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CVE-2014-0894

3.5 · LOW

RICOS in IBM Algo Credit Limits (aka ACLM) 4.5.0 through 4.7.0 before 4.7.0.03 FP5 in IBM Algorithmics allows context-dependent attackers to discover database credentials by reading the DbUser and…

Published Jul 7, 2014ibmCWE-200EPSS 4.00%

Overview

CVE-2014-0894 is a low-severity vulnerability affecting ibm algo_credit_limits. It was published on July 7, 2014 and has a CVSS 2.0 base score of 3.5 (LOW).

This vulnerability has a CVSS 2.0 base score of 3.5, rated LOW. It can be exploited remotely over the network. Some level of privileges is required for exploitation.

Technical description

RICOS in IBM Algo Credit Limits (aka ACLM) 4.5.0 through 4.7.0 before 4.7.0.03 FP5 in IBM Algorithmics allows context-dependent attackers to discover database credentials by reading the DbUser and DbPass fields in an XML document.

Remediation

Check the references section for vendor advisories and patches from ibm. Update algo_credit_limits to the latest patched version. If immediate patching is not possible, review the CVSS vector to understand the attack surface and apply compensating controls such as network segmentation or access restrictions.

Affected products

VendorProductVersionsStatus

Frequently asked questions

What is CVE-2014-0894?

CVE-2014-0894 is a low-severity vulnerability affecting ibm algo_credit_limits. It was published on July 7, 2014 and has a CVSS 2.0 base score of 3.5 (LOW).

How severe is CVE-2014-0894?

This vulnerability has a CVSS 2.0 base score of 3.5, rated LOW. It can be exploited remotely over the network. Some level of privileges is required for exploitation.

How do I fix or remediate CVE-2014-0894?

Check the references section for vendor advisories and patches from ibm. Update algo_credit_limits to the latest patched version. If immediate patching is not possible, review the CVSS vector to understand the attack surface and apply compensating controls such as network segmentation or access restrictions.

How can CyberStrike help with CVE-2014-0894?

CyberStrike is an open-source, AI-augmented pentesting engine. Rather than flag a version number, it tests whether an issue like CVE-2014-0894 is actually reachable in your own applications and APIs, then verifies each finding before reporting it. That tells you if the weakness is a real, exploitable risk in your environment or a false positive you can safely deprioritize.

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