CVE-2020-15196

HIGHNVD 8.58.5
EchelonGraph scoreLOW confidence

This high-severity CVE scores 8.5 under NVD CVSS v3. EPSS exploit-prediction score not yet available (the EPSS model rescores nightly; freshly-published CVEs typically appear within 48 hours). 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: nvd
8.5
EchelonGraph verdictPlan a fixSerious severity, but no confirmed exploitation yet.
  • High severity, but no confirmed exploitation yet
CISA-KEV: Not listedEPSS: 1%CVSS: 8.5Exploit: NoneExposed: 0

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

In Tensorflow version 2.3.0, the SparseCountSparseOutput and RaggedCountSparseOutput implementations don't validate that the weights tensor has the same shape as the data. The check exists for DenseCountSparseOutput, where both tensors are fully specified. In the sparse and ragged count weights are still accessed in parallel with the data. But, since there is no validation, a user passing fewer weights than the values for the tensors can generate a read from outside the bounds of the heap buffer allocated for the weights. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.

CVSS v3
8.5
EG Score
8.5(low)
EPSS
56.0%
KEV
Not listed

Published

September 25, 2020

Last Modified

November 21, 2024

References (6)

Affected Packages

(3 across 1 ecosystem)
PyPI(3)
PackageVulnerable rangeFixed inDependents
tensorflow0.12.0rc0 ... 2.2.3 (104 versions)2.3.1—
tensorflow-cpu1.15.0 ... 2.3.0 (11 versions)2.3.1—
tensorflow-gpu0.12.0 ... 2.3.0 (46 versions)2.3.1—

Weakness Classification(3)

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

Data Freshness Timeline

(refreshed 10× in last 7d / 45× 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 14:05 UTCEPSS rescore
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  1. 2026-07-06 16:25 UTCEPSS rescore
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  18. 2026-06-24 11:50 UTCOSV refresh
  19. 2026-06-23 21:31 UTCEPSS rescore
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  21. 2026-06-22 14:23 UTCEPSS rescore
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  44. 2026-06-07 15:46 UTCOSV refresh
  45. 2026-06-07 15:23 UTCEPSS rescore
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  71. 2026-05-23 07:13 UTCEG score recompute

Frequently asked(5)

What is CVE-2020-15196?
CVE-2020-15196 is a high vulnerability published on September 25, 2020. In Tensorflow version 2.3.0, the SparseCountSparseOutput and RaggedCountSparseOutput implementations don't validate that the weights tensor has the same shape as the data. The check exists for DenseCountSparseOutput, where both tensors are fully specified. In the sparse and ragged count weights are…
When was CVE-2020-15196 disclosed?
CVE-2020-15196 was first published in the National Vulnerability Database on September 25, 2020, 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-2020-15196 actively exploited?
CVE-2020-15196 is not currently on CISA's Known Exploited Vulnerabilities catalog. FIRST EPSS estimates a 56.0% percentile likelihood of exploitation in the next 30 days — higher percentiles indicate greater predicted risk.
What is the CVSS score of CVE-2020-15196?
CVE-2020-15196 has a CVSS v3 base score of 8.5 (NVD). The EG score is currently aggregating — additional source signals are being incorporated as they become available..
How do I remediate CVE-2020-15196?
Patch to the fixed version published by the affected vendor. Where vendor advisories exist for CVE-2020-15196, 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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