CVE-2025-33147 in Cognos Analytics
Summary
by MITRE • 09/18/2026
IBM Cognos Analytics 12.1.0 through 12.1.3 FP1, and 12.0.4 through 12.0.4 FP2 could allow an attacker on a shared network to obtain sensitive information caused by insecure network communication.
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Analysis
by VulDB Data Team • 09/18/2026
The vulnerability identified in IBM Cognos Analytics versions ranging from 12.1.0 through 12.1.3 Feature Pack 1, and 12.0.4 through 12.0.4 Feature Pack 2, represents a significant security deficiency related to the handling of network communications within enterprise analytics environments. This flaw allows an attacker positioned on the same shared network segment as the affected system to intercept or eavesdrop on sensitive data transmitted between clients and the server infrastructure. The core technical issue stems from the application's failure to enforce strict encryption protocols for all internal and external communication channels, particularly those involving authentication tokens, session identifiers, and query results containing proprietary business intelligence metrics. By relying on plaintext transmission or weak cryptographic implementations in specific operational modes, the software exposes critical data flows to passive network sniffing attacks using standard packet analysis tools available to any user with local area network access.
From a technical perspective, this vulnerability aligns closely with CWE-319, which classifies cleartext transmission of sensitive information over an exposed channel. The absence of mandatory Transport Layer Security or equivalent encryption mechanisms for all data exchanges creates a direct pathway for unauthorized disclosure. In many enterprise deployments, IBM Cognos Analytics is integrated into complex network topologies where multiple users and systems share the same broadcast domain. An adversary with physical or logical access to this segment can utilize tools such as Wireshark or tcpdump to capture unencrypted packets. Once captured, these packets may reveal user credentials, session cookies that allow for account takeover, or detailed analytical reports containing confidential financial projections, customer lists, and strategic planning data. The impact is not limited to immediate credential theft but extends to long-term intelligence gathering where historical traffic logs can be analyzed to reconstruct business operations and identify vulnerabilities in organizational processes.
The operational impact of this vulnerability is severe due to the nature of IBM Cognos Analytics as a central hub for enterprise decision-making. Compromise through this vector does not necessarily require exploitation of complex code execution flaws; instead, it leverages basic network reconnaissance capabilities that are widely accessible. This lowers the barrier to entry for attackers significantly, enabling threat actors with minimal technical expertise to conduct effective attacks against high-value targets. The exposure of sensitive information can lead to regulatory non-compliance under frameworks such as GDPR, HIPAA, or PCI-DSS, resulting in substantial legal penalties and reputational damage. Furthermore, the interception of session tokens facilitates privilege escalation scenarios where an attacker can impersonate legitimate users, potentially gaining access to restricted dashboards, modifying report configurations, or exporting large datasets for exfiltration. This undermines the confidentiality integrity triad essential for maintaining trust in business intelligence platforms.
Mitigation strategies must prioritize immediate remediation through software updates and network segmentation. IBM has addressed this issue by enforcing encrypted communications across all supported versions within the affected ranges. Administrators should immediately apply the latest available patches or feature packs that include fixes for insecure communication protocols to ensure that TLS 1.2 or higher is mandated for all client-server interactions. In addition to patching, organizations must implement robust network segmentation practices to isolate analytics servers from general user workstations and untrusted network zones. Utilizing virtual LANs or dedicated subnets restricts the attack surface by preventing unauthorized users on shared networks from reaching the Cognos infrastructure. Furthermore, deploying intrusion detection systems that monitor for cleartext traffic patterns can provide early warning indicators of exploitation attempts while broader security controls are being implemented. Regular audits of communication protocols and enforcement of strict cipher suites will further harden the environment against passive eavesdropping attacks.
This vulnerability is also relevant to MITRE ATT&CK technique T1043, which describes Common Application Protocol as a mechanism for data exfiltration or command and control when used improperly by attackers. By exploiting insecure network communication, adversaries can leverage standard protocols like HTTP without encryption to move stolen data out of the environment undetected by traditional security monitoring tools that focus on malicious payloads rather than protocol misuse. Addressing this flaw requires a holistic approach combining patch management, network architecture review, and continuous traffic analysis to ensure that sensitive information remains protected against interception in shared network environments.