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CVE Record

CVE-2021-29516: Null pointer dereference via invalid Ragged Tensors

TensorFlow is an end-to-end open source platform for machine learning. Calling `tf.raw_ops.RaggedTensorToVariant` with arguments specifying an invalid ragged tensor results in a null pointer dereference. The implementation of `RaggedTensorToVariant` operations(https://github.com/tensorflow/tensorflow/blob/904b3926ed1c6c70380d5313d282d248a776baa1/tensorflow/core/kernels/ragged_tensor_to_variant_op.cc#L39-L40) does not validate that the ragged tensor argument is non-empty. Since `batched_ragged` contains no elements, `batched_ragged.splits` is a null vector, thus `batched_ragged.splits(0)` will result in dereferencing `nullptr`. 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

TensorFlow could crash when a specific low-level operation receives an invalid empty ragged tensor. This is mainly an availability issue: it can cause a null pointer dereference, not data theft or code execution according to the supplied sources.

Executive priority

Treat this as routine patching unless TensorFlow runs in shared or multi-tenant environments. The business risk is service disruption, not compromise of confidentiality or integrity based on the supplied evidence.

Technical view

CVE-2021-29516 affects TensorFlow RaggedTensorToVariant handling. The operation failed to validate that the ragged tensor was non-empty, allowing an invalid input to dereference a null splits vector. CVSS 3.1 is 2.5, with local access, low privileges, high complexity, and low availability impact.

Likely exposure

Exposure is limited to TensorFlow deployments using affected versions and allowing a low-privileged local user or local workload to invoke TensorFlow raw operations with crafted invalid ragged tensors.

Exploitation context

The source bundle does not show known active exploitation, and KEV is false. The issue requires local access and a specific invalid TensorFlow operation invocation, making broad remote exploitation unlikely from the provided evidence.

Researcher notes

The key condition is an invalid empty ragged tensor passed to RaggedTensorToVariant. Sources identify CWE-476 and a vendor fix commit. Evidence does not establish exploit availability or exploitation in the wild.

Mitigation direction

  • Upgrade TensorFlow to 2.5.0 or a fixed supported backport.
  • Use 2.4.2, 2.3.3, 2.2.3, or 2.1.4 where staying on those branches.
  • Inventory ML runtimes, notebooks, containers, and application dependencies for affected TensorFlow versions.
  • Restrict untrusted local users or workloads from executing TensorFlow code until patched.

Validation and detection

  • Check installed TensorFlow versions against the affected ranges in the advisory.
  • Confirm dependency scans or SBOMs no longer report vulnerable TensorFlow builds.
  • Prioritize shared notebooks, batch workers, and multi-tenant ML environments for review.
  • Verify deployed images and lockfiles use the intended fixed TensorFlow release.
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-476: Exact CWE lookup

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cve · low confidence lookup

CVE-2021-29516 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-2021-29516Attack 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-476

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

CWE-476 · source CWE mapping

NULL Pointer Dereference

NULL Pointer Dereference represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.

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