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CRITICAL severity

CVE-2020-15207 — tensorflow

CRITICALFix: tensorflow/tensorflow@2d88f47

CVE-2020-15207 is a critical-severity (CVSS 9) 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.

Segfault and data corruption in tensorflow-lite

Also known asBIT-tensorflow-2020-15207GHSA-q4qf-3fc6-8x34PYSEC-2020-130PYSEC-2020-287PYSEC-2020-322
Published
Updated
Affected
15 pkgs
Patched
15 / 15
Exploits
1 known
Exploitation data as of Oct 9, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

EPSS Exploitation Probability

via FIRST.org ↗
1.2%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs68th percentile — riskier than 68% of all scored CVEsHighest risk
0.73%1.12%1.52%1.91%1.4%1.2%Apr 26Aug 26Oct 26

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

How urgent is this, really

CVE-2020-15207 by exploitation likelihood (EPSS) against impact (CVSS). Outside the shaded patch-first corner.

Where this sits among everything scored

Of 385,987 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

To mimic Python's indexing with negative values, TFLite uses ResolveAxis to convert negative values to positive indices. However, the only check that the converted index is now valid is only present in debug builds: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/internal/reference/reduce.h#L68-L72

If the DCHECK does not trigger, then code execution moves ahead with a negative index. This, in turn, results in accessing data out of bounds which results in segfaults and/or data corruption.

Patches

We have patched the issue in 2d88f470dea2671b430884260f3626b1fe99830a and will release patch releases for all versions between 1.15 and 2.3.

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-2020-15207 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 To mimic Python's indexing with negative values, TFLite uses `ResolveAxis` to convert negative values to positive indices. However, the only check that the converted index is now valid is only present in debug builds: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/internal/reference/reduce.h#L68-L72 If the `DCHECK` does not trigger, then code execution moves ahead with a negative index. This, in turn, results in accessing data out of bounds which results in segfaults and/or data corruption. ### Patches We have patched
O3 Security · Impact-Aware SCA

Is CVE-2020-15207 in your dependencies?

Find it across PyPI, including transitive dependencies.

CVE-2020-15207: tensorflow — Fixed in 1.15.4