| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 6.0 | $0-$5k | 0.00 |
Summary
A vulnerability identified as problematic has been detected in IBM Algo Credit Limits up to 4.7.0. The impacted element is an unknown function. Performing a manipulation results in cross-site request forgery. This vulnerability is known as CVE-2014-0864. Remote exploitation of the attack is possible. Furthermore, an exploit is available.
Details
A vulnerability, which was classified as critical, was found in IBM Algo Credit Limits up to 4.7.0. This affects some unknown functionality. The manipulation with an unknown input leads to a cross-site request forgery vulnerability. CWE is classifying the issue as CWE-352. The web application does not, or can not, sufficiently verify whether a well-formed, valid, consistent request was intentionally provided by the user who submitted the request. This is going to have an impact on confidentiality, integrity, and availability. The summary by CVE is:
Multiple cross-site request forgery (CSRF) vulnerabilities in Executer in RICOS in IBM Algo Credit Limits (aka ACLM) 4.5.0 through 4.7.0 before 4.7.0.03 FP5 in IBM Algorithmics allow remote attackers to hijack the authentication of arbitrary users for requests that change (1) a deal s currency or (2) a limit via a crafted XML document.
The weakness was published 07/07/2014 (Website). It is possible to read the advisory at sec-consult.com. This vulnerability is uniquely identified as CVE-2014-0864 since 01/06/2014. It is possible to initiate the attack remotely. No form of authentication is needed for exploitation. It demands that the victim is doing some kind of user interaction. Technical details are unknown but a public exploit is available.
A public exploit has been developed by SEC Consult and been published even before and not after the advisory. The exploit is shared for download at exploit-db.com. It is declared as highly functional. The vulnerability was handled as a non-public zero-day exploit for at least 6 days. During that time the estimated underground price was around $5k-$25k.
The vulnerability is also documented in the databases at X-Force (90938), Exploit-DB (33942), SecurityFocus (BID 68262†) and Secunia (SA59296†). Similar entries are available at VDB-70284, VDB-70282, VDB-70281 and VDB-70280. Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
Product
Vendor
Name
Version
License
Website
- Vendor: https://www.ibm.com/
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔍VulDB Reliability: 🔍
CVSSv3
VulDB Meta Base Score: 6.3VulDB Meta Temp Score: 6.0
VulDB Base Score: 6.3
VulDB Temp Score: 6.0
VulDB Vector: 🔍
VulDB Reliability: 🔍
CVSSv2
| AV | AC | Au | C | I | A |
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| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
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| Vector | Complexity | Authentication | Confidentiality | Integrity | Availability |
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| Unlock | Unlock | Unlock | Unlock | Unlock | Unlock |
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VulDB Base Score: 🔍
VulDB Temp Score: 🔍
VulDB Reliability: 🔍
NVD Base Score: 🔍
Exploiting
Class: Cross-site request forgeryCWE: CWE-352 / CWE-862 / CWE-863
CAPEC: 🔍
ATT&CK: 🔍
Physical: No
Local: No
Remote: Yes
Availability: 🔍
Access: Public
Status: Highly functional
Author: SEC Consult
Download: 🔍
EPSS Score: 🔍
EPSS Percentile: 🔍
Price Prediction: 🔍
Current Price Estimation: 🔍
| 0-Day | Unlock | Unlock | Unlock | Unlock |
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| Today | Unlock | Unlock | Unlock | Unlock |
Exploit-DB: 🔍
Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: no mitigation knownStatus: 🔍
0-Day Time: 🔍
Timeline
01/06/2014 🔍07/01/2014 🔍
07/01/2014 🔍
07/07/2014 🔍
07/07/2014 🔍
03/26/2015 🔍
10/06/2024 🔍
Sources
Vendor: ibm.comAdvisory: 127304
Status: Confirmed
Confirmation: 🔍
CVE: CVE-2014-0864 (🔍)
GCVE (CVE): GCVE-0-2014-0864
GCVE (VulDB): GCVE-100-70275
X-Force: 90938 - IBM Algo Credit Limits ACLM WEB GUI cross-site request forgery
SecurityFocus: 68262
Secunia: 59296
scip Labs: https://www.scip.ch/en/?labs.20161013
See also: 🔍
Entry
Created: 03/26/2015 12:07Updated: 10/06/2024 03:13
Changes: 03/26/2015 12:07 (58), 03/07/2018 09:44 (3), 03/24/2022 13:12 (3), 10/06/2024 03:13 (14)
Complete: 🔍
Cache ID: 216:794:103
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
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