LiveActive security incident?Get immediate response
CVE Record

CVE-2021-29595: Division by zero in TFLite's implementation of `DepthToSpace`

TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `DepthToSpace` TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/depth_to_space.cc#L63-L69). An attacker can craft a model such that `params->block_size` is 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-2021-29595 is a low-severity TensorFlow Lite flaw where a malformed model can trigger a divide-by-zero in the DepthToSpace operator. The practical impact is limited availability disruption, not data theft or code execution, based on the provided CVSS and advisory details.

Executive priority

Treat this as routine remediation unless your business accepts untrusted TFLite models. Prioritize patching in ML services with external model ingestion, but this does not warrant emergency response based on the provided evidence.

Technical view

Affected TensorFlow versions mishandle DepthToSpace when the TFLite operator parameter block_size is zero, causing division by zero. The issue is classified as CWE-369 with CVSS 2.5: local attack vector, high complexity, low privileges, and low availability impact only.

Likely exposure

Exposure is most relevant where affected TensorFlow or TFLite versions load models from users, tenants, partners, or other untrusted sources. Environments using only trusted models or patched TensorFlow releases have lower practical risk.

Exploitation context

The source bundle does not show CISA KEV listing or active exploitation. Successful abuse requires a crafted model and local access conditions reflected by the CVSS vector, with expected impact limited to availability.

Researcher notes

The public advisory ties the flaw to TensorFlow Lite DepthToSpace and the linked fixing commit. Evidence supports availability-only impact and specific affected release ranges, but the bundle does not provide proof-of-concept status, real-world exploitation, or broader product impact.

Mitigation direction

  • Upgrade to TensorFlow 2.5.0 or a listed patched supported branch release.
  • For 2.4.x, update to TensorFlow 2.4.2 or later.
  • For 2.3.x, update to TensorFlow 2.3.3 or later.
  • For 2.2.x, update to TensorFlow 2.2.3 or later.
  • For 2.1.x, update to TensorFlow 2.1.4 or later.
  • Restrict loading of untrusted TFLite models until patched.

Validation and detection

  • Inventory TensorFlow and TensorFlow Lite versions in applications and ML pipelines.
  • Check whether any service accepts user-supplied or partner-supplied models.
  • Confirm affected ranges are upgraded to the patched releases named by TensorFlow.
  • Review dependency lockfiles and container images for older TensorFlow packages.
  • Verify model-ingestion paths enforce trusted-source controls.
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-2021-29595 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-2021-29595Attack 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