Security readout for executives and security teams
Plain-English summary
CVE-2021-29590 is a low-severity TensorFlow Lite bug. Under specific conditions, the Minimum or Maximum operators can read past a heap allocation when an input tensor is empty. The sourced impact is limited to availability, not data theft or tampering.
Executive priority
Treat this as routine patch management unless your product processes untrusted ML inputs with affected TensorFlow Lite builds. The business risk is low, but embedded or bundled ML components can be missed in normal dependency inventories.
Technical view
TFLite Minimum and Maximum broadcasting indexed both tensors with the same index without confirming bounds when either input tensor was empty. This created a CWE-125 heap out-of-bounds read. Affected TensorFlow ranges include versions before patched 2.1.4, 2.2.3, 2.3.3, and 2.4.2 releases.
Likely exposure
Exposure is most likely where applications use affected TensorFlow Lite versions and process attacker-influenced models or tensor inputs. The CVSS vector is local, high complexity, low privileges required, no user interaction, and availability-only impact.
Exploitation context
The source bundle does not show active exploitation, and KEV is false. Exploitation evidence is incomplete beyond the vendor advisory and fix commit. Any real risk depends on whether untrusted inputs can reach the affected TFLite operators.
Researcher notes
The advisory ties the issue to empty tensor handling in TFLite Minimum and Maximum broadcasting. CVSS 2.5 indicates local, high-complexity exploitation with availability impact only. Do not assume broader TensorFlow operator exposure without confirming affected TFLite code paths.
Mitigation direction
- Upgrade TensorFlow to 2.5.0 or a patched supported maintenance release.
- Use TensorFlow 2.4.2, 2.3.3, 2.2.3, or 2.1.4 where applicable.
- Check vendor guidance if running unsupported TensorFlow versions older than these branches.
- Limit untrusted model or tensor input processing until affected deployments are patched.
Validation and detection
- Inventory applications and embedded components using TensorFlow Lite.
- Identify TensorFlow versions matching the listed affected ranges.
- Review whether Minimum or Maximum TFLite operators process attacker-influenced inputs.
- Confirm patched versions are deployed in build manifests and runtime artifacts.
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
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CWE-125: Exact CWE lookup
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Open ATT&CK lookupCVE-2021-29590 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-24x6-8c7m-hv3fCVE reference · x_refsource_CONFIRM
- https://github.com/tensorflow/tensorflow/commit/953f28dca13c92839ba389c055587cfe6c723578CVE 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.