CVE-2021-37686 is a medium-severity (CVSS 5.5) CWE-835 vulnerability in tensorflow. A fix is available for tensorflow — see the affected versions and patch details below.
Infinite loop in TFLite
EPSS Exploitation Probability
Probability of exploitation in the next 30 days, from FIRST.org EPSS.
How urgent is this, really
CVE-2021-37686 by exploitation likelihood (EPSS) against impact (CVSS). Outside the shaded patch-first corner.
Where this sits among everything scored
Of 385,386 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Counts from FIRST.org, log-scaled.
Real-World Exposure
tensorflow🐍tensorflow-cpu🐍tensorflow-gpuReal-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 strided slice implementation in TFLite has a logic bug which can allow an attacker to trigger an infinite loop. This arises from newly introduced support for ellipsis in axis definition:
for (int i = 0; i < effective_dims;) {
if ((1 << i) & op_context->params->ellipsis_mask) {
// ...
int ellipsis_end_idx =
std::min(i + 1 + num_add_axis + op_context->input_dims - begin_count,
effective_dims);
// ...
for (; i < ellipsis_end_idx; ++i) {
// ...
}
continue;
}
// ...
++i;
}
An attacker can craft a model such that ellipsis_end_idx is smaller than i (e.g., always negative). In this case, the inner loop does not increase i and the continue statement causes execution to skip over the preincrement at the end of the outer loop.
Patches
We have patched the issue in GitHub commit dfa22b348b70bb89d6d6ec0ff53973bacb4f4695.
The fix will be included in TensorFlow 2.6.0. This is the only affected version.
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
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | tensorflow | ≥ 2.6.0rc0&&< 2.6.0rc2 | 2.6.0rc2pip install --upgrade 'tensorflow==2.6.0rc2' |
| 🐍PyPI | tensorflow-cpu | ≥ 2.6.0rc0&&< 2.6.0rc2 | 2.6.0rc2pip install --upgrade 'tensorflow-cpu==2.6.0rc2' |
| 🐍PyPI | tensorflow-gpu | ≥ 2.6.0rc0&&< 2.6.0rc2 | 2.6.0rc2pip install --upgrade 'tensorflow-gpu==2.6.0rc2' |
Affected Products
tensorflowgoogleDetection & mitigation playbook
Open-source dependencyDetect
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.
Fix
Update tensorflow to 2.6.0rc2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2021-37686 is resolved across your whole dependency graph.
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
Is CVE-2021-37686 in your dependencies?
Find it across PyPI, including transitive dependencies.