# CVE-2022-23563: Insecure temporary file in Tensorflow > A race condition in TensorFlow's temporary file creation allows attackers to hijack files, potentially leading to code execution or privilege escalation. - **Severity:** High 7.1 (`CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N`) - **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:** 4 Feb 2022 - **Updated:** 23 Apr 2025 - **Also known as:** BIT-tensorflow-2022-23563, GHSA-wc4g-r73w-x8mm, PYSEC-2022-127, PYSEC-2022-72, PYSEC-2026-3253 ## What is CVE-2022-23563? CVE-2022-23563 is a high-severity vulnerability in Google Tensorflow, published on 4 Feb 2022. 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 Machine Learning Framework. In multiple places, TensorFlow uses `tempfile.mktemp` to create temporary files. While this is acceptable in testing, in utilities and libraries it is dangerous as a different process can create the file between the check for the filename in `mktemp` and the actual creation of the file by a subsequent operation (a TOC/TOU type of weakness). In several instances, TensorFlow was supposed to actually create a temporary directory instead of a file. This logic bug is hidden away by the `mktemp` function usage. We have patched the issue in several commits, replacing `mktemp` with the safer `mkstemp`/`mkdtemp` functions, according to the usage pattern. Users are advised to upgrade as soon as possible. Weakness: CWE-367 (Time-of-check Time-of-use (TOCTOU) Race Condition) ## Which versions are affected by CVE-2022-23563? 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 | 2.5.3, 2.6.3, 2.7.1 | | `tensorflow` | PyPI | All versions | 2.5.3, 2.6.3, 2.7.1 | | `tensorflow` | PyPI | All versions | 2.5.3 | | `tensorflow` | PyPI | All versions | 2.5.3 | | `tensorflow` | PyPI | From 2.6.0 | 2.6.3 | | `tensorflow` | PyPI | From 2.6.0 | 2.6.3 | | `tensorflow` | PyPI | From 2.7.0 | 2.7.1 | | `tensorflow` | PyPI | From 2.7.0 | 2.7.1 | | `tensorflow-cpu` | PyPI | All versions | 2.5.3, 2.6.3 | | `tensorflow-cpu` | PyPI | All versions | 2.5.3 | | `tensorflow-cpu` | PyPI | All versions | 2.5.3 | | `tensorflow-cpu` | PyPI | From 2.6.0 | 2.6.3 | | `tensorflow-cpu` | PyPI | From 2.6.0 | 2.6.3 | | `tensorflow-cpu` | PyPI | From 2.7.0 | 2.7.1 | | `tensorflow-cpu` | PyPI | From 2.7.0 | 2.7.1 | | `tensorflow-gpu` | PyPI | All versions | 2.5.3, 2.6.3 | | `tensorflow-gpu` | PyPI | All versions | 2.5.3 | | `tensorflow-gpu` | PyPI | All versions | 2.5.3 | | `tensorflow-gpu` | PyPI | From 2.6.0 | 2.6.3 | | `tensorflow-gpu` | PyPI | From 2.6.0 | 2.6.3 | | `tensorflow-gpu` | PyPI | From 2.7.0 | 2.7.1 | | `tensorflow-gpu` | PyPI | From 2.7.0 | 2.7.1 | Products: Google Tensorflow. ## How do I fix CVE-2022-23563? Upgrade tensorflow to a fixed version for your release line: 2.5.3, 2.6.3 or 2.7.1. ## Is CVE-2022-23563 being exploited? There is no known exploitation of CVE-2022-23563 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-2022-23563 and fix it if it is affected. What it is: CVE-2022-23563 is a high-severity vulnerability in Google Tensorflow, published on 4 Feb 2022. 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-2022-23563 in the wild and no public exploit code. Affected packages and fixed versions: - tensorflow (Bitnami): affected all versions; fixed in 2.5.3, 2.6.3, 2.7.1 - tensorflow (PyPI): affected all versions; fixed in 2.5.3, 2.6.3, 2.7.1 - tensorflow (PyPI): affected all versions; fixed in 2.5.3 - tensorflow (PyPI): affected all versions; fixed in 2.5.3 - tensorflow (PyPI): affected from 2.6.0; fixed in 2.6.3 - tensorflow (PyPI): affected from 2.6.0; fixed in 2.6.3 - tensorflow (PyPI): affected from 2.7.0; fixed in 2.7.1 - tensorflow (PyPI): affected from 2.7.0; fixed in 2.7.1 - tensorflow-cpu (PyPI): affected all versions; fixed in 2.5.3, 2.6.3 - tensorflow-cpu (PyPI): affected all versions; fixed in 2.5.3 - tensorflow-cpu (PyPI): affected all versions; fixed in 2.5.3 - tensorflow-cpu (PyPI): affected from 2.6.0; fixed in 2.6.3 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/CVE-2022-23563/ (Markdown: https://insights.sbomify.com/CVE-2022-23563/index.md) ``` ## Sources - CVE record: https://www.cve.org/CVERecord?id=CVE-2022-23563 - NVD: https://nvd.nist.gov/vuln/detail/CVE-2022-23563 - OSV: https://osv.dev/vulnerability/CVE-2022-23563 --- From sbomify Insights: https://insights.sbomify.com/CVE-2022-23563/ Summaries are generated and may contain mistakes; the official description above is the record.