LiveActive security incident?Get immediate response
CVE Record

CVE-2021-29600: Division by zero in TFLite's implementation of `OneHot`

TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `OneHot` TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/f61c57bd425878be108ec787f4d96390579fb83e/tensorflow/lite/kernels/one_hot.cc#L68-L72). An attacker can craft a model such that at least one of the dimensions of `indices` would be 0. In turn, the `prefix_dim_size` value would become 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

LowCVSS 2.5Not KEV-listedUpdated
Discuss exposureBack to CVEs
Glexia's TakeAutomated analysislow

Security readout for executives and security teams

Plain-English summary

CVE-2021-29600 is a low-severity TensorFlow Lite issue where a specially crafted model can crash processing by triggering division by zero in the OneHot operator. The known impact is limited to availability, not data theft or code execution.

Executive priority

Treat as routine patching unless the business processes untrusted ML models. The risk is service disruption in affected model-processing workflows, not known compromise or data exposure.

Technical view

TensorFlow Lite OneHot mishandles an indices tensor where at least one dimension is 0. That can make prefix_dim_size become 0 and cause a division by zero. CVSS is 2.5 with local access, high complexity, low privileges, and low availability impact.

Likely exposure

Exposure is most likely where applications load or process TensorFlow Lite models from users, partners, pipelines, or other less-trusted sources while running affected TensorFlow versions.

Exploitation context

The provided sources do not show active exploitation, and KEV status is false. Exploitation requires a crafted model and local, low-privileged conditions per the CVSS vector.

Researcher notes

The root weakness is CWE-369 in tensorflow/lite/kernels/one_hot.cc. Focus validation on TFLite OneHot model parsing paths and trust boundaries for model ingestion, without assuming broader TensorFlow execution impact.

Mitigation direction

  • Upgrade TensorFlow to 2.5.0 or later where feasible.
  • For supported older branches, apply fixed releases 2.4.2, 2.3.3, 2.2.3, or 2.1.4.
  • Restrict processing of untrusted TensorFlow Lite models until fixed.
  • Check TensorFlow vendor guidance for branch-specific remediation details.

Validation and detection

  • Inventory TensorFlow and TensorFlow Lite versions in applications and build pipelines.
  • Identify services that accept or process externally supplied TFLite models.
  • Confirm affected ranges are absent from deployed artifacts and containers.
  • Review dependency lockfiles for TensorFlow versions below the fixed releases.
Prepared
Confidence
high
Sources
4

Public sources used

Generated from the cited source records. This long-tail analysis has not been individually reviewed by a named human.

Potential ATT&CK relevance

Conservative CVE-to-ATT&CK context

These mappings and lookup hints may be relevant to the vulnerability behavior, CWE, affected product, or exposure path. Glexia-inferred context is not an official MITRE, ATT&CK, CWE, or CVE Program mapping.

ATT&CK lookup starting points

Use these exact CWE pages and searches to review the Glexia ATT&CK library from this CVE's weakness and description context.

cwe · low confidence lookup

CWE-369: Exact CWE lookup

Use the exact CWE identifier as the starting point before reviewing related ATT&CK behavior. Open the exact CWE lookup page first, then review the ATT&CK searches from that MITRE weakness context. This is a Glexia lookup hint, not an official ATT&CK mapping.

Open ATT&CK lookup
cve · low confidence lookup

CVE-2021-29600 mapping review

Open the CVE-to-ATT&CK bridge for reviewed, inferred, or future official mappings tied to this CVE.

Open ATT&CK lookup
Vulnerability profileCVE Program record
Severity
Low
CVSS
2.5 (3.1)
Known Exploited
No
Published

Vector: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L

Official CVE source material

CNA and ADP enrichment extracted from CVE v5

These fields come from the CVE record and ADP containers, not from Glexia's Take. They preserve time-varying source decisions such as CISA SSVC, KEV status, CVSS metrics, and provider references.

1CVSS vectors
0Timeline events
0ADP providers
3Source links

CVSS vector scores

1 official score

We collect every scored CVSS vector available in the official CNA and ADP containers. When more than one version is present, the table keeps the source vectors side by side instead of collapsing them into the highest score.

ScoreVersionSeverityVectorExploitImpactSource
2.5CVSS 3.1LowCVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L11.4Primary CVE score

Vulnerability scoring details

Base CVSS 3.1 score

2.5Low
CVSS 3.1 vector shape for CVE-2021-29600Attack VectorAttack ComplexityPrivileges RequiredUser InteractionScopeConfidentiality ImpactIntegrity ImpactAvailability Impact

Vector: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L

Attack Vector
NetworkAdjacentLocalPhysical
Attack Complexity
LowHigh
Privileges Required
NoneLowHigh
User Interaction
NoneRequired
Scope
ChangedUnchanged
Confidentiality Impact
HighLowNone
Integrity Impact
HighLowNone
Availability Impact
HighLowNone

Source materials

Affected products

Products and packages named in the record

VendorProductVersion / packageStatus
tensorflowtensorflow< 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2Listed
Weakness

CWE details

CWE-369

CWE links open Glexia weakness intelligence pages with official CWE context, developer remediation guidance, and related CVE mappings.

CWE-369 · source CWE mapping

Divide By Zero

Divide By Zero represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.

Open CWE intelligenceSame-CWE CVEs