CVE-2026-15995 in Cognos Analytics
Summary
by MITRE • 07/17/2026
IBM Cognos Analytics 12.1.3 GA Version with build number through 12.1.3-2606251736 could allow an attacker to obtain incorrect report summary results or cause report-processing failures due to a race condition in the Agentic AI assistant's concurrent request-handling logic when multiple authenticated users submit report-related tasks simultaneously.
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Analysis
by VulDB Data Team • 07/17/2026
This vulnerability exists within IBM Cognos Analytics 12.1.3 GA version and build numbers up to 12.1.3-2606251736 where a race condition affects the Agentic AI assistant component responsible for handling concurrent report requests. The flaw manifests when multiple authenticated users submit report-related tasks simultaneously, creating a timing dependency issue in the system's request-processing pipeline that can lead to incorrect summary results or complete report processing failures. This vulnerability represents a classic concurrency issue that undermines data integrity and system reliability in enterprise reporting environments.
The technical root cause stems from inadequate synchronization mechanisms within the Agentic AI assistant's concurrent request handling logic. When multiple users submit similar report requests concurrently, the system fails to properly coordinate access to shared resources or state variables that track report processing status and result aggregation. This race condition can cause data corruption during result consolidation phases where multiple threads attempt to modify shared summary data structures simultaneously without proper locking mechanisms. The vulnerability falls under CWE-362 which specifically addresses Race Conditions and CWE-835 which covers Loop with Unreachable Exit Condition, both of which are fundamental concurrency flaws that can lead to unpredictable system behavior.
The operational impact of this vulnerability extends beyond simple data accuracy issues as it can compromise the reliability of business intelligence reporting systems. Organizations relying on IBM Cognos Analytics for critical decision-making may receive incorrect summary data from reports, potentially leading to misguided business strategies or financial decisions based on flawed information. Additionally, the report processing failures can cause cascading system issues where legitimate user requests are not properly handled, creating service degradation and potential denial of service conditions in high-traffic reporting environments. This vulnerability particularly affects organizations with multiple concurrent users submitting similar analytics requests, making it a significant concern for enterprises with active reporting workloads.
Security professionals should consider this vulnerability in the context of the MITRE ATT&CK framework, specifically under TA0006 Credential Access and TA0005 Defense Evasion categories where improper concurrency control can create opportunities for attackers to manipulate system behavior through carefully timed request sequences. The vulnerability's impact is amplified in environments where multiple users have authenticated access to reporting systems, as it requires minimal privileges to exploit. Organizations should implement immediate mitigations including applying IBM's official security patches and updates, implementing proper rate limiting for concurrent report requests, and monitoring for unusual patterns in report processing failures or data inconsistencies that may indicate exploitation attempts. Additionally, system administrators should consider disabling the Agentic AI assistant component if its functionality is not critical to operations until proper security patches are applied.
The vulnerability demonstrates how modern enterprise software components can introduce subtle but significant security risks through improper concurrency management. In enterprise environments where analytics systems handle sensitive business data and support critical operational decisions, such flaws can have far-reaching consequences beyond immediate system failures. Organizations should conduct thorough risk assessments considering their specific usage patterns of concurrent reporting requests, as the vulnerability's exploitability may vary based on system load and user behavior patterns. Regular security testing and monitoring of concurrent processing scenarios should be implemented to detect potential exploitation attempts before they cause significant operational impact or data integrity issues within business intelligence systems.