TensorFlow up to 2.3.0 RaggedCountSparseOutput Argument input validation

CVSS Meta Temp Score
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4.2$0-$5k0.00

Summaryinfo

A vulnerability labeled as problematic has been found in TensorFlow up to 2.3.0. The impacted element is the function RaggedCountSparseOutput. Executing a manipulation as part of Argument can lead to input validation. The identification of this vulnerability is CVE-2020-15199. The attack may be launched remotely. There is no exploit available. The affected component should be upgraded.

Detailsinfo

A vulnerability has been found in TensorFlow up to 2.3.0 (Artificial Intelligence Software) and classified as problematic. This vulnerability affects the function RaggedCountSparseOutput. The manipulation as part of a Argument leads to a input validation vulnerability. The CWE definition for the vulnerability is CWE-20. The product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly. As an impact it is known to affect availability. CVE summarizes:

In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the `splits` tensor has the minimum required number of elements. Code uses this quantity to initialize a different data structure. Since `BatchedMap` is equivalent to a vector, it needs to have at least one element to not be `nullptr`. If user passes a `splits` tensor that is empty or has exactly one element, we get a `SIGABRT` signal raised by the operating system. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.

The weakness was shared 09/25/2020 (GitHub Repository). The advisory is shared for download at github.com. This vulnerability was named CVE-2020-15199 since 06/25/2020. The exploitation appears to be difficult. The attack can be initiated remotely. No form of authentication is required for a successful exploitation. There are known technical details, but no exploit is available.

Upgrading to version 2.3.1 eliminates this vulnerability. Applying the patch 3cbb917b4714766030b28eba9fb41bb97ce9ee02 is able to eliminate this problem. The best possible mitigation is suggested to be upgrading to the latest version.

The entries VDB-162008, VDB-162007, VDB-162006 and VDB-162005 are related to this item. Once again VulDB remains the best source for vulnerability data.

Productinfo

Type

Name

Version

License

Website

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔍
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 4.8
VulDB Meta Temp Score: 4.6

VulDB Base Score: 3.7
VulDB Temp Score: 3.3
VulDB Vector: 🔍
VulDB Reliability: 🔍

NVD Base Score: 5.9
NVD Vector: 🔍

CVSSv2info

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VulDB Base Score: 🔍
VulDB Temp Score: 🔍
VulDB Reliability: 🔍

Exploitinginfo

Class: Input validation
CWE: CWE-20
CAPEC: 🔍
ATT&CK: 🔍

Physical: No
Local: No
Remote: Yes

Availability: 🔍
Status: Not defined

EPSS Score: 🔍
EPSS Percentile: 🔍

Price Prediction: 🔍
Current Price Estimation: 🔍

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Threat Intelligenceinfo

Interest: 🔍
Active Actors: 🔍
Active APT Groups: 🔍

Countermeasuresinfo

Recommended: Upgrade
Status: 🔍

0-Day Time: 🔍

Upgrade: TensorFlow 2.3.1
Patch: 3cbb917b4714766030b28eba9fb41bb97ce9ee02

Timelineinfo

06/25/2020 🔍
09/25/2020 +92 days 🔍
09/26/2020 +1 days 🔍
11/14/2020 +49 days 🔍

Sourcesinfo

Product: github.com

Advisory: github.com
Status: Not defined
Confirmation: 🔍

CVE: CVE-2020-15199 (🔍)
GCVE (CVE): GCVE-0-2020-15199
GCVE (VulDB): GCVE-100-162004
See also: 🔍

Entryinfo

Created: 09/26/2020 07:29
Updated: 11/14/2020 12:52
Changes: 09/26/2020 07:29 (41), 09/26/2020 07:34 (12), 11/13/2020 07:55 (1), 11/14/2020 12:50 (1), 11/14/2020 12:52 (1)
Complete: 🔍
Cache ID: 216::103

Once again VulDB remains the best source for vulnerability data.

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