Security readout for executives and security teams
Plain-English summary
CVE-2021-29543 is a low-severity TensorFlow denial-of-service flaw. A local, low-privileged attacker who can reach a vulnerable CTC greedy decoder path may cause the process to abort instead of returning a normal error. The direct business risk is service interruption in affected machine learning workloads, not data theft or system takeover.
Executive priority
Treat this as routine patching unless vulnerable TensorFlow decoding is exposed in production workflows. Prioritize internet-facing or multi-tenant ML services first, but the source evidence supports low business urgency compared with code execution or data exposure vulnerabilities.
Technical view
The issue is a CWE-617 reachable assertion in tf.raw_ops.CTCGreedyDecoder. TensorFlow used a CHECK_LT invariant check in ctc_decoder_ops.cc; when false, TensorFlow aborts. Affected ranges include TensorFlow versions below listed patched releases: 2.1.4, 2.2.3, 2.3.3, and 2.4.2, with the fix also included in 2.5.0.
Likely exposure
Exposure is most likely in applications, services, notebooks, or batch ML jobs running affected TensorFlow versions and using CTC greedy decoding. The CVSS vector indicates local access, high attack complexity, and low privileges are required, with availability impact only.
Exploitation context
The provided sources describe denial-of-service potential through abnormal process termination. They do not report active exploitation, and the CVE is not listed as KEV in the provided bundle. No evidence here supports remote exploitation, confidentiality loss, or integrity impact.
Researcher notes
The key behavior is a reachable CHECK failure rather than graceful error handling. Analysis should stay focused on version confirmation, affected decoder usage, and availability blast radius. The provided evidence does not establish exploit prevalence or broader product impact beyond TensorFlow.
Mitigation direction
- Upgrade TensorFlow to 2.5.0 or supported patched branch versions 2.4.2, 2.3.3, 2.2.3, or 2.1.4.
- Review the TensorFlow advisory before relying on branch-specific remediation.
- Restrict untrusted access to ML workflows using CTC greedy decoding until patched.
- Rebuild containers or runtime images that bundle affected TensorFlow versions.
Validation and detection
- Inventory TensorFlow versions in applications, containers, notebooks, and ML worker images.
- Check whether code paths invoke tf.raw_ops.CTCGreedyDecoder or CTC decoder wrappers.
- Confirm dependency lockfiles and runtime environments resolve to patched TensorFlow versions.
- Review service restart or crash telemetry for unexplained TensorFlow process aborts.
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
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
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Open ATT&CK lookupCVE-2021-29543 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-fphq-gw9m-ghrvCVE reference · x_refsource_CONFIRM
- https://github.com/tensorflow/tensorflow/commit/ea3b43e98c32c97b35d52b4c66f9107452ca8fb2CVE 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.