GHSA-frqp-wp83-qggv is a medium-severity (CVSS 4.8) Out-of-bounds Read vulnerability in tensorflow. O3 Security confirms whether GHSA-frqp-wp83-qggv is actually reachable in your code before you act, and blocks exploitation at runtime until you patch.
Heap overflow in `QuantizeAndDequantizeV2`
Real-World Exposure
tensorflow🐍tensorflow🐍tensorflow🐍tensorflow-cpu🐍tensorflow-gpu🐍tensorflow-cpu🐍tensorflow-gpu🐍tensorflow-cpu+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 function MakeGrapplerFunctionItem takes arguments that determine the sizes of inputs and outputs. If the inputs given are greater than or equal to the sizes of the outputs, an out-of-bounds memory read or a crash is triggered.
import tensorflow as tf
@tf.function
def test():
tf.raw_ops.QuantizeAndDequantizeV2(input=[2.5],
input_min=[1.0],
input_max=[10.0],
signed_input=True,
num_bits=1,
range_given=True,
round_mode='HALF_TO_EVEN',
narrow_range=True,
axis=0x7fffffff)
test()
Patches
We have patched the issue in GitHub commit 7b174a0f2e40ff3f3aa957aecddfd5aaae35eccb.
The fix will be included in TensorFlow 2.11.0. We will also cherrypick this commit on TensorFlow 2.10.1.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | tensorflow | all versions | 2.8.4 |
| 🐍PyPI | tensorflow | ≥ 2.9.0&&< 2.9.3 | 2.9.3 |
| 🐍PyPI | tensorflow | ≥ 2.10.0&&< 2.10.1 | 2.10.1 |
| 🐍PyPI | tensorflow-cpu | all versions | 2.8.4 |
| 🐍PyPI | tensorflow-gpu | all versions | 2.8.4 |
| 🐍PyPI | tensorflow-cpu | ≥ 2.9.0&&< 2.9.3 | 2.9.3 |
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 2.8.4 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-frqp-wp83-qggv 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-frqp-wp83-qggv 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-frqp-wp83-qggv. 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-frqp-wp83-qggv in your dependencies?
O3 detects GHSA-frqp-wp83-qggv across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.