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MEDIUM severity

GHSA-jjr8-m8g8-p6wv

MEDIUMFix: tensorflow/tensorflow@f837892

GHSA-jjr8-m8g8-p6wv is a medium-severity (CVSS 4.4) NULL Pointer Dereference vulnerability in tensorflow. 1 public exploit reference exists, so weaponization risk is real. O3 Security confirms whether GHSA-jjr8-m8g8-p6wv is actually reachable in your code before you act, and blocks exploitation at runtime until you patch.

Null pointer dereference in TFLite's `Reshape` operator

Also known asBIT-tensorflow-2021-29592CVE-2021-29592PYSEC-2021-229PYSEC-2021-520PYSEC-2021-718
Published
May 21, 2021
Updated
Mar 13, 2026
Affected
12 pkgs
Patched
12 / 12
Exploits
1 known
Exploitation data as of Mar 13, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Real-World Exposure

12 pkgs affected
🐍tensorflow🐍tensorflow🐍tensorflow🐍tensorflow🐍tensorflow-cpu🐍tensorflow-cpu🐍tensorflow-cpu🐍tensorflow-cpu+4 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 fix for CVE-2020-15209 missed the case when the target shape of Reshape operator is given by the elements of a 1-D tensor. As such, the fix for the vulnerability allowed passing a null-buffer-backed tensor with a 1D shape:

if (tensor->data.raw == nullptr && tensor->bytes > 0) {
  if (registration.builtin_code == kTfLiteBuiltinReshape && i == 1) {
    // In general, having a tensor here with no buffer will be an error.
    // However, for the reshape operator, the second input tensor is only
    // used for the shape, not for the data. Thus, null buffer is ok.
    continue;
  } else {
    // In all other cases, we need to return an error as otherwise we will
    // trigger a null pointer dereference (likely).
    ReportError("Input tensor %d lacks data", tensor_index);
    return kTfLiteError;
  }
}

Patches

We have patched the issue in GitHub commit f8378920345f4f4604202d4ab15ef64b2aceaa16.

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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.

Attribution

This vulnerability has been reported by members of the Aivul Team from Qihoo 360.

Affected Packages

12 total 12 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItensorflowall versions2.1.4
🐍PyPItensorflow2.2.0&&< 2.2.32.2.3
🐍PyPItensorflow2.3.0&&< 2.3.32.3.3
🐍PyPItensorflow2.4.0&&< 2.4.22.4.2
🐍PyPItensorflow-cpuall versions2.1.4
🐍PyPItensorflow-cpu2.2.0&&< 2.2.32.2.3
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 2.1.4 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-jjr8-m8g8-p6wv 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 GHSA-jjr8-m8g8-p6wv 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 GHSA-jjr8-m8g8-p6wv. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

### Impact The fix for [CVE-2020-15209](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15209) missed the case when the target shape of `Reshape` operator is given by the elements of a 1-D tensor. As such, the [fix for the vulnerability](https://github.com/tensorflow/tensorflow/blob/9c1dc920d8ffb4893d6c9d27d1f039607b326743/tensorflow/lite/core/subgraph.cc#L1062-L1074) allowed passing a null-buffer-backed tensor with a 1D shape: ```cc if (tensor->data.raw == nullptr && tensor->bytes > 0) { if (registration.builtin_code == kTfLiteBuiltinReshape && i == 1) { // In general, having a
O3 Security · Impact-Aware SCA

Is GHSA-jjr8-m8g8-p6wv in your dependencies?

O3 detects GHSA-jjr8-m8g8-p6wv across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.

GHSA-jjr8-m8g8-p6wv: Null pointer… | O3 Security