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HIGH severity

CVE-2020-15195 — tensorflow

HIGHFix: tensorflow/tensorflow@390611e

CVE-2020-15195 is a high-severity (CVSS 8.8) Buffer Overflow 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.

Heap buffer overflow in Tensorflow

Also known asBIT-tensorflow-2020-15195GHSA-63xm-rx5p-xvqrPYSEC-2020-118PYSEC-2020-275PYSEC-2020-310
Published
Updated
Affected
15 pkgs
Patched
15 / 15
Exploits
1 known
Exploitation data as of Oct 10, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

EPSS Exploitation Probability

via FIRST.org ↗
0.9%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs60th percentile — riskier than 60% of all scored CVEsHighest risk
0.00%0.48%0.97%1.45%0.4%0.9%Apr 26Aug 26Oct 26

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

How urgent is this, really

CVE-2020-15195 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

The implementation of SparseFillEmptyRowsGrad uses a double indexing pattern: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/sparse_fill_empty_rows_op.cc#L263-L269

It is possible for reverse_index_map(i) to be an index outside of bounds of grad_values, thus resulting in a heap buffer overflow.

Patches

We have patched the issue in 390611e0d45c5793c7066110af37c8514e6a6c54 and will release a patch release for all affected versions.

We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

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 members of the Aivul Team from Qihoo 360.

Affected Packages

15 total 15 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItensorflowall versions1.15.4pip install --upgrade 'tensorflow==1.15.4'
🐍PyPItensorflow≥ 2.0.0&&< 2.0.32.0.3pip install --upgrade 'tensorflow==2.0.3'
🐍PyPItensorflow≥ 2.1.0&&< 2.1.22.1.2pip install --upgrade 'tensorflow==2.1.2'
🐍PyPItensorflow≥ 2.2.0&&< 2.2.12.2.1pip install --upgrade 'tensorflow==2.2.1'
🐍PyPItensorflow≥ 2.3.0&&< 2.3.12.3.1pip install --upgrade 'tensorflow==2.3.1'
🐍PyPItensorflow-cpuall versions1.15.4pip install --upgrade 'tensorflow-cpu==1.15.4'

Affected Products

2 products · 6 configurations
Application
tensorflowgoogle
≥ 2.3.0 && < 2.3.1
range
OS
leapopensuse
1 version
15.2
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 1.15.4 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2020-15195 is resolved across your whole dependency graph.

  3. Workarounds

    Stop feeding it untrusted input: reject or quarantine files and payloads from unverified sources until you can upgrade, restrict accepted formats to the ones you actually need, and run the parsing or decoding step in a least-privileged sandbox or short-lived worker so a crash or corrupted read cannot reach the rest of the process.

Frequently Asked Questions

### Impact The implementation of `SparseFillEmptyRowsGrad` uses a double indexing pattern: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/sparse_fill_empty_rows_op.cc#L263-L269 It is possible for `reverse_index_map(i)` to be an index outside of bounds of `grad_values`, thus resulting in a heap buffer overflow. ### Patches We have patched the issue in 390611e0d45c5793c7066110af37c8514e6a6c54 and will release a patch release for all affected versions. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3
O3 Security · Impact-Aware SCA

Is CVE-2020-15195 in your dependencies?

Find it across PyPI, including transitive dependencies.

CVE-2020-15195: tensorflow — Fixed in 1.15.4