IBM Watson Machine Learning on Cloud Pak for Data 4.0/4.5 server-side request forgery

CVSS Meta Temp Score
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CTI Interest Score
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6.5$0-$5k0.00

Summaryinfo

A vulnerability marked as critical has been reported in IBM Watson Machine Learning on Cloud Pak for Data 4.0/4.5. Impacted is an unknown function. Performing a manipulation results in server-side request forgery. This vulnerability is known as CVE-2023-30444. Remote exploitation of the attack is possible. No exploit is available. It is suggested to upgrade the affected component.

Detailsinfo

A vulnerability, which was classified as critical, was found in IBM Watson Machine Learning on Cloud Pak for Data 4.0/4.5 (Cloud Software). This affects an unknown code. The manipulation with an unknown input leads to a server-side request forgery vulnerability. CWE is classifying the issue as CWE-918. The web server receives a URL or similar request from an upstream component and retrieves the contents of this URL, but it does not sufficiently ensure that the request is being sent to the expected destination. This is going to have an impact on confidentiality, integrity, and availability. The summary by CVE is:

IBM Watson Machine Learning on Cloud Pak for Data 4.0 and 4.5 is vulnerable to server-side request forgery (SSRF). This may allow an authenticated attacker to send unauthorized requests from the system, potentially leading to network enumeration or facilitating other attacks. IBM X-Force ID: 253350.

The weakness was published 04/27/2023. It is possible to read the advisory at ibm.com. This vulnerability is uniquely identified as CVE-2023-30444 since 04/08/2023. The technical details are unknown and an exploit is not publicly available.

Upgrading eliminates this vulnerability.

The vulnerability is also documented in the vulnerability database at X-Force (253350). Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

Productinfo

Type

Vendor

Name

Version

License

Website

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔍
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 6.6
VulDB Meta Temp Score: 6.5

VulDB Base Score: 6.3
VulDB Temp Score: 6.0
VulDB Vector: 🔍
VulDB Reliability: 🔍

NVD Base Score: 6.5
NVD Vector: 🔍

CNA Base Score: 7.1
CNA Vector (IBM Corporation): 🔍

CVSSv2info

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

Exploitinginfo

Class: Server-side request forgery
CWE: CWE-918
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: 🔍

Timelineinfo

04/08/2023 🔍
04/27/2023 +19 days 🔍
04/27/2023 +0 days 🔍
05/21/2023 +24 days 🔍

Sourcesinfo

Vendor: ibm.com

Advisory: ibm.com
Status: Confirmed

CVE: CVE-2023-30444 (🔍)
GCVE (CVE): GCVE-0-2023-30444
GCVE (VulDB): GCVE-100-227595
X-Force: 253350

Entryinfo

Created: 04/27/2023 15:44
Updated: 05/21/2023 10:00
Changes: 04/27/2023 15:44 (51), 05/21/2023 10:00 (10)
Complete: 🔍
Cache ID: 216::103

Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

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