CVE-2026-17644 in Financial Transaction Manager
Summary
by MITRE • 09/23/2026
IBM Financial Transaction Manager (FTM) for RedHat OpenShift could allow a local attacker to gain unauthorized access to sensitive information and modify transaction data due to the use of hard-coded credentials.
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Analysis
by VulDB Data Team • 09/23/2026
The vulnerability identified in IBM Financial Transaction Manager for Red Hat OpenShift represents a critical security flaw rooted in poor credential management practices, specifically the embedding of static authentication tokens or passwords directly within the application codebase or configuration files rather than utilizing dynamic secret injection mechanisms. This architectural weakness allows any user with local access to the underlying container environment or host system where the FTM instance is deployed to extract these hard-coded credentials from memory dumps, source code repositories, or persistent volume mounts that may not be properly secured by default permissions. The presence of such static secrets fundamentally undermines the principle of least privilege and eliminates the ability to rotate keys without redeploying application components, thereby creating a persistent backdoor for malicious actors who have achieved initial foothold within the cluster through other vectors such as misconfigured service accounts or exposed APIs.
From an operational perspective, this flaw enables unauthorized entities to bypass authentication controls entirely, granting them full administrative privileges over the transaction processing subsystems managed by IBM FTM. An attacker leveraging these credentials can read sensitive financial data including customer personally identifiable information and account details, violating core confidentiality requirements of regulations such as PCI DSS and GDPR. Furthermore, the ability to modify transaction data introduces severe integrity risks, allowing for the alteration of payment records, creation of fraudulent transactions, or disruption of critical banking operations which could lead to significant financial loss and reputational damage for the affected organization. The impact extends beyond immediate data theft, as compromised credentials can be used laterally within the Kubernetes cluster to access other services that trust the same identity, amplifying the blast radius of the initial compromise across the entire infrastructure ecosystem.
This vulnerability aligns with CWE-798: Use of Hard-coded Credentials, a classification widely recognized in industry standards for identifying weaknesses where authentication data is statically embedded rather than dynamically managed. In terms of offensive security frameworks, this flaw facilitates ATT&CK technique T1078: Valid Accounts, as it provides attackers with legitimate-looking credentials that can be used to maintain persistence and move laterally without triggering typical anomaly detection systems designed to flag unknown login attempts. The exploitation path typically involves local privilege escalation followed by credential harvesting from the application process space or configuration storage, highlighting the necessity for robust isolation boundaries between different tenants within a multi-tenant OpenShift environment.
Mitigation strategies must prioritize immediate remediation of the hard-coded secrets through automated secret scanning tools integrated into the CI/CD pipeline to prevent future occurrences. Organizations should implement externalized secret management solutions such as HashiCorp Vault or IBM Cloud Secrets Manager, ensuring that credentials are injected at runtime via secure environment variables rather than being baked into container images. Additionally, enforcing strict RBAC policies within Red Hat OpenShift is essential to limit which service accounts can access sensitive volumes and secrets, thereby reducing the attack surface for local privilege escalation attacks. Regular auditing of application configurations and implementing network segmentation between critical transaction processing components and less trusted zones will further enhance resilience against exploitation of this vulnerability type.