐍PyPI | tensorflow-cpu | ≥ 2.4.0&&< 2.4.3 | 2.4.3 |
| 🐍PyPI | tensorflow-cpu | ≥ 2.5.0&&< 2.5.1 | 2.5.1 |
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for tensorflow. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.
Fix
Update tensorflow to 2.3.4 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-w74j-v8xh-3w5h 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.
How O3 protects you
O3 pinpoints whether GHSA-w74j-v8xh-3w5h is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.
Tailored to GHSA-w74j-v8xh-3w5h. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.
Frequently Asked Questions
Is GHSA-w74j-v8xh-3w5h in your dependencies?
O3 detects GHSA-w74j-v8xh-3w5h across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.