Security readout for executives and security teams
Plain-English summary
This TensorFlow flaw can let a local, low-privileged attacker crash affected TensorFlow processing through the IRFFT raw operation. The documented impact is limited availability loss, not data theft or code execution. It is low severity but relevant where untrusted users or jobs can run TensorFlow workloads.
Executive priority
Treat this as a low-priority patching item unless TensorFlow runs in shared or user-submitted workload environments. It should be remediated through normal dependency maintenance, with higher urgency for multi-tenant ML platforms.
Technical view
CVE-2021-29562 is a CWE-617 reachable CHECK failure in tf.raw_ops.IRFFT. Affected TensorFlow versions are 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. The CVSS 3.1 score is 2.5 with local attack vector and low availability impact.
Likely exposure
Exposure is most likely in ML services, notebooks, batch workers, or shared compute environments running affected TensorFlow versions where low-privileged users or submitted jobs can exercise TensorFlow operations.
Exploitation context
The source bundle does not show active exploitation, and KEV status is false. The CVSS vector requires local access, high attack complexity, and low privileges. The stated consequence is denial of service from a CHECK failure.
Researcher notes
The issue is specifically tied to tf.raw_ops.IRFFT and a CHECK failure. The referenced commit is the authoritative fix point for code review and backport verification. Sources do not support claims of remote code execution, data exposure, or active exploitation.
Mitigation direction
- Upgrade TensorFlow to 2.5.0 or fixed supported branches: 2.4.2, 2.3.3, 2.2.3, or 2.1.4.
- Check vendor advisory guidance before choosing any unsupported workaround.
- Limit untrusted users or jobs from executing TensorFlow workloads until patched.
- Prioritize shared ML platforms over isolated developer machines.
Validation and detection
- Inventory TensorFlow versions in applications, notebooks, containers, and lockfiles.
- Confirm deployed versions are outside the affected ranges listed in the advisory.
- Review dependency scanners for CVE-2021-29562 coverage and stale TensorFlow packages.
- Check ML service logs for unexplained TensorFlow process crashes.
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-617: 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-2021-29562 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-36vm-xw34-x4pjCVE reference · x_refsource_CONFIRM
- https://github.com/tensorflow/tensorflow/commit/1c56f53be0b722ca657cbc7df461ed676c8642a2CVE 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.
Reachable Assertion
Reachable Assertion represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.
