| CVE-ID | ||
|---|---|---|
CVE-2020-5215 |
• CVSS Severity Rating • Fix Information • Vulnerable Software Versions • SCAP Mappings • CPE Information
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| 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. | ||
| References | ||
| Note: References are provided for the convenience of the reader to help distinguish between vulnerabilities. The list is not intended to be complete. | ||
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| Assigning CNA | ||
| GitHub (maintainer security advisories) | ||
| Date Record Created | ||
| 20200102 | Disclaimer: The record creation date may reflect when the CVE ID was allocated or reserved, and does not necessarily indicate when this vulnerability was discovered, shared with the affected vendor, publicly disclosed, or updated in CVE. | |
| Phase (Legacy) | ||
| Assigned (20200102) | ||
| Votes (Legacy) | ||
| Comments (Legacy) | ||
| Proposed (Legacy) | ||
| N/A | ||
| This is an record on the CVE List, which provides common identifiers for publicly known cybersecurity vulnerabilities. | ||
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