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HIGH severity

CVE-2022-23574 — tensorflow

HIGHFix: tensorflow/tensorflow@0657c83

CVE-2022-23574 is a high-severity (CVSS 8.8) Out-of-bounds Read 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.

Out of bounds read and write in Tensorflow

Also known asBIT-tensorflow-2022-23574GHSA-77gp-3h4r-6428PYSEC-2022-138PYSEC-2022-83PYSEC-2026-3127
Published
Updated
Affected
9 pkgs
Patched
9 / 9
Exploits
1 known
Exploitation data as of Oct 11, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

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.
  • A successful exploit gives an attacker total control of the affected component, not partial access.

Exploitation and automatability from CISA’s SSVC triage for CVE-2022-23574.

EPSS Exploitation Probability

via FIRST.org ↗
0.8%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs57th percentile — riskier than 57% of all scored CVEsHighest risk
0.00%0.45%0.90%1.34%0.3%0.8%Apr 26Aug 26Oct 26

Probability of exploitation in the next 30 days, from FIRST.org EPSS.

How urgent is this, really

CVE-2022-23574 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

9 pkgs affected
🐍tensorflow🐍tensorflow🐍tensorflow🐍tensorflow-cpu🐍tensorflow-cpu🐍tensorflow-cpu🐍tensorflow-gpu🐍tensorflow-gpu+1 more

Real-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

There is a typo in TensorFlow's SpecializeType which results in heap OOB read/write:

for (int i = 0; i < op_def.output_arg_size(); i++) {
  // ...
  for (int j = 0; j < t->args_size(); j++) {
    auto* arg = t->mutable_args(i);
    // ...
  }
} 

Due to a typo, arg is initialized to the ith mutable argument in a loop where the loop index is j. Hence it is possible to assign to arg from outside the vector of arguments. Since this is a mutable proto value, it allows both read and write to outside of bounds data.

Patches

We have patched the issue in GitHub commit 0657c83d08845cc434175934c642299de2c0f042.

The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, 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.

Affected Packages

9 total 9 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItensorflowall versions2.5.3pip install --upgrade 'tensorflow==2.5.3'
🐍PyPItensorflow≥ 2.6.0&&< 2.6.32.6.3pip install --upgrade 'tensorflow==2.6.3'
🐍PyPItensorflow≥ 2.7.0&&< 2.7.12.7.1pip install --upgrade 'tensorflow==2.7.1'
🐍PyPItensorflow-cpuall versions2.5.3pip install --upgrade 'tensorflow-cpu==2.5.3'
🐍PyPItensorflow-cpu≥ 2.6.0&&< 2.6.32.6.3pip install --upgrade 'tensorflow-cpu==2.6.3'
🐍PyPItensorflow-cpu≥ 2.7.0&&< 2.7.12.7.1pip install --upgrade 'tensorflow-cpu==2.7.1'

Affected Products

1 product · 3 configurations
Application
tensorflowgoogle
≥ 2.6.0 && ≤ 2.6.2
1 version
2.7.0
Exploits & PoCs
1

Research 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 dependency
  1. Detect

    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.

  2. Fix

    Update tensorflow to 2.5.3 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2022-23574 is resolved across your whole dependency graph.

  3. Workarounds

    Constrain what reaches the vulnerable code: limit the size and shape of untrusted input, isolate the affected component in a sandboxed or least-privileged process, and enable the platform's memory-safety mitigations (ASLR, stack protector, hardened allocator) so an out-of-bounds access is more likely to fail closed than to be exploitable.

Frequently Asked Questions

### Impact There is a typo in TensorFlow's [`SpecializeType`](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/full_type_util.cc#L81-L102) which results in heap OOB read/write: ```cc for (int i = 0; i < op_def.output_arg_size(); i++) { // ... for (int j = 0; j < t->args_size(); j++) { auto* arg = t->mutable_args(i); // ... } } ``` Due to a typo, `arg` is initialized to the `i`th mutable argument in a loop where the loop index is `j`. Hence it is possible to assign to `arg` from outside the vector of arguments. Sin
O3 Security · Impact-Aware SCA

Is CVE-2022-23574 in your dependencies?

Find it across PyPI, including transitive dependencies.

CVE-2022-23574: tensorflow — Fixed in 2.5.3