CVE-2021-37657

HIGHNVD 7.17.1—
EchelonGraph scoreMEDIUM confidence

This high-severity CVE scores 7.1 under NVD CVSS v3. EPSS exploit probability: 0.2%, top 94% of all CVEs by exploit prediction. GitHub Security Advisory data not yet ingested — confidence will rise once GHSA publishes (typical lag: hours to days for open-source ecosystem CVEs; never for infrastructure-only CVEs).

Triggered by: NVD CVSS baseline
Sources: epss, nvd
Trending — 3 sources updated this week
7.1
EchelonGraph verdictPlan a fixSerious severity, but no confirmed exploitation yet.
  • High severity, but no confirmed exploitation yet
CISA-KEV: Not listedEPSS: 0%CVSS: 7.1Exploit: NoneExposed: 0

No vendor fix yet — apply a workaround or compensating control (WAF / firewall / segmentation) and watch for a patch.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type tf.raw_ops.MatrixDiagV*. The implementation has incomplete validation that the value of k is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

CVSS v3
7.1
EG Score
7.1(medium)
EG Risk
—
EPSS
6.4%
KEV
Not listed

Published

August 12, 2021

Last Modified

November 21, 2024

References (4)

Affected Packages

(3 across 1 ecosystem)
PyPI(3)
PackageVulnerable rangeFixed inDependents
tensorflow2.3.0 ... 2.4.2 (7 versions)2.4.3—
tensorflow-cpu2.3.0 ... 2.4.2 (7 versions)2.4.3—
tensorflow-gpu2.3.0 ... 2.4.2 (7 versions)2.4.3—

Weakness Classification(1)

MITRE Common Weakness Enumeration — the root-cause categories this CVE belongs to.

Data Freshness Timeline

(refreshed 14× in last 7d / 46× in last 30d)

Each row is a source pipeline that fetched or updated this CVE on that date, with what changed. For example, "NVD update" means NVD published or revised its analysis for this CVE; "MITRE cvelistV5" means we ingested or refreshed it from the CNA feed. Most recent first.

  1. 2026-07-22 22:49 UTCEG score recompute
  2. 2026-07-22 14:06 UTCEPSS rescore
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  1. 2026-07-06 16:25 UTCEPSS rescore
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  38. 2026-06-13 00:14 UTCOSV refresh
  39. 2026-06-12 23:10 UTCEPSS rescore
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  72. 2026-05-26 12:07 UTCEG score recompute
  73. 2026-05-26 07:17 UTCEPSS rescore
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Frequently asked(5)

What is CVE-2021-37657?
CVE-2021-37657 is a high vulnerability published on August 12, 2021. TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type tf.rawops.MatrixDiagV*. The implementation has incomplete validation that the value of k is a valid…
When was CVE-2021-37657 disclosed?
CVE-2021-37657 was first published in the National Vulnerability Database on August 12, 2021, with the most recent update on November 21, 2024. EchelonGraph re-ingests CVE updates from NVD on a 2-hour cycle, so this page reflects the latest published state.
Is CVE-2021-37657 actively exploited?
CVE-2021-37657 is not currently on CISA's Known Exploited Vulnerabilities catalog. FIRST EPSS estimates a 6.4% percentile likelihood of exploitation in the next 30 days — higher percentiles indicate greater predicted risk.
What is the CVSS score of CVE-2021-37657?
CVE-2021-37657 has a CVSS v3 base score of 7.1 (NVD).
How do I remediate CVE-2021-37657?
Patch to the fixed version published by the affected vendor. Where vendor advisories exist for CVE-2021-37657, EchelonGraph cross-links them in the Vendor Advisories panel below — those typically contain the canonical remediation steps, fixed version numbers, and any vendor-specific mitigations.

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