CVE-2023-30767 Memory corruption in TensorFlow
An authenticated local attacker can exploit improper buffer restrictions in Intel Optimization for TensorFlow to escalate privileges.
- 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
- None listed
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.
Which versions are affected by CVE-2023-30767?
It affects 1 product.
Products include 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.
Upgrade to the fixed version. Memory-safe languages, compiler hardening and fuzzing prevent most new cases. More about Memory corruption.
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
Sources
Also known as GHSA-7cxm-qx65-mv3h.