Security readout for executives and security teams
Plain-English summary
This TensorFlow flaw can crash affected workloads when a user-controlled tensor reaches the Reverse operation. It affects availability only, not data confidentiality or integrity. The published severity is low because exploitation requires local access or a constrained path to influence TensorFlow inputs.
Executive priority
Treat as routine patch management unless affected TensorFlow workloads process untrusted inputs in shared or customer-facing environments. Business risk is limited to service disruption, but ML platforms with multi-user execution should remediate promptly.
Technical view
CVE-2021-29556 is a division-by-zero flaw in TensorFlow's tf.raw_ops.Reverse implementation. The vulnerable code divides using the tensor argument's first dimension, causing a floating point exception runtime error and denial of service under specific input conditions.
Likely exposure
Exposure is most likely in applications running affected TensorFlow versions and allowing untrusted users, plugins, or jobs to influence tensors processed by tf.raw_ops.Reverse. Sources do not identify broader affected products beyond TensorFlow.
Exploitation context
The CVSS vector is local, high complexity, low privileges, and availability-only impact. CISA KEV status is false in the supplied bundle, and no cited source states active exploitation.
Researcher notes
The evidence supports a narrow TensorFlow availability issue in tf.raw_ops.Reverse caused by division by zero. Do not assume remote exploitability from the sources. The commit reference is the authoritative code-level fix indicator; GHSA provides affected and patched release guidance.
Mitigation direction
- Upgrade to TensorFlow 2.5.0 or later where the fix is included.
- For supported older branches, apply TensorFlow 2.4.2, 2.3.3, 2.2.3, or 2.1.4.
- Check TensorFlow advisory GHSA-fxqh-cfjm-fp93 before choosing a remediation path.
- Restrict untrusted access to TensorFlow jobs that can submit arbitrary tensors.
Validation and detection
- Inventory TensorFlow package versions across production, CI, notebooks, and model-serving containers.
- Flag versions below 2.1.4, 2.2.3, 2.3.3, or 2.4.2 as applicable.
- Confirm upgraded builds include TensorFlow 2.5.0 or the listed patched branch release.
- Review services for user-controlled tensor inputs reaching Reverse operations.
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-369: Exact CWE lookup
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Open ATT&CK lookupCVE-2021-29556 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-fxqh-cfjm-fp93CVE reference · x_refsource_CONFIRM
- https://github.com/tensorflow/tensorflow/commit/4071d8e2f6c45c1955a811fee757ca2adbe462c1CVE 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.
Divide By Zero
Divide By Zero represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.