GHSA-gjh7-xx4r-x345 is a high-severity (CVSS 7.5) CWE-190 vulnerability in tensorflow. A fix is available for tensorflow — see the affected versions and patch details below.
TensorFlow has segfault in array_ops.upper_bound
Exploitation Status
No confirmed exploitation observed yet
- CISA’s own triage has not observed active exploitation or public proof-of-concept code for this CVE as of its last assessment.
Exploitation and automatability from CISA’s SSVC triage for GHSA-gjh7-xx4r-x345.
EPSS Exploitation Probability
EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.
How urgent is this, really
GHSA-gjh7-xx4r-x345 plotted by exploitation likelihood (EPSS) against impact (CVSS). The shaded corner — EPSS 50%+ and CVSS 7.0+ — is where this CVE doesn't sit, though severity or exploitability alone can still warrant action.
Where this sits among everything scored
Of 378,567 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Real counts from FIRST.org, not a sample — log-scaled since the landscape is heavily right-skewed.
Real-World Exposure
tensorflow🐍tensorflow-cpu🐍tensorflow-gpuReal-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
array_ops.upper_bound causes a segfault when not given a rank 2 tensor.
Patches
We have patched the issue in GitHub commit 915884fdf5df34aaedd00fc6ace33a2cfdefa586.
The fix will be included in TensorFlow 2.13. We will also cherrypick this commit in TensorFlow 2.12.1.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Attribution
This vulnerability has been reported by dmc1778
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | tensorflow | all versions | 2.12.1pip install --upgrade 'tensorflow==2.12.1' |
| 🐍PyPI | tensorflow-cpu | all versions | 2.12.1pip install --upgrade 'tensorflow-cpu==2.12.1' |
| 🐍PyPI | tensorflow-gpu | all versions | 2.12.1pip install --upgrade 'tensorflow-gpu==2.12.1' |
Detection & 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 2.12.1 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-gjh7-xx4r-x345 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 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like GHSA-gjh7-xx4r-x345 can be triaged on real exposure rather than presence alone.
Tailored to GHSA-gjh7-xx4r-x345. 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-gjh7-xx4r-x345 in your dependencies?
O3 Security finds GHSA-gjh7-xx4r-x345 across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.