Security readout for executives and security teams
Plain-English summary
A flaw in TensorFlow's SdcaOptimizer operation can trigger undefined behavior from a null pointer dereference. The documented impact is limited availability loss, not data theft or data modification. Business urgency is highest for platforms that let users run or submit TensorFlow workloads.
Executive priority
Schedule remediation through standard dependency management. Escalate sooner for multi-tenant ML platforms or services accepting untrusted TensorFlow workloads, where a process crash could affect other users or production jobs.
Technical view
CVE-2021-29572 is a CWE-476 null pointer dereference in tf.raw_ops.SdcaOptimizer. The op did not validate user-supplied arguments against required constraints, allowing undefined behavior. CVSS 3.1 is 2.5: local attack vector, high complexity, low privileges, no confidentiality or integrity impact, and low availability impact.
Likely exposure
Exposure is likely limited to TensorFlow environments using affected versions and allowing low-privileged local users, notebooks, jobs, or submitted models to invoke TensorFlow operations. Systems that do not run TensorFlow, or do not accept untrusted TensorFlow workloads, have lower practical exposure.
Exploitation context
The source bundle does not show active exploitation, and CISA KEV status is false. Exploitation requires local access with low privileges and high complexity. Treat it mainly as a denial-of-service risk in shared ML execution environments.
Researcher notes
The public advisory attributes the bug to missing validation in SdcaOptimizer and a null pointer dereference in sdca_internal.cc. The fix is linked to a TensorFlow commit. The provided evidence does not include exploit availability, weaponization, or broader impact beyond low availability loss.
Mitigation direction
- Upgrade TensorFlow to 2.5.0 or later where practical.
- For supported older branches, use 2.4.2, 2.3.3, 2.2.3, or 2.1.4.
- Restrict untrusted users from running arbitrary TensorFlow operations in shared environments.
- Review vendor guidance before applying compensating controls not stated in the advisory.
Validation and detection
- Inventory TensorFlow versions across applications, notebooks, containers, and ML job images.
- Flag versions below 2.1.4 or vulnerable 2.2.x, 2.3.x, and 2.4.x ranges.
- Confirm whether workloads can invoke tf.raw_ops.SdcaOptimizer with user-controlled inputs.
- Verify upgraded environments report a fixed TensorFlow release.
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
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ATT&CK lookup starting points
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CWE-476: Exact CWE lookup
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Open ATT&CK lookupCVE-2021-29572 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-5gqf-456p-4836CVE reference · x_refsource_CONFIRM
- https://github.com/tensorflow/tensorflow/commit/f7cc8755ac6683131fdfa7a8a121f9d7a9dec6fbCVE 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.