CVE-2020-15265

What it is

In Tensorflow before version 2.4.0, an attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dim_size only does a DCHECK to validate the argument and then uses it to access the corresponding element of an array. Since in normal builds, `DCHECK`-like macros are no-ops, this results in segfault and access out of bounds of the array. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.

At a glance

Exploitability

Can be exploited over the network without logging in. High risk of service disruption.

Exploit odds

0.9% chance of exploitation in the next 30 days (EPSS).

Fix

A patch, advisory or fixed version is referenced. Upgrade or apply it.

Timeline

1. 2020-10-21 21:15 UTC PublishedDisclosed publicly on CVE.org and NVD
2. 2026-06-17 02:56 UTC Last updatedMost recent change to the record

Why it ranks here

• Exploited in the wild: no, CISA does not list it.
• Exploit odds: 0.9% in the next 30 days (EPSS).
• Severity: 5.9 MEDIUM (CVSS).
• Fix: a patch or advisory is linked.

Details

Published

2020-10-21 21:15 UTC

Last modified

2026-06-17 02:56 UTC

Exploit probability

0.9% · EPSS, next 30 days

Weakness

CWE-125 · Out-of-bounds read

Record status

Modified

Affected

• Google Tensorflow < 2.4.0

Attack profile CVSS 3.1 · 5.9

Attack vector

Network

Complexity

High

Privileges needed

None

User interaction

None

Scope

Unchanged

Confidentiality

None

Integrity

None

Availability

High

Is it in your code?

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