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CVE Record

CVE-2021-29576: Heap buffer overflow in `MaxPool3DGradGrad`

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPool3DGradGrad` is vulnerable to a heap buffer overflow. The implementation(https://github.com/tensorflow/tensorflow/blob/596c05a159b6fbb9e39ca10b3f7753b7244fa1e9/tensorflow/core/kernels/pooling_ops_3d.cc#L694-L696) does not check that the initialization of `Pool3dParameters` completes successfully. Since the constructor(https://github.com/tensorflow/tensorflow/blob/596c05a159b6fbb9e39ca10b3f7753b7244fa1e9/tensorflow/core/kernels/pooling_ops_3d.cc#L48-L88) uses `OP_REQUIRES` to validate conditions, the first assertion that fails interrupts the initialization of `params`, making it contain invalid data. In turn, this might cause a heap buffer overflow, depending on default initialized values. 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
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Glexia's TakeAutomated analysislow

Security readout for executives and security teams

Plain-English summary

This TensorFlow flaw can crash or disrupt a local ML workload when a low-privileged user reaches a vulnerable 3D max-pooling gradient operation with malformed parameters. The public record rates impact as low availability only, with no confidentiality or integrity impact stated.

Executive priority

Treat this as routine dependency remediation unless vulnerable TensorFlow is used in multi-user ML platforms. Prioritize upgrades during normal patch cycles, with faster action for shared notebook, training, or inference environments exposed to tenant-controlled code.

Technical view

CVE-2021-29576 is a heap buffer overflow in tf.raw_ops.MaxPool3DGradGrad. Pool3dParameters initialization could fail through OP_REQUIRES validation, leaving invalid parameter data later used by the kernel. Affected TensorFlow releases include branches before fixed versions 2.1.4, 2.2.3, 2.3.3, and 2.4.2.

Likely exposure

Exposure is most likely in systems running affected TensorFlow versions where a local user, tenant job, notebook, or pipeline can execute TensorFlow operations. The CVSS vector indicates local access, low privileges, high attack complexity, and no user interaction.

Exploitation context

The source bundle does not cite active exploitation, public weaponization, or CISA KEV listing. Exploitation is constrained by local access and high complexity, and the described impact is limited to availability disruption.

Researcher notes

The vulnerable condition depends on failed Pool3dParameters initialization leaving invalid data after OP_REQUIRES stops constructor progress. The advisory does not provide exploit evidence. Validation should focus on reachable operation usage, TensorFlow version, and local execution boundaries.

Mitigation direction

  • Upgrade TensorFlow to 2.5.0 or a fixed supported backport release.
  • Use TensorFlow 2.4.2, 2.3.3, 2.2.3, or 2.1.4 where branch pinning is required.
  • Review vendor guidance for unsupported TensorFlow versions older than fixed branches.
  • Limit untrusted users' ability to run arbitrary TensorFlow operations in shared environments.

Validation and detection

  • Inventory application, notebook, container, and pipeline dependencies for TensorFlow versions.
  • Confirm deployed runtime versions, not only source dependency declarations.
  • Identify workloads using tf.raw_ops.MaxPool3DGradGrad or related 3D pooling gradient paths.
  • Check whether shared ML platforms allow low-privileged users to execute arbitrary TensorFlow jobs.
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

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ATT&CK lookup starting points

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cwe · low confidence lookup

CWE-119: Exact CWE lookup

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cve · low confidence lookup

CVE-2021-29576 mapping review

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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-2021-29576Attack 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-119

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

CWE-119 · source CWE mapping

Improper Restriction of Operations within the Bounds of a Memory Buffer

Improper Restriction of Operations within the Bounds of a Memory Buffer represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.

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