# GHSA-xf83-q765-xm6m: `CHECK` fail in `TensorListScatter` and `TensorListScatterV2` in eager mode > A CHECK failure in TensorFlow's TensorListScatter operations allows attackers to cause a denial of service via crafted non-scalar inputs. - **Severity:** Not scored - **Exploited in the wild:** Not known - **Login needed:** Not needed - **Attackable:** Not stated - **Victim action needed:** Not needed - **Fix available:** Yes - **Published:** 21 Nov 2022 ## What is GHSA-xf83-q765-xm6m? GHSA-xf83-q765-xm6m is a denial of service vulnerability in tensorflow, published on 21 Nov 2022. ### Official description ### Impact Another instance of CVE-2022-35991, where `TensorListScatter` and `TensorListScatterV2` crash via non scalar inputs in`element_shape`, was found in eager mode and fixed. ```python import tensorflow as tf arg_0=tf.random.uniform(shape=(2, 2, 2), dtype=tf.float16, maxval=None) arg_1=tf.random.uniform(shape=(2, 2, 2), dtype=tf.int32, maxval=65536) arg_2=tf.random.uniform(shape=(2, 2, 2), dtype=tf.int32, maxval=65536) arg_3='' tf.raw_ops.TensorListScatter(tensor=arg_0, indices=arg_1, element_shape=arg_2, name=arg_3) ``` ### Patches We have patched the issue in GitHub commit [bf9932fc907aff0e9e8cccf769e8b00d30fd81a1](https://github.com/tensorflow/tensorflow/commit/bf9932fc907aff0e9e8cccf769e8b00d30fd81a1). The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by Pattarakrit Rattankul ## Which versions are affected by GHSA-xf83-q765-xm6m? 18 open source packages ship an affected version, including tensorflow, tensorflow-cpu and tensorflow-gpu. | Package | Ecosystem | Affected | Fixed in | | --- | --- | --- | --- | | `tensorflow` | PyPI | All versions | 2.8.4 | | `tensorflow` | PyPI | All versions | 2.8.4 | | `tensorflow` | PyPI | From 2.10.0 | 2.10.1 | | `tensorflow` | PyPI | From 2.10.0 | 2.10.1 | | `tensorflow` | PyPI | From 2.9.0 | 2.9.3 | | `tensorflow` | PyPI | From 2.9.0 | 2.9.3 | | `tensorflow-cpu` | PyPI | All versions | 2.8.4 | | `tensorflow-cpu` | PyPI | All versions | 2.8.4 | | `tensorflow-cpu` | PyPI | From 2.10.0 | 2.10.1 | | `tensorflow-cpu` | PyPI | From 2.10.0 | 2.10.1 | | `tensorflow-cpu` | PyPI | From 2.9.0 | 2.9.3 | | `tensorflow-cpu` | PyPI | From 2.9.0 | 2.9.3 | | `tensorflow-gpu` | PyPI | All versions | 2.8.4 | | `tensorflow-gpu` | PyPI | All versions | 2.8.4 | | `tensorflow-gpu` | PyPI | From 2.10.0 | 2.10.1 | | `tensorflow-gpu` | PyPI | From 2.10.0 | 2.10.1 | | `tensorflow-gpu` | PyPI | From 2.9.0 | 2.9.3 | | `tensorflow-gpu` | PyPI | From 2.9.0 | 2.9.3 | ## How do I fix GHSA-xf83-q765-xm6m? Upgrade tensorflow to a fixed version for your release line: 2.8.4, 2.10.1 or 2.9.3. ## Is GHSA-xf83-q765-xm6m being exploited? There is no known exploitation of GHSA-xf83-q765-xm6m in the wild and no public exploit code. ## Fix prompt for AI coding agents ```text Check this codebase for GHSA-xf83-q765-xm6m and fix it if it is affected. What it is: GHSA-xf83-q765-xm6m is a denial of service vulnerability in tensorflow, published on 21 Nov 2022. Exploitation: There is no known exploitation of GHSA-xf83-q765-xm6m in the wild and no public exploit code. Affected packages and fixed versions: - tensorflow (PyPI): affected all versions; fixed in 2.8.4 - tensorflow (PyPI): affected all versions; fixed in 2.8.4 - tensorflow (PyPI): affected from 2.10.0; fixed in 2.10.1 - tensorflow (PyPI): affected from 2.10.0; fixed in 2.10.1 - tensorflow (PyPI): affected from 2.9.0; fixed in 2.9.3 - tensorflow (PyPI): affected from 2.9.0; fixed in 2.9.3 - tensorflow-cpu (PyPI): affected all versions; fixed in 2.8.4 - tensorflow-cpu (PyPI): affected all versions; fixed in 2.8.4 - tensorflow-cpu (PyPI): affected from 2.10.0; fixed in 2.10.1 - tensorflow-cpu (PyPI): affected from 2.10.0; fixed in 2.10.1 - tensorflow-cpu (PyPI): affected from 2.9.0; fixed in 2.9.3 - tensorflow-cpu (PyPI): affected from 2.9.0; fixed in 2.9.3 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/GHSA-xf83-q765-xm6m/ (Markdown: https://insights.sbomify.com/GHSA-xf83-q765-xm6m/index.md) ``` ## Sources - OSV: https://osv.dev/vulnerability/GHSA-xf83-q765-xm6m --- From sbomify Insights: https://insights.sbomify.com/GHSA-xf83-q765-xm6m/ Summaries are generated and may contain mistakes; the official description above is the record.