Financial institution secrets management is now a breach control

At a glance

What this is: This guide argues that financial institution security now depends on secrets management because compromised credentials are the dominant entry point and the longest-dwelling breach path.

Why it matters: It matters because IAM, PAM, NHI, and cloud teams have to govern machine credentials as lifecycle assets, not static configuration, if they want to reduce fraud, compliance exposure, and lateral movement.

By the numbers:

• The average cost of a data breach in the US financial services sector reached USD 6.08 million in 2024.
• Breaches involving stolen or compromised credentials took an average of 292 days to identify and contain.
• Stolen credentials were the initial attack vector in 24% of all breaches analyzed in the 2024 Verizon DBIR.

👉 Read Akeyless's guide to financial institution secrets management

Context

Financial institution security is the discipline of protecting banking systems, customer data, payment rails, and operational continuity from credential abuse and related attacks. In this article, the primary problem is not generic cyber risk. It is the fact that financial institutions depend on tens of thousands of secrets, and those secrets often outlive the identities and workflows they were created for.

That creates a governance problem for NHI programmes as much as for traditional IAM and PAM teams. API keys, database passwords, encryption keys, certificates, and tokens need lifecycle control, auditability, and scope limitation because a single exposed credential can open access to transactions, customer records, and downstream cloud services.

The starting position is typical for the sector: high-value payment infrastructure, heavy regulation, and a sprawling mix of human and machine access. The article’s central claim is that the breach pattern is predictable because the credentials themselves are the weakest persistent layer.

Key questions

Q: How should financial institutions reduce the risk from compromised machine credentials?

A: They should treat every machine credential as a lifecycle asset, not a static configuration item. That means inventorying secrets, eliminating hardcoded values, scoping access to one workload and environment, and automating rotation and revocation so stolen credentials do not remain usable long enough to drive fraud or lateral movement.

Q: Why do service account secrets create more risk than teams expect?

A: Service account secrets create risk because they often authenticate connected systems with broad privileges and little human visibility. If one secret is reused, hardcoded, or left active after a workflow changes, an attacker can move through linked payment, data, or automation systems without needing a second compromise.

Q: How do security teams know whether secret governance is actually working?

A: Look for evidence that secrets are inventoried, scoped, rotated, and revoked on time, and that no secret remains active beyond its business need. If the environment still contains hardcoded keys, stale certificates, or undocumented third-party tokens, governance is not controlling the attack surface.

Q: Who is accountable when a leaked credential is used to access banking systems?

A: Accountability should sit with the system owner, the identity governance function, and the control owner for the secret store or vault. In regulated environments, the institution must also be able to prove to auditors that access was limited, logged, and removed when the underlying use case ended.

Technical breakdown

Why static secrets become a durable attack surface

Static secrets are credentials that remain valid until someone remembers to change them. In financial environments, that means API keys, service account passwords, certificates, and tokens can survive personnel moves, application refactors, and vendor changes. Once exposed, they often remain usable long after detection because they are embedded in code, pipelines, or configuration systems. The structural issue is not only exposure. It is persistence. A secret that stays valid after the original purpose ends creates a standing access window that attackers can exploit repeatedly.

Practical implication: inventory every long-lived secret and remove any credential that cannot be rotated, scoped, and revoked without manual effort.

How machine identities turn secrets into lateral movement

Machine identities are the non-human identities that applications, scripts, workloads, and integrations use to authenticate. In banking, those identities connect payment gateways, data stores, trading workflows, and cloud services, so a single secret can grant access far beyond the original system. If the credential is over-privileged, the attacker does not need to break a second control to move laterally. They already have the trust relationship. That is why NHI governance is not only about keeping secrets hidden. It is about ensuring each secret is bound to the smallest viable scope and a clear lifecycle.

Practical implication: bind every machine credential to one workload, one environment, and one purpose, then recertify that relationship on a fixed cadence.

Why multi-cloud secret sprawl weakens control consistency

Multi-cloud banking usually means separate IAM models, separate secret stores, and separate audit logs across AWS, Azure, GCP, and on-premises systems. That fragmentation makes it hard to prove where a credential exists, who can use it, and whether it still belongs in production. It also encourages drift, where development secrets leak into staging or production and partner credentials remain active after the relationship changes. The technical weakness is not cloud diversity itself. It is the absence of one control plane that can enforce consistent policy across all environments.

Practical implication: treat cross-cloud secret inventory as a control requirement, not an operational convenience, and enforce environment separation centrally.

Threat narrative

Attacker objective: The attacker wants durable access to banking systems through a credential path that is easier to exploit than direct compromise of a hardened control plane.

1. Entry occurs when an attacker finds a hardcoded key, leaked token, or exposed API credential in code, a repository, or a partner integration.
2. Escalation follows when the compromised credential grants access to banking workloads, payment systems, or internal APIs with more privilege than the original use case required.
3. Impact occurs when the attacker moves through connected systems, manipulates transactions, exfiltrates sensitive records, or maintains access long enough to hide the activity.

Breaches seen in the wild

• MongoBleed breach — MongoBleed exposed secrets across 87K MongoDB servers.
• Shai Hulud npm malware campaign — Shai Hulud campaign: npm malware exposed secrets on GitHub.

Read our 52 NHI Breaches Analysis report for a comprehensive view of breaches impacting Non-Human Identities including AI Agents.

NHI Mgmt Group analysis

Static credential persistence is the core failure mode in financial services. The article shows that banks are not dealing with isolated leaks. They are dealing with credentials that remain valid after the business process, workforce change, or vendor relationship that created them has already moved on. That is a lifecycle governance problem, not just a storage problem. Practitioners should treat every long-lived secret as an active liability until rotation, revocation, and scope reduction are proven.

Secret blast radius is the right organising concept for banking NHI governance. A single credential often reaches payment rails, customer databases, and automation workflows because machine identities are wired into the operating model. The control question is not whether a secret exists. It is how far that secret can move if it is stolen. Teams that do not map blast radius by workload and environment are effectively blind to the real impact of compromise.

Credential-based breach dwell time exposes a monitoring assumption that no longer holds. Detection programmes are often built around the idea that a compromised credential will be found before it can be widely abused. The IBM data cited in the article shows that this assumption fails when access persists for months. The implication is that review cycles alone do not contain machine identity risk; the access itself must be designed to expire, narrow, and leave a clean audit trail.

NHI lifecycle governance is now a compliance control, not an optional hygiene layer. The article ties secrets management to GLBA, SOX, NY DFS Part 500, PCI DSS v4.0, FFIEC, and NIST CSF 2.0 because credential handling determines whether institutions can evidence control over sensitive systems. That alignment matters for audit readiness, but the deeper issue is operational accountability. If a secret cannot be attributed, rotated, and revoked on demand, the control is incomplete.

Multi-cloud banking will keep amplifying credential exposure until secrets are managed as shared infrastructure. Different cloud IAM schemes do not remove the need for one policy model across workloads, environments, and third-party links. The article makes clear that inconsistency creates sprawl, and sprawl creates exploitable delay. Practitioners should assume that any fragmented secret model will eventually produce stale access unless governance is centralised.

From our research:

• 24% of all breaches analyzed in the 2024 Verizon DBIR began with stolen credentials, according to Guide to the Secret Sprawl Challenge.
• 64% of valid secrets leaked in 2022 are still valid and exploitable today, proving that detection without revocation leaves an active attack surface.
• For teams building a programme response, the Ultimate Guide to NHIs , Static vs Dynamic Secrets explains why static credentials create persistent exposure windows.

What this signals

Static secrets are becoming a governance debt item. When 64% of valid secrets leaked in 2022 are still valid and exploitable today, the problem is no longer discovery alone. Financial institutions need processes that pair detection with revocation, environment separation, and ownership assignment, or the same credential exposure will keep reappearing in different forms.

Secret sprawl now sits across code, collaboration tools, and cloud operations. The operational boundary is wider than the repository scan most teams still rely on, which means IAM and security engineering need one view of where credentials live and who can still use them. That is the governance shift financial programmes need to make before auditors or attackers force it.

Identity teams should align credential control with lifecycle control. In a banking environment, the same principles used for user offboarding and privileged access review now need to apply to service accounts, API keys, and certificates. The most reliable next step is to pair central secret inventory with a policy model that can prove the control is current, not merely documented.

For practitioners

• Map every credential to a named workload owner Create an authoritative inventory of API keys, certificates, database passwords, and tokens, and require each one to have a named owner, a purpose, and a revocation path.
• Eliminate hardcoded secrets from code and pipelines Scan repositories, CI/CD jobs, and container images for embedded credentials, then block merges and releases until the secret is replaced with a managed secret reference.
• Reduce machine privilege to one workload and one environment Scope each secret so it only authorises the specific application, system, and environment that needs it, and recertify the mapping when integrations change.
• Automate rotation and revocation by event Rotate credentials on schedule and when staff leave, vendors change, or anomalous use appears, so stale access does not survive the business event that invalidates it.
• Unify cross-cloud secret governance under one control plane Maintain one inventory and one policy layer for AWS, Azure, GCP, and on-premises systems so that audit evidence and enforcement stay consistent across environments.

Key takeaways

• Financial institution breaches are increasingly credential-led, which makes secrets management a first-line control rather than an operational convenience.
• The scale of the problem is measurable: high breach cost, long dwell time, and a large share of incidents beginning with stolen credentials.
• The control that changes outcomes is lifecycle governance for machine identities, including scoping, rotation, revocation, and cross-cloud consistency.

Key terms

• Machine Identity: A machine identity is the credentialed identity used by software, workloads, scripts, and integrations to authenticate to other systems. In banking environments, these identities often carry direct access to data, payment, or automation workflows, so they need the same governance discipline as other production identities.
• Secret Sprawl: Secret sprawl is the uncontrolled spread of API keys, passwords, tokens, and certificates across code, pipelines, cloud services, and collaboration tools. It increases the chance that a credential will be reused, forgotten, or left active after its original purpose ends, which makes compromise harder to contain.
• Dynamic Secret: A dynamic secret is a credential generated for a specific use case and limited lifetime rather than stored permanently. For machine identities, dynamic secrets reduce the standing access window, but they only work when issuance, rotation, and revocation are automated and tied to clear policy.
• Secret Blast Radius: Secret blast radius is the amount of damage an attacker can cause after stealing one credential. It depends on scope, privilege, environment separation, and downstream trust relationships, so a well-governed secret should have a narrow blast radius and a fast revocation path.

What's in the full article

Akeyless's full guide covers the operational detail this post intentionally leaves for the source:

• Regulatory mapping across GLBA, SOX, NY DFS Part 500, PCI DSS v4.0, FFIEC, and NIST CSF 2.0 for credential controls.
• Implementation detail on dynamic secrets, JIT access, and automated rotation for banking workloads.
• Multi-cloud control patterns for AWS, Azure, GCP, and on-premises environments, including environment isolation and audit logging.
• A practical walkthrough of how zero-trust access applies to banking secrets, including request approval and revocation triggers.

👉 Akeyless's full guide covers the regulatory mapping, multi-cloud patterns, and dynamic secret controls in more detail.

Deepen your knowledge

NHI governance, agentic AI identity, and machine identity lifecycle are core topics in our NHI Foundation Level course, the industry's only accredited NHI security programme. If you are responsible for identity security strategy or NHI governance in your organisation, it is worth exploring.