CVE-2022-23563
HIGHCVE-2022-23563 is a high-severity (CVSS 7.1) CWE-367 vulnerability in tensorflow. O3 Security confirms whether CVE-2022-23563 is actually reachable in your code before you act, and blocks exploitation at runtime until you patch.
Insecure temporary file in Tensorflow
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
CVE-2022-23563 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 0 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🐍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
Tensorflow is an Open Source Machine Learning Framework. In multiple places, TensorFlow uses tempfile.mktemp to create temporary files. While this is acceptable in testing, in utilities and libraries it is dangerous as a different process can create the file between the check for the filename in mktemp and the actual creation of the file by a subsequent operation (a TOC/TOU type of weakness). In several instances, TensorFlow was supposed to actually create a temporary directory instead of a file. This logic bug is hidden away by the mktemp function usage. We have patched the issue in several commits, replacing mktemp with the safer mkstemp/mkdtemp functions, according to the usage pattern. Users are advised to upgrade as soon as possible.
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | tensorflow | all versions | 2.5.3 |
| 🐍PyPI | tensorflow | ≥ 2.6.0&&< 2.6.3 | 2.6.3 |
| 🐍PyPI | tensorflow | ≥ 2.7.0&&< 2.7.1 | 2.7.1 |
| 🐍PyPI | tensorflow-cpu | all versions | 2.5.3 |
| 🐍PyPI | tensorflow-cpu | ≥ 2.6.0&&< 2.6.3 | 2.6.3 |
| 🐍PyPI | tensorflow-cpu | ≥ 2.7.0&&< 2.7.1 | 2.7.1 |
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 2.5.3 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2022-23563 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 CVE-2022-23563 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 CVE-2022-23563. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.
Frequently Asked Questions
Is CVE-2022-23563 in your dependencies?
O3 detects CVE-2022-23563 across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.