Machine identities are now an integral part of business processes. If they are not inventoried, protected and monitored, they can become a grey area characterised by elevated privileges, access that is difficult to trace, and a direct impact on business continuity.
The problem no longer concerns human users alone
For years, we have associated the concept of digital identity almost exclusively with people: employees, administrators, suppliers and contractors. Today, this view is no longer sufficient. Corporate infrastructures are home to applications, cloud services, bots, automation pipelines and AI agents that access data and systems without direct human intervention.
These non-human entities need to authenticate themselves, receive authorisations and leave verifiable traces of their activities. From a security perspective, therefore, they must be managed as full-fledged identities. The problem is that many organisations continue to treat them as mere technical components, assigning them static credentials, shared accounts or privileges far broader than necessary.
This is precisely where one of the most insidious blind spots arises: an automated process may be legitimate, but if its identity is compromised, the attacker inherits its access rights, speed and operational capabilities. In a modern cybersecurity model, this is no longer merely a technical issue: it is a matter of risk governance.
The errors that expose machine identities
In practice, I often encounter configurations created for operational convenience and never reviewed since. A service has been using the same password for years, several applications share an API key, or a technical account retains administrative privileges because restricting them could cause malfunctions.
There are three main issues: credentials hardcoded in code or configuration files, secrets reused by different services, and permissions granted without applying the principle of least privilege. The absence of automatic rotation, expiry and revocation makes the problem even more serious.
A credential found in a data leak or accidentally exposed publicly cannot be considered secure or valid, even if the service using it is not publicly accessible. In fact, it may enable a broader, coordinated attack where other defences have failed to properly contain the threat. The correct response is to revoke it, replace it and verify where it has been used.
The issue is not about having ‘a wrong password’ or ‘a forgotten key’. The issue is not knowing how many technical identities exist, who is responsible for them, what privileges they have, and what impact their compromise might have.
Because a compromised machine can cause damage in a matter of minutes
A human account is normally bound by recognisable patterns of behaviour and timing. A compromised workload, on the other hand, can execute thousands of requests, query APIs, extract data or propagate across services within a very short timeframe.
The risk increases when a technical identity is shared. If multiple applications use the same credential, attributing an action to the correct service becomes complex. The incident response is also slowed down: revoking that secret may simultaneously interrupt multiple processes, whilst keeping it active leaves the door open to abuse.
The speed of automation, which is normally an advantage, multiplies the impact during an attack. This is why authentication, authorisation and traceability must be designed before the service goes live, not added after the first incident.
Today, attackers do not need to ‘break down a door’ when they can move about using valid credentials. And this is precisely why identity is becoming the new security perimeter.
Zero Trust applied to non-human identities
The Zero Trust model does not mean mistrusting everything across the board. It means eliminating implicit trust and evaluating every access request based on identity, the requested resource, context and risk. The model therefore shifts protection from the network perimeter to individual resources and requires authentication and authorisation to take place before the session begins.
For a machine identity, this approach translates into concrete controls: a unique identity for each workload or service, credentials with limited validity, granular authorisations, access assessed on a per-session basis, and continuous verification of contextual signals. It is not enough for a request to originate from the internal network, a known address or an environment considered ‘trusted’.
Where possible, it is preferable to use identities based on open standards, short-lived certificates, dynamically issued tokens or workload identity mechanisms instead of passwords and static keys. The aim is not to add complexity, but to reduce the time window within which a compromised credential can be reused.
The new perimeter consists of identities, policies and data flows
The cloud, distributed working, microservices and cross-organisational integrations have rendered the distinction between internal and external insufficient. An application can be hosted in a public cloud, call upon an on-premises service and exchange data with a supplier within a matter of seconds.
In this scenario, the real perimeter consists of the identities making the requests, the policies that restrict their behaviour, and the authorised flows between resources. Protecting only the network boundary means ignoring what happens between services that are already authenticated.
The relevant question, therefore, is no longer ‘where is this connection coming from?’, but ‘which identity is requesting access, to which resource, for what purpose and under what conditions?’.
This is where cybersecurity must cease to be viewed as a collection of isolated tools. What is needed is a coordinated system, capable of understanding the context, linking different signals and transforming data into operational decisions.
Two scenarios to recognise
The first concerns shared accounts, often created with generic names and passed from one person to another. If the account is used for anomalous activity, it becomes difficult to establish individual accountability. Revoking access is equally problematic, as it is unclear which processes still depend on that account.
The second scenario concerns an application that communicates via an API using a key embedded in the code, in a configuration file or in an ungoverned environment variable. If the repository, pipeline or runtime environment is compromised, the attacker can impersonate the service for as long as the key remains valid. Without centralised secret management, identifying all copies of the key and completing the rotation may take longer than expected.
In both cases, the problem is not just the credential itself. It is the absence of an owner, a defined lifecycle and a clear relationship between identities, permissions and application dependencies.
Recognising these scenarios means looking beyond the one-off event. We need to understand which process made it possible and which other identities might find themselves in the same situation.
Logging and auditing: seeing what is really happening
A Zero Trust strategy loses its effectiveness if access decisions cannot be observed. Logs must allow us to link each request to a specific identity, the resource involved, the policy applied and the outcome of the operation.
For non-human identities, it is advisable to establish a baseline of expected behaviour: services contacted, source environments, call volume, privileges normally used and time windows consistent with the process. Significant deviations – such as a token being used from an unusual environment or an application suddenly accessing data it has never requested before – must trigger alerts that are useful to the SOC and the CIRT.
Auditing remains essential even after an incident. If multiple systems share the same account, forensic analysis will inevitably be less precise. A one-to-one relationship between identity and workload reduces this margin of uncertainty.
From this perspective, monitoring is the ability to correlate events, recognise anomalous patterns and transform scattered signals into a timely response.
Where to start: an operational roadmap
The first step is to catalogue the non-human identities present in the environment: service accounts, API keys, certificates, tokens, bots, CI/CD pipelines, cloud workloads, scheduled jobs, SaaS integrations and AI agents. For each identity, the owner, purpose, dependencies, privileges, last use, authentication mechanism and revocation procedure must be specified.
Next, it is advisable to eliminate shared accounts, centralise the management of secrets, introduce automatic rotation, and replace persistent credentials with tokens, short-lived certificates or federated identities where the architecture permits. Permissions should be scaled back based on actual usage, with temporary access and contextual approvals for the most sensitive cases.
Finally, telemetry must be integrated into detection and incident response processes. Every technical identity should have documented procedures for suspension, rotation and restoration, so as to avoid ad-hoc decisions during an emergency.
True maturity lies not only in knowing how many identities exist, but in knowing how to govern them over time: who uses them, why they exist, what signals they produce and how they are managed when something goes wrong.
In conclusion
Managing a non-human identity means assigning a technical profile, a purpose and an operational scope to what was previously considered a mere automated process. It is not a mere formality: it is the prerequisite for knowing who can do what and for reacting swiftly when something deviates from expected behaviour.
The Zero Trust model is well-suited to addressing this transformation, as it replaces implicit trust with ad hoc verification, least privilege and continuous monitoring. But this alone is not enough. A broader vision is needed, one capable of integrating technologies, processes, specialist expertise and governance.
In environments where people, applications and intelligent agents operate together, ignoring non-human identities means leaving part of the infrastructure beyond control. And it is often precisely there that an incident finds the easiest route.
Cybersecurity today cannot be limited to protecting tools. It must govern relationships, access, dependencies and responsibilities. This is the cultural shift that enables organisations to become truly resilient.
By Andrea Lusetti – Cybersecurity Analyst, CYBEROO
