In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the Shard API in TensorFlow expects the last argument to be a function taking two int64 (i.e., long long) arguments. However, there are several places in TensorFlow where a lambda taking int or int32 arguments is being used. In these cases, if the amount of work to be parallelized is large enough, integer truncation occurs. Depending on how the two arguments of the lambda are used, this can result in segfaults, read/write outside of heap allocated arrays, stack overflows, or data corruption. The issue is patched in commits 27b417360cbd671ef55915e4bb6bb06af8b8a832 and ca8c013b5e97b1373b3bb1c97ea655e69f31a575, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
CVE-2020-15202
This critical-severity CVE scores 9.0 under NVD CVSS v3. EPSS exploit probability: 1.2%, top 34% 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).
- High severity, but no confirmed exploitation yet
No vendor fix yet — apply a workaround or compensating control (WAF / firewall / segmentation) and watch for a patch.
- CVSS v3
- 9.0
- EG Score
- 9.0(medium)
- EG Risk
- 45(Track)EG Risk 45/100SSVC: Track
EG Risk is EchelonGraph's 0–100 priority score: it fuses intrinsic severity with real-world exploitation and automatability so you can rank equal-severity CVEs and fix the most dangerous first. Higher = act sooner. Distinct from the 0–10 EG Score (severity).
How it’s computedSeverity90% × 45%Exploitation1% × 40%Automatability30% × 15%Action: Routine — remediate on your standard cadence. - EPSS
- 65.9%
- KEV
- Not listed
Published
September 25, 2020
Last Modified
November 21, 2024
References (10)
- security-advisories@githubhttp://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html
- security-advisories@githubhttps://github.com/tensorflow/tensorflow/commit/27b417360cbd671ef55915e4bb6bb06af8b8a832
- security-advisories@githubhttps://github.com/tensorflow/tensorflow/commit/ca8c013b5e97b1373b3bb1c97ea655e69f31a575
- security-advisories@githubhttps://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
- security-advisories@githubhttps://github.com/tensorflow/tensorflow/security/advisories/GHSA-h6fg-mjxg-hqq4
- af854a3a-2127-422b-91ae-364da2661108http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html
- af854a3a-2127-422b-91ae-364da2661108https://github.com/tensorflow/tensorflow/commit/27b417360cbd671ef55915e4bb6bb06af8b8a832
- af854a3a-2127-422b-91ae-364da2661108https://github.com/tensorflow/tensorflow/commit/ca8c013b5e97b1373b3bb1c97ea655e69f31a575
- af854a3a-2127-422b-91ae-364da2661108https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
- af854a3a-2127-422b-91ae-364da2661108https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h6fg-mjxg-hqq4
Affected Packages
(3 across 1 ecosystem)
PyPI(3)
| Package | Vulnerable range | Fixed in | Dependents |
|---|---|---|---|
| tensorflow | 0.12.0rc0 ... 2.3.0 (77 versions) | 2.3.1 | — |
| tensorflow-cpu | 1.15.0, 2.1.0, 2.1.1, 2.2.0, 2.3.0 | 2.3.1 | — |
| tensorflow-gpu | 0.12.0 ... 2.3.0 (36 versions) | 2.3.1 | — |
Weakness Classification(2)
MITRE Common Weakness Enumeration — the root-cause categories this CVE belongs to.
Data Freshness Timeline
(refreshed 11× 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.
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Related CVEs(same CWE)
Same CWE
10 shownCWE-754
Frequently asked(5)
What is CVE-2020-15202?
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What is the CVSS score of CVE-2020-15202?
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Dependency Blast Radius
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