In TensorFlow before 1.15.2 and 2.0.1, converting a string (from Python) to a tf.float16 value results in a segmentation fault in eager mode as the format checks for this use case are only in the graph mode. This issue can lead to denial of service in inference/training where a malicious attacker can send a data point which contains a string instead of a tf.float16 value. Similar effects can be obtained by manipulating saved models and checkpoints whereby replacing a scalar tf.float16 value with a scalar string will trigger this issue due to automatic conversions. This can be easily reproduced by tf.constant("hello", tf.float16), if eager execution is enabled. This issue is patched in TensorFlow 1.15.1 and 2.0.1 with this vulnerability patched. TensorFlow 2.1.0 was released after we fixed the issue, thus it is not affected. Users are encouraged to switch to TensorFlow 1.15.1, 2.0.1 or 2.1.0.
CVE-2020-5215
This medium-severity CVE scores 5.0 under NVD CVSS v3. EPSS exploit probability: 0.6%, top 56% 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).
- Lower severity and no public exploit yet
No vendor fix yet — apply a workaround or compensating control (WAF / firewall / segmentation) and watch for a patch.
- CVSS v3
- 5.0
- EG Score
- 5.0(medium)
- EG Risk
- 27(Track)EG Risk 27/100SSVC: 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 computedSeverity50% × 45%Exploitation1% × 40%Automatability30% × 15%Action: Routine — remediate on your standard cadence. - EPSS
- 44.2%
- KEV
- Not listed
Published
January 28, 2020
Last Modified
November 21, 2024
References (8)
- security-advisories@githubhttps://github.com/tensorflow/tensorflow/commit/5ac1b9e24ff6afc465756edf845d2e9660bd34bf
- security-advisories@githubhttps://github.com/tensorflow/tensorflow/releases/tag/v1.15.2
- security-advisories@githubhttps://github.com/tensorflow/tensorflow/releases/tag/v2.0.1
- security-advisories@githubhttps://github.com/tensorflow/tensorflow/security/advisories/GHSA-977j-xj7q-2jr9
- af854a3a-2127-422b-91ae-364da2661108https://github.com/tensorflow/tensorflow/commit/5ac1b9e24ff6afc465756edf845d2e9660bd34bf
- af854a3a-2127-422b-91ae-364da2661108https://github.com/tensorflow/tensorflow/releases/tag/v1.15.2
- af854a3a-2127-422b-91ae-364da2661108https://github.com/tensorflow/tensorflow/releases/tag/v2.0.1
- af854a3a-2127-422b-91ae-364da2661108https://github.com/tensorflow/tensorflow/security/advisories/GHSA-977j-xj7q-2jr9
Affected Packages
(3 across 1 ecosystem)
PyPI(3)
| Package | Vulnerable range | Fixed in | Dependents |
|---|---|---|---|
| tensorflow | 0.12.0 ... 2.0.0 (69 versions) | 2.0.1 | — |
| tensorflow-cpu | 1.15.0 | 2.0.1 | — |
| tensorflow-gpu | 0.12.0 ... 2.0.0 (28 versions) | 2.0.1 | — |
Weakness Classification(2)
MITRE Common Weakness Enumeration — the root-cause categories this CVE belongs to.
Data Freshness Timeline
(refreshed 14× in last 7d / 52× 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.
Showing the most recent 100 of 103 total refreshes for this CVE.
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Related CVEs(same CWE)
Frequently asked(5)
What is CVE-2020-5215?
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What is the CVSS score of CVE-2020-5215?
How do I remediate CVE-2020-5215?
Dependency Blast Radius
See which npm, PyPI, Go, and Maven packages are affected by CVE-2020-5215
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