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MEDIUM severity

CHECK-fail in LSTM with zero-length input in TensorFlowGHSA-m648-33qf-v3gp

MEDIUMFix: tensorflow/tensorflow@1475541

GHSA-m648-33qf-v3gp is a medium-severity (CVSS 4.4) Improper Input Validation vulnerability in tensorflow. A fix is available for tensorflow — see the affected versions and patch details below.

Also known asBIT-tensorflow-2020-26270CVE-2020-26270PYSEC-2020-256PYSEC-2020-301PYSEC-2020-336
Published
Updated
Affected
15 pkgs
Patched
15 / 15
Exploits
None indexed
Exploitation data as of Oct 12, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

EPSS Exploitation Probability

via FIRST.org ↗
0.2%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs6th percentile — riskier than 6% of all scored CVEsHighest risk
0.00%0.22%0.45%0.67%0.0%0.2%Apr 26Aug 26Oct 26

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

How urgent is this, really

GHSA-m648-33qf-v3gp 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

15 pkgs affected
🐍tensorflow🐍tensorflow🐍tensorflow🐍tensorflow🐍tensorflow🐍tensorflow-cpu🐍tensorflow-cpu🐍tensorflow-cpu+7 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

Running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend.

This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer.

Patches

We have patched the issue in GitHub commit 14755416e364f17fb1870882fa778c7fec7f16e3 and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.

Since this issue also impacts TF versions before 2.4, we will patch all releases between 1.15 and 2.3 inclusive.

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

15 total 15 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItensorflowall versions1.15.5pip install --upgrade 'tensorflow==1.15.5'
🐍PyPItensorflow≥ 2.0.0&&< 2.0.42.0.4pip install --upgrade 'tensorflow==2.0.4'
🐍PyPItensorflow≥ 2.1.0&&< 2.1.32.1.3pip install --upgrade 'tensorflow==2.1.3'
🐍PyPItensorflow≥ 2.2.0&&< 2.2.22.2.2pip install --upgrade 'tensorflow==2.2.2'
🐍PyPItensorflow≥ 2.3.0&&< 2.3.22.3.2pip install --upgrade 'tensorflow==2.3.2'
🐍PyPItensorflow-cpuall versions1.15.5pip install --upgrade 'tensorflow-cpu==1.15.5'

Affected Products

1 product · 5 configurations
Application
tensorflowgoogle
≥ 2.3.0 && < 2.3.2
range

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 1.15.5 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-m648-33qf-v3gp is resolved across your whole dependency graph.

  3. Workarounds

    Cap what an attacker can consume: apply request size, rate and timeout limits in front of the affected component, and run it with memory and CPU limits so exhaustion degrades one worker rather than the whole service.

Frequently Asked Questions

### Impact Running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a `CHECK` failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer. ### Patches We have patched the issue in GitHub commit [14755416e364f17fb1870882fa778c7fec7f16e3](https://github.com/tensorflow/tensorflow/commit/14755416e364f17fb1870882fa778c7fec7f16e3) and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.
O3 Security · Impact-Aware SCA

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CHECK-fail in LSTM with zero-length input in TensorFlow