# CVE-2021-37692: Segfault on strings tensors with mistmatched dimensions in TensorFlow

> An attacker can cause a segmentation fault and denial of service in TensorFlow by providing string tensors with mismatched dimensions that fail encoding.

- **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:** 4 Aug 2024
- **Also known as:** BIT-tensorflow-2021-37692, GHSA-cmgw-8vpc-rc59, PYSEC-2021-314, PYSEC-2021-605, PYSEC-2021-803

## What is CVE-2021-37692?

CVE-2021-37692 is a medium-severity 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 under certain conditions, Go code can trigger a segfault in string deallocation. For string tensors, `C.TF_TString_Dealloc` is called during garbage collection within a finalizer function. However, tensor structure isn't checked until encoding to avoid a performance penalty. The current method for dealloc assumes that encoding succeeded, but segfaults when a string tensor is garbage collected whose encoding failed (e.g., due to mismatched dimensions). To fix this, the call to set the finalizer function is deferred until `NewTensor` returns and, if encoding failed for a string tensor, deallocs are determined based on bytes written. We have patched the issue in GitHub commit 8721ba96e5760c229217b594f6d2ba332beedf22. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, which is the other affected version.

Weakness: CWE-20 (Improper Input Validation)

## Which versions are affected by CVE-2021-37692?

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 2.5.0 | 2.6.0 |
| `tensorflow` | PyPI | From 2.3.0 | 2.3.4, 2.4.3 |
| `tensorflow` | PyPI | From 2.5.0rc0 | 2.5.1 |
| `tensorflow` | PyPI | From 2.5.0rc0 | 2.5.1 |
| `tensorflow-cpu` | PyPI | From 2.3.0 | 2.3.4, 2.4.3 |
| `tensorflow-cpu` | PyPI | From 2.5.0rc0 | 2.5.1 |
| `tensorflow-cpu` | PyPI | From 2.5.0rc0 | 2.5.1 |
| `tensorflow-gpu` | PyPI | From 2.3.0 | 2.3.4, 2.4.3 |
| `tensorflow-gpu` | PyPI | From 2.5.0rc0 | 2.5.1 |
| `tensorflow-gpu` | PyPI | From 2.5.0rc0 | 2.5.1 |

Products: Google Tensorflow.

## How do I fix CVE-2021-37692?

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

## Is CVE-2021-37692 being exploited?

There is no known exploitation of CVE-2021-37692 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-2021-37692 and fix it if it is affected.

What it is: CVE-2021-37692 is a medium-severity 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-2021-37692 in the wild and no public exploit code.

Affected packages and fixed versions:
- tensorflow (Bitnami): affected from 2.5.0; fixed in 2.6.0
- tensorflow (PyPI): affected from 2.3.0; fixed in 2.3.4, 2.4.3
- tensorflow (PyPI): affected from 2.5.0rc0; fixed in 2.5.1
- tensorflow (PyPI): affected from 2.5.0rc0; fixed in 2.5.1
- tensorflow-cpu (PyPI): affected from 2.3.0; fixed in 2.3.4, 2.4.3
- tensorflow-cpu (PyPI): affected from 2.5.0rc0; fixed in 2.5.1
- tensorflow-cpu (PyPI): affected from 2.5.0rc0; fixed in 2.5.1
- tensorflow-gpu (PyPI): affected from 2.3.0; fixed in 2.3.4, 2.4.3
- tensorflow-gpu (PyPI): affected from 2.5.0rc0; fixed in 2.5.1
- tensorflow-gpu (PyPI): affected from 2.5.0rc0; fixed in 2.5.1

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-2021-37692/ (Markdown: https://insights.sbomify.com/CVE-2021-37692/index.md)
```

## Sources

- CVE record: https://www.cve.org/CVERecord?id=CVE-2021-37692
- NVD: https://nvd.nist.gov/vuln/detail/CVE-2021-37692
- OSV: https://osv.dev/vulnerability/CVE-2021-37692

---
From sbomify Insights: https://insights.sbomify.com/CVE-2021-37692/
Summaries are generated and may contain mistakes; the official description above is the record.