# CVE-2022-35985: `CHECK` fail in `LRNGrad` in TensorFlow > Attackers can cause a denial of service in TensorFlow by providing a non-4-D tensor to the LRNGrad operation, triggering a CHECK failure. - **Severity:** Medium 5.9 (`CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H`) - **Exploited in the wild:** Not known - **Login needed:** Not needed - **Attackable:** Over the internet - **Victim action needed:** Not needed - **Fix available:** Yes - **Published:** 16 Sep 2022 - **Updated:** 23 Apr 2025 - **Also known as:** BIT-tensorflow-2022-35985, GHSA-9942-r22v-78cp, PYSEC-2026-3147, PYSEC-2026-3303, PYSEC-2026-975 ## What is CVE-2022-35985? CVE-2022-35985 is a medium-severity denial of service vulnerability in Google Tensorflow, published on 16 Sep 2022. An attacker can exploit it over the internet without logging in, with no action from the victim. ### Official description TensorFlow is an open source platform for machine learning. If `LRNGrad` is given an `output_image` input tensor that is not 4-D, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit bd90b3efab4ec958b228cd7cfe9125be1c0cf255. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue. Weakness: CWE-617 (Reachable Assertion) ## Which versions are affected by CVE-2022-35985? 22 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 | All versions | 2.7.2, 2.8.1, 2.9.1 | | `tensorflow` | PyPI | All versions | 2.7.2, 2.8.1, 2.9.1 | | `tensorflow` | PyPI | All versions | 2.7.2 | | `tensorflow` | PyPI | All versions | 2.7.2 | | `tensorflow` | PyPI | From 2.8.0 | 2.8.1 | | `tensorflow` | PyPI | From 2.8.0 | 2.8.1 | | `tensorflow` | PyPI | From 2.9.0 | 2.9.1 | | `tensorflow` | PyPI | From 2.9.0 | 2.9.1 | | `tensorflow-cpu` | PyPI | All versions | 2.7.2, 2.8.1, 2.9.1 | | `tensorflow-cpu` | PyPI | All versions | 2.7.2 | | `tensorflow-cpu` | PyPI | All versions | 2.7.2 | | `tensorflow-cpu` | PyPI | From 2.8.0 | 2.8.1 | | `tensorflow-cpu` | PyPI | From 2.8.0 | 2.8.1 | | `tensorflow-cpu` | PyPI | From 2.9.0 | 2.9.1 | | `tensorflow-cpu` | PyPI | From 2.9.0 | 2.9.1 | | `tensorflow-gpu` | PyPI | All versions | 2.7.2, 2.8.1, 2.9.1 | | `tensorflow-gpu` | PyPI | All versions | 2.7.2 | | `tensorflow-gpu` | PyPI | All versions | 2.7.2 | | `tensorflow-gpu` | PyPI | From 2.8.0 | 2.8.1 | | `tensorflow-gpu` | PyPI | From 2.8.0 | 2.8.1 | | `tensorflow-gpu` | PyPI | From 2.9.0 | 2.9.1 | | `tensorflow-gpu` | PyPI | From 2.9.0 | 2.9.1 | Products: Google Tensorflow. ## How do I fix CVE-2022-35985? Upgrade tensorflow to a fixed version for your release line: 2.7.2, 2.8.1 or 2.9.1. ## Is CVE-2022-35985 being exploited? There is no known exploitation of CVE-2022-35985 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-2022-35985 and fix it if it is affected. What it is: CVE-2022-35985 is a medium-severity denial of service vulnerability in Google Tensorflow, published on 16 Sep 2022. An attacker can exploit it over the internet without logging in, with no action from the victim. Exploitation: There is no known exploitation of CVE-2022-35985 in the wild and no public exploit code. Affected packages and fixed versions: - tensorflow (Bitnami): affected all versions; fixed in 2.7.2, 2.8.1, 2.9.1 - tensorflow (PyPI): affected all versions; fixed in 2.7.2, 2.8.1, 2.9.1 - tensorflow (PyPI): affected all versions; fixed in 2.7.2 - tensorflow (PyPI): affected all versions; fixed in 2.7.2 - tensorflow (PyPI): affected from 2.8.0; fixed in 2.8.1 - tensorflow (PyPI): affected from 2.8.0; fixed in 2.8.1 - tensorflow (PyPI): affected from 2.9.0; fixed in 2.9.1 - tensorflow (PyPI): affected from 2.9.0; fixed in 2.9.1 - tensorflow-cpu (PyPI): affected all versions; fixed in 2.7.2, 2.8.1, 2.9.1 - tensorflow-cpu (PyPI): affected all versions; fixed in 2.7.2 - tensorflow-cpu (PyPI): affected all versions; fixed in 2.7.2 - tensorflow-cpu (PyPI): affected from 2.8.0; fixed in 2.8.1 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-2022-35985/ (Markdown: https://insights.sbomify.com/CVE-2022-35985/index.md) ``` ## Sources - CVE record: https://www.cve.org/CVERecord?id=CVE-2022-35985 - NVD: https://nvd.nist.gov/vuln/detail/CVE-2022-35985 - OSV: https://osv.dev/vulnerability/CVE-2022-35985 --- From sbomify Insights: https://insights.sbomify.com/CVE-2022-35985/ Summaries are generated and may contain mistakes; the official description above is the record.