Security readout for executives and security teams
Plain-English summary
CVE-2021-29616 is a low-severity TensorFlow bug that can cause a process crash in limited circumstances. The issue is a null pointer dereference in Grappler optimization when handling a node with no inputs. Business urgency is low unless affected TensorFlow versions process untrusted or externally supplied ML graphs or models.
Executive priority
Schedule remediation through normal patch management unless TensorFlow is exposed to untrusted model inputs. The expected impact is service instability or job failure, not compromise of sensitive data. Track completion because patched versions are available from the vendor.
Technical view
TensorFlow Grappler's arithmetic optimizer function TrySimplify can dereference a null pointer in corner cases involving optimization of a node with no inputs. The CVSS 3.1 vector is local, high complexity, low privilege, no confidentiality or integrity impact, and low availability impact.
Likely exposure
Exposure is limited to TensorFlow deployments using affected versions: before 2.1.4, 2.2.x before 2.2.3, 2.3.x before 2.3.3, and 2.4.x before 2.4.2. Risk is most relevant where TensorFlow optimizes graphs or models not fully controlled by the organization.
Exploitation context
The provided sources do not report active exploitation, and the CVE is not listed as KEV. The CVSS vector indicates local access, high attack complexity, and low availability impact. Treat this as a crash risk rather than a data theft or privilege escalation issue.
Researcher notes
The evidence points to CWE-476 null pointer dereference in TensorFlow Grappler TrySimplify. Public sources identify affected version ranges and fixed release targets, but do not provide evidence of exploitation in the wild. Avoid assuming remote exploitability beyond the CVSS local attack vector.
Mitigation direction
- Upgrade TensorFlow to 2.5.0 or later where practical.
- For supported older branches, apply TensorFlow 2.4.2, 2.3.3, 2.2.3, or 2.1.4.
- Prioritize systems that process external or user-supplied TensorFlow graphs or models.
- Check TensorFlow's advisory before using unsupported versions or custom forks.
Validation and detection
- Inventory TensorFlow versions across application, notebook, CI, and ML serving environments.
- Confirm no runtime uses the affected version ranges listed in the advisory.
- Review whether services accept externally supplied TensorFlow graphs or models.
- After upgrade, run existing ML workload and regression tests for compatibility.
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-476: 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-2021-29616 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-4hvv-7x94-7vq8CVE reference · x_refsource_CONFIRM
- https://github.com/tensorflow/tensorflow/commit/e6340f0665d53716ef3197ada88936c2a5f7a2d3CVE 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.
NULL Pointer Dereference
NULL Pointer Dereference represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.