CVE-2021-29550Public exploit

Runtime crash via unchecked zero pool length

Published May 14, 2021 · Updated Aug 3, 2024

A divide-by-zero in affected Google TensorFlow releases allows local users to crash the runtime through crafted FractionalAvgPool inputs. The FractionalAvgPool kernel accepts an input dimension smaller than its pooling ratio, computes a zero output length, and passes it to GeneratePoolingSequence for a modulo operation. Exploitation requires executing the crafted operation in a hosting process and terminates that process without reported data disclosure or modification.

CVSS severity2.5
Low
EPSS probability0.19%
Next 30 days · Sep 16, 2026
Known exploitationUnconfirmed
Based on sourced intelligence
Hinoki checkNot available
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Summary

What happened

A divide-by-zero in affected Google TensorFlow releases allows local users to crash the runtime through crafted FractionalAvgPool inputs. The FractionalAvgPool kernel accepts an input dimension smaller than its pooling ratio, computes a zero output length, and passes it to GeneratePoolingSequence for a modulo operation. Exploitation requires executing the crafted operation in a hosting process and terminates that process without reported data disclosure or modification.

The record

CVE
CVE-2021-29550
Published
May 14, 2021
Updated
Aug 3, 2024
Vendor
Google
Product
TensorFlow
Classifications
CWE-369, T1499.004
Attack vector
local
Privileges
authenticated

Timeline

How it unfolded

  1. May 14, 2021CVE publishedPublication date reported by the CVE source.
  2. Aug 3, 2024Record updatedLatest update available in the CVE record.

Exploitability

Present is not the same as exploitable

Compare your product and version with the public record. A matching version still requires validation against your environment.

Is a vulnerable build present?

Compare these published version ranges with your installed build and any vendor patches.

  1. Affected versionversion=< 2.1.4
  2. Affected versionversion=>= 2.2.0, < 2.2.3
  3. Affected versionversion=>= 2.3.0, < 2.3.3
  4. Affected versionversion=>= 2.4.0, < 2.4.2

What conditions does exploitation require?

Attack vectorlocal
Required privilegesauthenticated

What is affected?

Google · TensorFlowversion=< 2.1.4; version=>= 2.2.0, < 2.2.3; version=>= 2.3.0, < 2.3.3; version=>= 2.4.0, < 2.4.2

Published CVSS scores

5.5NIST NVDCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
2.1NIST NVDAV:L/AC:L/Au:N/C:N/I:N/A:P
2.5GitHub, Inc.CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L

CVSS describes severity. EPSS estimates exploitation probability.

Attacks

What attackers are doing with it

Daily unique IPs observed by Shadowserver honeypots for known exploited vulnerabilities (KEVs). Missing observations do not establish an absence of attacks.

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No observations available

Sep 10, 2026Sep 16, 2026
Latest reporting daySep 16, 2026
Latest daily unique IPsUnavailable
Prior 30-day averageUnavailable
SourceShadowserver honeypots (KEV)
Vectorlocal
Privilegesauthenticated
Known exploitationUnconfirmed
Public exploitPublished

Weakness, pattern, technique

CWE-369Divide By Zero
T1499.004Application or System Exploitation

Public exploit references

Labels summarize the accepted research assessment. They do not indicate a test against your environment.

Technologies

Your stack

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Your stack

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