# CVE-2021-41211: Heap OOB read in shape inference for `QuantizeV2`

> An attacker can trigger a heap out-of-bounds read in TensorFlow's QuantizeV2 shape inference by providing a negative axis value, potentially leaking memory or causing a crash.

- **Severity:** High 7.1 (`CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/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:** 5 Nov 2021
- **Updated:** 4 Aug 2024
- **Also known as:** BIT-tensorflow-2021-41211, GHSA-cvgx-3v3q-m36c, PYSEC-2021-403, PYSEC-2021-620, PYSEC-2021-818

## What is CVE-2021-41211?

CVE-2021-41211 is a high-severity memory corruption vulnerability in Google Tensorflow, published on 5 Nov 2021. It can only be exploited from the same machine or local network, with no action from the victim.

### Official description

TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `QuantizeV2` can trigger a read outside of bounds of heap allocated array. This occurs whenever `axis` is a negative value less than `-1`. In this case, we are accessing data before the start of a heap buffer. The code allows `axis` to be an optional argument (`s` would contain an `error::NOT_FOUND` error code). Otherwise, it assumes that `axis` is a valid index into the dimensions of the `input` tensor. If `axis` is less than `-1` then this results in a heap OOB read. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected.

Weakness: CWE-125 (Out-of-bounds Read)

## Which versions are affected by CVE-2021-41211?

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 2.6.0 | 2.6.1 |
| `tensorflow` | PyPI | From 2.6.0 | 2.6.1, 2.7.0 |
| `tensorflow` | PyPI | From 2.6.0 | 2.6.1 |
| `tensorflow` | PyPI | From 2.6.0 | 2.6.1 |
| `tensorflow-cpu` | PyPI | From 2.6.0 | 2.6.1, 2.7.0 |
| `tensorflow-cpu` | PyPI | From 2.6.0 | 2.6.1 |
| `tensorflow-cpu` | PyPI | From 2.6.0 | 2.6.1 |
| `tensorflow-gpu` | PyPI | From 2.6.0 | 2.6.1, 2.7.0 |
| `tensorflow-gpu` | PyPI | From 2.6.0 | 2.6.1 |
| `tensorflow-gpu` | PyPI | From 2.6.0 | 2.6.1 |

Products: Google Tensorflow.

## How do I fix CVE-2021-41211?

Upgrade tensorflow to a fixed version for your release line: 2.6.1 or 2.7.0.

## Is CVE-2021-41211 being exploited?

There is no known exploitation of CVE-2021-41211 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-2021-41211 and fix it if it is affected.

What it is: CVE-2021-41211 is a high-severity memory corruption vulnerability in Google Tensorflow, published on 5 Nov 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-2021-41211 in the wild and no public exploit code.

Affected packages and fixed versions:
- tensorflow (Bitnami): affected from 2.6.0; fixed in 2.6.1
- tensorflow (PyPI): affected from 2.6.0; fixed in 2.6.1, 2.7.0
- tensorflow (PyPI): affected from 2.6.0; fixed in 2.6.1
- tensorflow (PyPI): affected from 2.6.0; fixed in 2.6.1
- tensorflow-cpu (PyPI): affected from 2.6.0; fixed in 2.6.1, 2.7.0
- tensorflow-cpu (PyPI): affected from 2.6.0; fixed in 2.6.1
- tensorflow-cpu (PyPI): affected from 2.6.0; fixed in 2.6.1
- tensorflow-gpu (PyPI): affected from 2.6.0; fixed in 2.6.1, 2.7.0
- tensorflow-gpu (PyPI): affected from 2.6.0; fixed in 2.6.1
- tensorflow-gpu (PyPI): affected from 2.6.0; fixed in 2.6.1

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-2021-41211/ (Markdown: https://insights.sbomify.com/CVE-2021-41211/index.md)
```

## Sources

- CVE record: https://www.cve.org/CVERecord?id=CVE-2021-41211
- NVD: https://nvd.nist.gov/vuln/detail/CVE-2021-41211
- OSV: https://osv.dev/vulnerability/CVE-2021-41211

---
From sbomify Insights: https://insights.sbomify.com/CVE-2021-41211/
Summaries are generated and may contain mistakes; the official description above is the record.