# CVE-2021-37686: Infinite loop in TensorFlow Lite

> An attacker can cause a denial of service via an infinite loop in TensorFlow Lite by crafting a malicious model with specific strided slice parameters.

- **Severity:** Medium 5.5 (`CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H`)
- **Exploited in the wild:** Not known
- **Login needed:** Any signed-in user
- **Attackable:** Local or same network only
- **Victim action needed:** Not needed
- **Fix available:** Yes
- **Published:** 12 Aug 2021
- **Updated:** 13 Nov 2024
- **Also known as:** BIT-tensorflow-2021-37686, GHSA-mhhc-q96p-mfm9, PYSEC-2021-308, PYSEC-2021-599, PYSEC-2021-797

## What is CVE-2021-37686?

CVE-2021-37686 is a medium-severity denial of service vulnerability in Google Tensorflow, published on 12 Aug 2021. It can only be exploited from the same machine or local network, with no action from the victim.

### Official description

TensorFlow is an end-to-end open source platform for machine learning. In affected versions 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](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/strided_slice.cc#L103-L122). 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. We have patched the issue in GitHub commit dfa22b348b70bb89d6d6ec0ff53973bacb4f4695. TensorFlow 2.6.0 is the only affected version.

Weakness: CWE-835 (Loop with Unreachable Exit Condition)

## Which versions are affected by CVE-2021-37686?

10 open source packages ship an affected version, including tensorflow, tensorflow-cpu and tensorflow-gpu. It affects 1 product.


| Package | Ecosystem | Affected | Fixed in |
| --- | --- | --- | --- |
| `tensorflow` | Bitnami | From 2.3.0 | 2.3.4, 2.4.3, 2.5.1 |
| `tensorflow` | PyPI | From 2.3.0 | 2.3.4, 2.4.3 |
| `tensorflow` | PyPI | From 2.6.0rc0 | 2.6.0rc2 |
| `tensorflow` | PyPI | From 2.6.0rc0 | 2.6.0rc2 |
| `tensorflow-cpu` | PyPI | From 2.3.0 | 2.3.4, 2.4.3 |
| `tensorflow-cpu` | PyPI | From 2.6.0rc0 | 2.6.0rc2 |
| `tensorflow-cpu` | PyPI | From 2.6.0rc0 | 2.6.0rc2 |
| `tensorflow-gpu` | PyPI | From 2.3.0 | 2.3.4, 2.4.3 |
| `tensorflow-gpu` | PyPI | From 2.6.0rc0 | 2.6.0rc2 |
| `tensorflow-gpu` | PyPI | From 2.6.0rc0 | 2.6.0rc2 |

Products: Google Tensorflow.

## How do I fix CVE-2021-37686?

Upgrade tensorflow to a fixed version for your release line: 2.3.4, 2.4.3, 2.5.1 or 2.6.0rc2.

## Is CVE-2021-37686 being exploited?

There is no known exploitation of CVE-2021-37686 in the wild and no public exploit code.

## Other vulnerabilities in Google Tensorflow

- [CVE-2023-25668](https://insights.sbomify.com/CVE-2023-25668/): TensorFlow vulnerable to heap out-of-buffer read in the QuantizeAndDequantize operation (critical 9.8)
- [CVE-2018-7575](https://insights.sbomify.com/CVE-2018-7575/): Integer Overflow or Wraparound in Google TensorFlow (critical 9.8)
- [CVE-2021-37678](https://insights.sbomify.com/CVE-2021-37678/): Arbitrary code execution due to YAML deserialization (critical 9.3)
- [CVE-2021-35958](https://insights.sbomify.com/CVE-2021-35958/): Path traversal in n/a (critical 9.1)
- [CVE-2020-15202](https://insights.sbomify.com/CVE-2020-15202/): Integer truncation in Shard API usage (critical 9.0)

## Fix prompt for AI coding agents

```text
Check this codebase for CVE-2021-37686 and fix it if it is affected.

What it is: CVE-2021-37686 is a medium-severity denial of service vulnerability in Google Tensorflow, published on 12 Aug 2021. It can only be exploited from the same machine or local network, with no action from the victim.
Exploitation: There is no known exploitation of CVE-2021-37686 in the wild and no public exploit code.

Affected packages and fixed versions:
- tensorflow (Bitnami): affected from 2.3.0; fixed in 2.3.4, 2.4.3, 2.5.1
- tensorflow (PyPI): affected from 2.3.0; fixed in 2.3.4, 2.4.3
- tensorflow (PyPI): affected from 2.6.0rc0; fixed in 2.6.0rc2
- tensorflow (PyPI): affected from 2.6.0rc0; fixed in 2.6.0rc2
- tensorflow-cpu (PyPI): affected from 2.3.0; fixed in 2.3.4, 2.4.3
- tensorflow-cpu (PyPI): affected from 2.6.0rc0; fixed in 2.6.0rc2
- tensorflow-cpu (PyPI): affected from 2.6.0rc0; fixed in 2.6.0rc2
- tensorflow-gpu (PyPI): affected from 2.3.0; fixed in 2.3.4, 2.4.3
- tensorflow-gpu (PyPI): affected from 2.6.0rc0; fixed in 2.6.0rc2
- tensorflow-gpu (PyPI): affected from 2.6.0rc0; fixed in 2.6.0rc2

Task:
1. Search the dependency manifests and lockfiles (for example package.json, package-lock.json, requirements.txt, poetry.lock, uv.lock, pom.xml, build.gradle, go.mod, Cargo.lock, Gemfile.lock) and any Dockerfiles for the affected packages, including transitive dependencies.
2. If an affected version is in use, upgrade it to the fixed version for its release line with the project's package manager, so the lockfile is regenerated. Prefer the smallest upgrade that fixes it.
3. If there is no fix, or the upgrade would break the build, do not guess: explain the risk and the safest workaround instead.
4. Run the tests and summarise what changed and why.
5. If nothing in the project is affected, say so and change nothing.

Reference: https://insights.sbomify.com/CVE-2021-37686/ (Markdown: https://insights.sbomify.com/CVE-2021-37686/index.md)
```

## Sources

- CVE record: https://www.cve.org/CVERecord?id=CVE-2021-37686
- NVD: https://nvd.nist.gov/vuln/detail/CVE-2021-37686
- OSV: https://osv.dev/vulnerability/CVE-2021-37686

---
From sbomify Insights: https://insights.sbomify.com/CVE-2021-37686/
Summaries are generated and may contain mistakes; the official description above is the record.