Security readout for executives and security teams
Plain-English summary
This is a low-severity TensorFlow bug in a matrix-solving operation. A failed validation check could let kernel execution continue and read beyond expected memory. The published impact is limited availability loss, not data theft or tampering. Exposure matters mainly where users can run TensorFlow workloads or submit models/tensors to a service.
Executive priority
Low priority unless TensorFlow is used in multi-tenant or user-submitted ML workloads. Schedule patching through normal dependency maintenance, but do not defer indefinitely on shared compute platforms.
Technical view
CVE-2021-29551 is a CWE-125 out-of-bounds read in TensorFlow MatrixTriangularSolve. The implementation did not terminate execution after one validation failure. CVSS 3.1 is 2.5 with local access, high attack complexity, low privileges, no user interaction, and low availability impact only.
Likely exposure
Systems using TensorFlow versions before 2.1.4, 2.2.0 through before 2.2.3, 2.3.0 through before 2.3.3, or 2.4.0 through before 2.4.2 may be exposed. Risk is higher for shared ML platforms accepting untrusted workloads or tensor inputs.
Exploitation context
The source bundle does not show CISA KEV listing or active exploitation. The CVSS vector requires local access and low privileges, with high complexity. Treat it as a maintenance and tenant-isolation concern rather than an internet-scale emergency.
Researcher notes
Focus validation on version presence and trust boundaries around TensorFlow execution. The public description identifies the bug class and fixed releases but does not provide evidence of exploitation in the wild or broader product impact beyond TensorFlow.
Mitigation direction
- Upgrade to TensorFlow 2.5.0 or a fixed supported branch release.
- Use TensorFlow 2.4.2, 2.3.3, 2.2.3, or 2.1.4 where branch pinning is required.
- Check vendor advisory and commit notes before changing production ML runtimes.
- Restrict untrusted users from submitting arbitrary TensorFlow workloads on shared infrastructure.
Validation and detection
- Inventory TensorFlow versions in applications, notebooks, containers, and ML-serving images.
- Confirm no affected version ranges remain in deployed runtime environments.
- Prioritize shared platforms where low-privileged users can execute TensorFlow operations.
- Review dependency locks and base images for transitive TensorFlow inclusion.
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
These mappings and lookup hints may be relevant to the vulnerability behavior, CWE, affected product, or exposure path. Glexia-inferred context is not an official MITRE, ATT&CK, CWE, or CVE Program mapping.
ATT&CK lookup starting points
Use these exact CWE pages and searches to review the Glexia ATT&CK library from this CVE's weakness and description context.
CWE-125: Exact CWE lookup
Use the exact CWE identifier as the starting point before reviewing related ATT&CK behavior. Open the exact CWE lookup page first, then review the ATT&CK searches from that MITRE weakness context. This is a Glexia lookup hint, not an official ATT&CK mapping.
Open ATT&CK lookupCVE-2021-29551 mapping review
Open the CVE-to-ATT&CK bridge for reviewed, inferred, or future official mappings tied to this CVE.
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-vqw6-72r7-fgw7CVE reference · x_refsource_CONFIRM
- https://github.com/tensorflow/tensorflow/commit/480641e3599775a8895254ffbc0fc45621334f68CVE 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.
Out-of-bounds Read
Out-of-bounds Read represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.