Security readout for executives and security teams
Plain-English summary
Affected TensorFlow versions mishandle an empty input case in a ragged tensor conversion operation. A user who can run TensorFlow code locally could trigger undefined behavior, with high confidentiality, integrity, and availability impact per CVSS. This matters most in shared ML platforms and notebooks.
Executive priority
Treat as high priority for shared or multi-user ML infrastructure. The issue is patched and version-bounded, so remediation should focus on upgrading affected TensorFlow deployments and limiting untrusted code execution until patched.
Technical view
`tf.raw_ops.RaggedTensorToVariant` missed validation for empty splits values, leading to a reference binding to a null pointer. TensorFlow patched this in commit `be7a4de6adfbd303ce08be4332554dff70362612`, with fixes planned for 2.6.0, 2.5.1, 2.4.3, and 2.3.4.
Likely exposure
Exposure is likely where TensorFlow is installed in affected ranges and low-privileged users can execute TensorFlow operations. This includes shared training hosts, notebooks, CI jobs, or ML services that pass untrusted requests into TensorFlow execution paths.
Exploitation context
The source bundle does not report active exploitation, and CISA KEV status is false. CVSS indicates local attack vector, low complexity, low privileges, and no user interaction. No remote exploit path is established by the provided sources.
Researcher notes
This is CWE-824: access or binding involving a null pointer. The advisory attributes the bug to incomplete splits validation in `RaggedTensorToVariant`, specifically missing the empty-argument case. Provided sources do not include proof-of-concept details or exploitation claims.
Mitigation direction
- Upgrade TensorFlow to 2.6.0 or later where possible.
- For supported branches, apply 2.5.1, 2.4.3, or 2.3.4 fixes.
- Restrict untrusted users from running arbitrary TensorFlow operations on shared systems.
- Review vendor advisory and commit for branch-specific patch availability.
- Prioritize shared ML environments before isolated developer workstations.
Validation and detection
- Inventory TensorFlow package versions across hosts, containers, notebooks, and CI images.
- Flag versions >=2.5.0 <2.5.1, >=2.4.0 <2.4.3, and <2.3.4.
- Check whether workloads expose ragged tensor conversion to untrusted users or jobs.
- Confirm patched versions are deployed in runtime images, not only build manifests.
- Document any unavoidable affected deployments and compensating access controls.
Public sources used
Generated from the cited source records. This long-tail analysis has not been individually reviewed by a named human.
Conservative CVE-to-ATT&CK context
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ATT&CK lookup starting points
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CWE-824: Exact CWE lookup
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Open ATT&CK lookupCVE-2021-37666 mapping review
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Open ATT&CK lookup- Severity
- High
- CVSS
- 7.8 (3.1)
- Known Exploited
- No
- Published
Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
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.
CVSS vector scores
1 official scoreWe 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.
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H1.85.9Primary CVE scoreVulnerability scoring details
Base CVSS 3.1 score
7.8HighVector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Source materials
- CVE List V5 sourceCVE List V5
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-w4xf-2pqw-5mq7CVE reference · x_refsource_CONFIRM
- https://github.com/tensorflow/tensorflow/commit/be7a4de6adfbd303ce08be4332554dff70362612CVE reference · x_refsource_MISC
Products and packages named in the record
CWE details
CWE links open Glexia weakness intelligence pages with official CWE context, developer remediation guidance, and related CVE mappings.
Access of Uninitialized Pointer
Access of Uninitialized Pointer represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.