Security readout for executives and security teams
Plain-English summary
CVE-2021-29566 is a low-severity TensorFlow memory safety bug. A user who can run TensorFlow operations locally could pass invalid arguments to Dilation2DBackpropInput and cause a heap out-of-bounds write. The published impact is limited to availability, with high attack complexity and required local privileges.
Executive priority
Treat as routine remediation unless TensorFlow runs in shared or semi-trusted ML environments. Prioritize normal patch cycles and dependency hygiene; escalate only where untrusted users can submit TensorFlow workloads.
Technical view
TensorFlow failed to validate input-derived indices before writing to the Dilation2DBackpropInput output buffer. h_out and w_out were bounded by out_backprop, but h_in_max and w_in_max were not similarly guaranteed for in_backprop. The issue is classified as CWE-787 with CVSS 3.1 score 2.5.
Likely exposure
Exposure is most relevant in environments running affected TensorFlow versions where untrusted or low-privileged users can execute TensorFlow code, jobs, notebooks, or model logic. Single-user controlled ML pipelines have lower practical exposure.
Exploitation context
The source bundle does not show KEV listing or active exploitation. Exploitation requires local access, low privileges, no user interaction, and high complexity. The documented security impact is availability loss, not confidentiality or integrity compromise.
Researcher notes
The bug is a heap out-of-bounds write in TensorFlow core kernel code for Dilation2DBackpropInput. The advisory names invalid arguments as the trigger condition, but the provided sources do not include exploitation evidence or broader product impact beyond TensorFlow.
Mitigation direction
- Upgrade to TensorFlow 2.5.0 or a fixed supported patch release.
- Use TensorFlow 2.4.2, 2.3.3, 2.2.3, or 2.1.4 where applicable.
- Restrict untrusted users from executing arbitrary TensorFlow operations on shared systems.
- Check current vendor guidance for unsupported TensorFlow versions.
Validation and detection
- Inventory deployed TensorFlow versions in applications, notebooks, containers, and training images.
- Compare versions against the affected ranges listed in the advisory.
- Identify shared ML environments that permit untrusted TensorFlow code execution.
- Confirm upgraded environments report a fixed TensorFlow release.
- Review dependency lockfiles and container images for stale TensorFlow packages.
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-787: 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-2021-29566 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-pvrc-hg3f-58r6CVE reference · x_refsource_CONFIRM
- https://github.com/tensorflow/tensorflow/commit/3f6fe4dfef6f57e768260b48166c27d148f3015fCVE 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 Write
Out-of-bounds Write represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.