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MEDIUM severity

CVE-2020-15192

MEDIUMFix: tensorflow/tensorflow@22e07fb

CVE-2020-15192 is a medium-severity (CVSS 4.3) vulnerability in tensorflow. 1 public exploit reference exists, so weaponization risk is real. O3 Security confirms whether CVE-2020-15192 is actually reachable in your code before you act, and blocks exploitation at runtime until you patch.

Memory leak in Tensorflow

Also known asBIT-tensorflow-2020-15192GHSA-8fxw-76px-3rxvPYSEC-2020-115PYSEC-2020-272PYSEC-2020-307
Published
Sep 25, 2020
Updated
Aug 7, 2026
Affected
6 pkgs
Patched
6 / 6
Exploits
1 known
Exploitation data as of Aug 7, 2026 · OSV.dev, FIRST.org (EPSS)

Real-World Exposure

6 pkgs affected
🐍tensorflow🐍tensorflow🐍tensorflow-cpu🐍tensorflow-cpu🐍tensorflow-gpu🐍tensorflow-gpu

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

In Tensorflow before versions 2.2.1 and 2.3.1, if a user passes a list of strings to dlpack.to_dlpack there is a memory leak following an expected validation failure. The issue occurs because the status argument during validation failures is not properly checked. Since each of the above methods can return an error status, the status value must be checked before continuing. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1.

Affected Packages

6 total 6 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItensorflow2.2.0&&< 2.2.12.2.1
🐍PyPItensorflow2.3.0&&< 2.3.12.3.1
🐍PyPItensorflow-cpu2.2.0&&< 2.2.12.2.1
🐍PyPItensorflow-cpu2.3.0&&< 2.3.12.3.1
🐍PyPItensorflow-gpu2.2.0&&< 2.2.12.2.1
🐍PyPItensorflow-gpu2.3.0&&< 2.3.12.3.1
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. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.

  2. Fix

    Update tensorflow to 2.2.1 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2020-15192 is resolved across your whole dependency graph.

  3. 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.

  4. How O3 protects you

    O3 pinpoints whether CVE-2020-15192 is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.

Tailored to CVE-2020-15192. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

In Tensorflow before versions 2.2.1 and 2.3.1, if a user passes a list of strings to `dlpack.to_dlpack` there is a memory leak following an expected validation failure. The issue occurs because the `status` argument during validation failures is not properly checked. Since each of the above methods can return an error status, the `status` value must be checked before continuing. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1.
O3 Security · Impact-Aware SCA

Is CVE-2020-15192 in your dependencies?

O3 detects CVE-2020-15192 across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.