IBM Db2 Mirror for i 7.4/7.5/7.6 information disclosure

CVSS Meta Temp Score
CVSS is a standardized scoring system to determine possibilities of attacks. The Temp Score considers temporal factors like disclosure, exploit and countermeasures. The unique Meta Score calculates the average score of different sources to provide a normalized scoring system.
Current Exploit Price (≈)
Our analysts are monitoring exploit markets and are in contact with vulnerability brokers. The range indicates the observed or calculated exploit price to be seen on exploit markets. A good indicator to understand the monetary effort required for and the popularity of an attack.
CTI Interest Score
Our Cyber Threat Intelligence team is monitoring different web sites, mailing lists, exploit markets and social media networks. The CTI Interest Score identifies the interest of attackers and the security community for this specific vulnerability in real-time. A high score indicates an elevated risk to be targeted for this vulnerability.
7.6$5k-$25k0.47+

Summaryinfo

A vulnerability has been found in IBM Db2 Mirror for i 7.4/7.5/7.6 and classified as problematic. The affected element is an unknown function. Performing a manipulation results in information disclosure. This vulnerability is cataloged as CVE-2026-17182. It is possible to initiate the attack remotely. There is no exploit available.

Detailsinfo

A vulnerability, which was classified as problematic, was found in IBM Db2 Mirror for i 7.4/7.5/7.6. This affects an unknown part. The manipulation with an unknown input leads to a information disclosure vulnerability. CWE is classifying the issue as CWE-200. The product exposes sensitive information to an actor that is not explicitly authorized to have access to that information. This is going to have an impact on confidentiality. The summary by CVE is:

IBM Db2 Mirror for i 7.4, 7.5, and 7.6 could allow a remote attacker to bypass authentication and obtain or alter sensitive information due to improper validation of request URI path segments.

It is possible to read the advisory at ibm.com. This vulnerability is uniquely identified as CVE-2026-17182 since 07/24/2026. The exploitability is told to be easy. It is possible to initiate the attack remotely. No form of authentication is needed for exploitation. The technical details are unknown and an exploit is not publicly available. The pricing for an exploit might be around USD $5k-$25k at the moment (estimation calculated on 08/14/2026). The attack technique deployed by this issue is T1592 according to MITRE ATT&CK.

There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.

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: 7.6
VulDB Meta Temp Score: 7.6

VulDB Base Score: 5.3
VulDB Temp Score: 5.3
VulDB Vector: 🔒
VulDB Reliability: 🔍

CNA Base Score: 9.8
CNA Vector (ibm): 🔒

CVSSv2info

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

Exploitinginfo

Class: Information disclosure
CWE: CWE-200 / CWE-284 / CWE-266
CAPEC: 🔒
ATT&CK: 🔒

Physical: No
Local: No
Remote: Yes

Availability: 🔒
Status: Not defined
Price Prediction: 🔍
Current Price Estimation: 🔒

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Threat Intelligenceinfo

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

Countermeasuresinfo

Recommended: no mitigation known
Status: 🔍

0-Day Time: 🔒

Timelineinfo

07/24/2026 CVE reserved
08/14/2026 +21 days Advisory disclosed
08/14/2026 +0 days VulDB entry created
08/14/2026 +0 days VulDB entry last update

Sourcesinfo

Vendor: ibm.com

Advisory: ibm.com
Status: Confirmed

CVE: CVE-2026-17182 (🔒)
GCVE (CVE): GCVE-0-2026-17182
GCVE (VulDB): GCVE-100-390099

Entryinfo

Created: 08/14/2026 21:43
Changes: 08/14/2026 21:43 (61)
Complete: 🔍
Cache ID: 216::103

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

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