CVE-2022-23590 is a medium-severity (CVSS 5.9) CWE-754 vulnerability in tensorflow. 1 public exploit reference exists, so weaponization risk is real. A fix is available for tensorflow — see the affected versions and patch details below.
Crash due to erroneous `StatusOr` in Tensorflow
Exploitation Status
Proof-of-concept exploit code exists
- CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.
Exploitation and automatability from CISA’s SSVC triage for CVE-2022-23590.
EPSS Exploitation Probability
Probability of exploitation in the next 30 days, from FIRST.org EPSS.
How urgent is this, really
CVE-2022-23590 by exploitation likelihood (EPSS) against impact (CVSS). Outside the shaded patch-first corner.
Where this sits among everything scored
Of 385,738 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-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
A GraphDef from a TensorFlow SavedModel can be maliciously altered to cause a TensorFlow process to crash due to encountering a StatusOr value that is an error and forcibly extracting the value from it:
if (op_reg_data->type_ctor != nullptr) {
VLOG(3) << "AddNode: found type constructor for " << node_def.name();
const auto ctor_type =
full_type::SpecializeType(AttrSlice(node_def), op_reg_data->op_def);
const FullTypeDef ctor_typedef = ctor_type.ValueOrDie();
if (ctor_typedef.type_id() != TFT_UNSET) {
*(node_def.mutable_experimental_type()) = ctor_typedef;
}
}
If ctor_type is an error status, ValueOrDie results in a crash.
Patches
We have patched the issue in GitHub commit 955059813cc325dc1db5e2daa6221271406d4439.
We have patched the issue in multiple GitHub commits and these will be included in TensorFlow 2.8.0 and TensorFlow 2.7.1, as both are affected.
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 | 2.7.1pip install --upgrade 'tensorflow==2.7.1' |
| 🐍PyPI | tensorflow-cpu | all versions | 2.7.1pip install --upgrade 'tensorflow-cpu==2.7.1' |
| 🐍PyPI | tensorflow-gpu | all versions | 2.7.1pip install --upgrade 'tensorflow-gpu==2.7.1' |
Affected Products
tensorflowgoogleResearch use only. For defensive security, authorized penetration testing, and academic research only. Never execute exploit code against systems without explicit written authorization.
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 2.7.1 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2022-23590 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.
Frequently Asked Questions
Is CVE-2022-23590 in your dependencies?
Find it across PyPI, including transitive dependencies.