CVE-2020-15211

What it is

In TensorFlow Lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, saved models in the flatbuffer format use a double indexing scheme: a model has a set of subgraphs, each subgraph has a set of operators and each operator has a set of input/output tensors. The flatbuffer format uses indices for the tensors, indexing into an array of tensors that is owned by the subgraph. This results in a pattern of double array indexing when trying to get the data of each tensor. However, some operators can have some tensors be optional. To handle this scenario, the flatbuffer model uses a negative `-1` value as index for these tensors. This results in special casing during validation at model loading time. Unfortunately, this means that the `-1` index is a valid tensor index for any operator, including those that don't expect optional inputs and including for output tensors. Thus, this allows writing and reading from outside the bounds of heap allocated arrays, although only at a specific offset from the start of these arrays. This results in both read and write gadgets, albeit very limited in scope. The issue is patched in several commits (46d5b0852, 00302787b7, e11f5558, cd31fd0ce, 1970c21, and fff2c83), and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to the model loading code to ensure that only operators which accept optional inputs use the `-1` special value and only for the tensors that they expect to be optional. Since this allow-list type approach is erro-prone, we advise upgrading to the patched code.

At a glance

Exploitability

Can be exploited over the network without logging in. Limited direct impact.

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: 4.8 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-125 · Out-of-bounds read

Record status

Modified

Affected

• Google Tensorflow < 1.15.4
• Google Tensorflow < 2.0.3
• Google Tensorflow < 2.1.2
• Google Tensorflow < 2.2.1
• Google Tensorflow < 2.3.1
• Opensuse Leap 15.2

Attack profile CVSS 3.1 · 4.8

Attack vector

Network

Complexity

High

Privileges needed

None

User interaction

None

Scope

Unchanged

Confidentiality

Low

Integrity

Low

Availability

None

Is it in your code?

Hand this to your coding agent. It searches your project for the affected products and checks versions. Nothing leaves your machine.

Read https://cve-list.com/agent/cve/CVE-2020-15211.md and follow it. Check whether this project is affected by CVE-2020-15211. Read only. Don't change anything and don't upload my code. Tell me yes, no or not sure, with the file as proof.

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