Security readout for executives and security teams
Plain-English summary
CVE-2021-29615 is a low-severity TensorFlow issue where specially crafted input can cause a stack overflow in attribute parsing. The documented impact is limited availability loss, not data theft or code execution. Organizations mainly need to find older TensorFlow deployments and move them to a fixed release line.
Executive priority
Treat as routine patch hygiene unless TensorFlow is exposed to untrusted local users or shared ML environments. It is not an emergency based on available evidence, but unsupported or stale TensorFlow installations should be upgraded during the next maintenance window.
Technical view
TensorFlow's ParseAttrValue implementation used recursive handling that could be driven into stack overflow with nested tensor input. The CVSS 3.1 score is 2.5 with local access, high attack complexity, low privileges, no user interaction, and low availability impact only.
Likely exposure
Exposure is most likely in ML applications, notebooks, services, or containers using TensorFlow versions before the patched 2.1.4, 2.2.3, 2.3.3, 2.4.2, or 2.5.0 releases. Risk depends on whether local or low-privileged users can supply crafted TensorFlow inputs.
Exploitation context
The source bundle does not indicate active exploitation, and the CVE is not listed as KEV. The advisory describes specially crafted input causing stack overflow, but the CVSS vector limits this to local, high-complexity, low-privilege availability impact.
Researcher notes
Focus review on TensorFlow ParseAttrValue behavior and environments accepting nested tensor attributes from untrusted sources. The public record supports denial-of-service analysis only. No source provided evidence of confidentiality impact, integrity impact, remote exploitation, or exploit availability.
Mitigation direction
- Upgrade TensorFlow to 2.5.0 where possible.
- For supported older branches, apply 2.4.2, 2.3.3, 2.2.3, or 2.1.4.
- Check the TensorFlow advisory for branch-specific upgrade guidance.
- Limit untrusted local input paths to TensorFlow parsers until patched.
Validation and detection
- Inventory TensorFlow versions in applications, containers, notebooks, and build manifests.
- Flag versions below 2.1.4, 2.2.3, 2.3.3, or 2.4.2.
- Confirm upgraded environments report a fixed TensorFlow release.
- Review whether local users can provide TensorFlow model or graph inputs.
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-674: Exact CWE lookup
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Open ATT&CK lookupCVE-2021-29615 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-qw5h-7f53-xrp6CVE reference · x_refsource_CONFIRM
- https://github.com/tensorflow/tensorflow/commit/e07e1c3d26492c06f078c7e5bf2d138043e199c1CVE 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.
Uncontrolled Recursion
Uncontrolled Recursion represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.