CVE-2014-0865: Input Validation

Published Jul 7, 2014
·
Updated

RICOS in IBM Algo Credit Limits (aka ACLM) 4.5.0 through 4.7.0 before 4.7.0.03 FP5 in IBM Algorithmics relies on client-side input validation, which allows remote authenticated users to bypass intended dual-control restrictions and modify data via crafted serialized objects, as demonstrated by limit manipulations.

Affected Software

3 affected components
IBM Algo Credit Limits=4.5.0
IBM Algo Credit Limits=4.7.0
IBM Algorithmics

Event History

Jul 7, 2014
CVE Published
via MITRE·10:00 AM
Data Sourced
via MITRE·10:00 AM
Description
Free Weekly Intel

Don't miss critical vulnerabilities

Join thousands of security professionals who receive our weekly digest of trending CVEs, zero-days, and exploited vulnerabilities.

No spam. Unsubscribe anytime.

Frequently Asked Questions

1

What is the severity of CVE-2014-0865?

CVE-2014-0865 has a medium severity rating due to the potential for authenticated users to bypass dual-control restrictions.

2

How do I fix CVE-2014-0865?

To remediate CVE-2014-0865, upgrade IBM Algo Credit Limits to version 4.7.0.03 FP5 or later.

3

What versions of IBM Algo Credit Limits are affected by CVE-2014-0865?

CVE-2014-0865 affects IBM Algo Credit Limits versions 4.5.0 through 4.7.0 before 4.7.0.03 FP5.

4

What type of attack is possible due to CVE-2014-0865?

CVE-2014-0865 allows for modification of data by authenticated users through crafted serialized objects.

5

Is CVE-2014-0865 related to input validation issues?

Yes, CVE-2014-0865 is related to client-side input validation vulnerabilities.

Contact

SecAlerts Pty Ltd.
132 Wickham Terrace
Fortitude Valley,
QLD 4006, Australia
info@secalerts.co
By using SecAlerts services, you agree to our services end-user license agreement. This website is safeguarded by reCAPTCHA and governed by the Google Privacy Policy and Terms of Service. All names, logos, and brands of products are owned by their respective owners, and any usage of these names, logos, and brands for identification purposes only does not imply endorsement. If you possess any content that requires removal, please get in touch with us.
© 2026 SecAlerts Pty Ltd.
ABN: 70 645 966 203, ACN: 645 966 203