# CVE-2023-30767: Memory corruption in TensorFlow

> An authenticated local attacker can exploit improper buffer restrictions in Intel Optimization for TensorFlow to escalate privileges.

- **Severity:** Medium 5.5 (`CVSS:3.1/AV:L/AC:H/PR:L/UI:R/S:U/C:L/I:H/A:L`)
- **Exploited in the wild:** Not known
- **Login needed:** Any signed-in user
- **Attackable:** Local or same network only
- **Victim action needed:** A user has to click or open something
- **Fix available:** No
- **Published:** 14 Feb 2024
- **Updated:** 14 Aug 2024
- **Also known as:** GHSA-7cxm-qx65-mv3h

## What is CVE-2023-30767?

CVE-2023-30767 is a medium-severity memory corruption vulnerability in TensorFlow, published on 14 Feb 2024. It can only be exploited from the same machine or local network, and only if a user opens a file or follows a link.

### Official description

Improper buffer restrictions in Intel(R) Optimization for TensorFlow before version 2.13.0 may allow an authenticated user to potentially enable escalation of privilege via local access.

Weakness: CWE-119 (Improper Restriction of Operations within the Bounds of a Memory Buffer), CWE-92 (DEPRECATED: Improper Sanitization of Custom Special Characters)

## Which versions are affected by CVE-2023-30767?

It affects 1 product.


Products: Intel Optimization for Tensorflow.

## How do I fix CVE-2023-30767?

No fix has been published for CVE-2023-30767 yet. Limit exposure of the affected software until one is available.

## Is CVE-2023-30767 being exploited?

There is no known exploitation of CVE-2023-30767 in the wild and no public exploit code.

## Other vulnerabilities in TensorFlow

- [CVE-2023-27506](https://insights.sbomify.com/CVE-2023-27506/): Authenticated Local Privilege Escalation vulnerability in Intel Optimization for Tensorflow (medium 5.5)

## Fix prompt for AI coding agents

```text
Check this codebase for CVE-2023-30767 and fix it if it is affected.

What it is: CVE-2023-30767 is a medium-severity memory corruption vulnerability in TensorFlow, published on 14 Feb 2024. It can only be exploited from the same machine or local network, and only if a user opens a file or follows a link.
Exploitation: There is no known exploitation of CVE-2023-30767 in the wild and no public exploit code.

Affected product: TensorFlow. No package-level version data is available, so check the vendor advisory linked from the reference page.

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-2023-30767/ (Markdown: https://insights.sbomify.com/CVE-2023-30767/index.md)
```

## Sources

- CVE record: https://www.cve.org/CVERecord?id=CVE-2023-30767
- NVD: https://nvd.nist.gov/vuln/detail/CVE-2023-30767
- OSV: https://osv.dev/vulnerability/CVE-2023-30767

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From sbomify Insights: https://insights.sbomify.com/CVE-2023-30767/
Summaries are generated and may contain mistakes; the official description above is the record.