Security readout for executives and security teams
Plain-English summary
This TensorFlow flaw can crash a process when a specific low-level operation is called with unsupported data types. It does not expose data or alter results, but it can cause limited downtime where TensorFlow executes untrusted or user-controlled model code.
Executive priority
Treat this as a low-priority availability risk unless TensorFlow is exposed to untrusted model execution. Patch during normal maintenance, but prioritize sooner for shared ML platforms where one user can crash worker processes affecting others.
Technical view
CVE-2021-29539 is a segfault in tf.raw_ops.ImmutableConst when dtype is tf.resource or tf.variant. The implementation assumed tensor contents were scalar, causing a crash. The issue is local, high-complexity, low-privilege, and availability-only per CVSS 3.1 score 2.5.
Likely exposure
Exposure is most relevant in ML platforms, notebooks, model-serving systems, or pipelines that allow low-privileged users to run TensorFlow operations or submit model graphs. Standard applications that do not expose TensorFlow execution to untrusted input are less likely to be affected.
Exploitation context
The provided sources do not report active exploitation, and the CVE is not listed as KEV. Exploitation requires local or equivalent ability to execute TensorFlow code that reaches ImmutableConst with the problematic dtype, so business impact is mainly process crash or job interruption.
Researcher notes
The root issue is a type assumption in ImmutableConst. Sources identify CWE-681 and affected TensorFlow maintenance ranges. No source confirms remote exploitation or broader product impact. Validation should focus on reachable low-level op usage and execution boundaries for untrusted TensorFlow workloads.
Mitigation direction
- Upgrade TensorFlow to a patched release outside the affected version ranges, such as 2.5.0 or later.
- Use TensorFlow nightly builds only if they include commit 4f663d4b8f0bec1b48da6fa091a7d29609980fa4 or later.
- If using tf.raw_ops.ImmutableConst, filter dtype to block tf.resource and tf.variant.
- Check vendor guidance before relying on compensating controls instead of upgrading.
Validation and detection
- Inventory deployed TensorFlow versions against the affected version ranges in the advisory.
- Review code and model pipelines for direct use of tf.raw_ops.ImmutableConst.
- Confirm any ImmutableConst usage rejects tf.resource and tf.variant dtype values.
- Assess whether untrusted users can submit TensorFlow code, graphs, or models for execution.
- Track remediation evidence to the TensorFlow advisory and patch commit.
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-681: Exact CWE lookup
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Open ATT&CK lookupCVE-2021-29539 mapping review
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Open ATT&CK lookup- 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
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:H/PR:L/UI:N/S:U/C:N/I:N/A:L11.4Primary CVE scoreVulnerability scoring details
Base CVSS 3.1 score
2.5LowVector: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
Source materials
- CVE List V5 sourceCVE List V5
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-g4h2-gqm3-c9wqCVE reference · x_refsource_CONFIRM
- https://github.com/tensorflow/tensorflow/commit/4f663d4b8f0bec1b48da6fa091a7d29609980fa4CVE 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.
Incorrect Conversion between Numeric Types
Incorrect Conversion between Numeric Types represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.