CVE & CISA-KEV Catalog

CVE-2020-5215

MEDIUM
5.0
CVSS v3
NVD

Description

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.

How to fix

Remediation Available
tensorflowNVD
Affected:>= 2.0.0, < 2.0.1Fixed in:2.0.1CVE-2020-5215derived from NVD

Remediation is compiled from vendor and distribution security advisories. Always confirm against the linked source for your exact version and platform.

CVSS v3 Vector

Exploitability

Attack VectorLocal
Attack ComplexityHigh
Privileges RequiredLow
User InteractionRequired
ScopeChanged

Impact

ConfidentialityLow
IntegrityLow
AvailabilityLow

CVSS:3.1/AV:L/AC:H/PR:L/UI:R/S:C/C:L/I:L/A:L

Exploit Intelligence

0.58%probability of exploitation in 30 days
44thpercentile

Moderate risk: more likely to be exploited than 44% of all known CVEs.

References

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This product uses NVD data but is not endorsed or certified by the NVD. EPSS scores courtesy of FIRST.org (https://www.first.org/epss). Source: CISA KEV Catalog. Data as of 2024-11-21.