Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Employees are adopting Artificial Intelligence (AI) tools to enhance their productivity, but they rarely consider the security implications of doing so. When an employee pastes sensitive customer data into an unapproved AI tool, that data is processed by a third-party model outside the organization’s control, often leaving no audit trail for security teams to review.

Zero trust is a cybersecurity framework built on the principle of “never trust, always verify,” meaning every user, device and session must be continuously verified for access to be granted and maintained. In federal environments, zero trust is especially critical because privileged accounts can provide access to sensitive systems, infrastructure and data.

Financial institutions rely heavily on third-party vendors like payment processors, banking platform providers and fintech integrations to maintain operational efficiency. In fact, according to Verizon’s 2025 Data Breach Investigations Report, 30% of data breaches involved a third party, including vendors with direct remote access to financial systems. As environments become more distributed and accommodate remote work, managing vendor access has become a modern security challenge.

Ransomware and stolen credentials are among the most common and harmful attack vectors targeting financial institutions. Since banking systems store valuable financial assets and sensitive customer data, organizations must demonstrate strict control and oversight of privileged access to support regulatory and audit expectations under frameworks such as SOX, PCI DSS and GLBA.

Although Jira serves as the system of record for many DevOps and IT teams, retrieving secrets or approving requests for privileged information often occurs on other platforms. Teams may depend on external tools, email messages or Slack chats to manage credentials or elevation requests, leading to context switching, audit gaps and delays that increase operational risk.