CVE-2020-15200

What it is

In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Thus, the code sets up conditions to cause a heap buffer overflow. A `BatchedMap` is equivalent to a vector where each element is a hashmap. However, if the first element of `splits_values` is not 0, `batch_idx` will never be 1, hence there will be no hashmap at index 0 in `per_batch_counts`. Trying to access that in the user code results in a segmentation fault. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.

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. 2020-09-25 19:15 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

2020-09-25 19:15 UTC

Last modified

2026-06-17 02:56 UTC

Exploit probability

0.9% · EPSS, next 30 days

Weakness

CWE-20 · Improper input validation

Record status

Modified

Affected

• Google Tensorflow 2.3.0

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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