Modern digital services rely on enormous computing infrastructures whose operation remains entirely invisible to the average user. This includes, among others, OpenAI (ChatGPT), Google, Facebook and Microsoft.
We use apps, messengers, search engines, cloud services and AI-based tools without giving a thought to how many technical layers stand behind each of these services. This in turn raises the question – can the data we entrust to such systems be obtained or used without our knowledge?
From an engineering perspective, every large platform must operate on an extensive infrastructure: servers, databases, networks, backups, failover systems and software that keeps the whole thing running. In such environments there are always people performing administrative functions, responsible for maintaining continuity of operation and responding to incidents. Even if they are bound by rigorous procedures, the very nature of the system means that at a certain technical level administrative access must exist, because without it there would be no way to fix errors, restore data after failures, or update the infrastructure. Although companies publish security policies, these also serve a formal function — they build trust and meet legal requirements — which does not change the fact that, from an engineering standpoint, the system cannot run without people and processes that have broad technical access.
This means that although users see the service as secure and fully automated, there are always technical layers in the background where human intervention is essential. And this is exactly where the risk arises. Low-level administrators, people operating backup systems, data-centre operators or maintenance engineers have the potential to come into contact with resources that users consider private. In practice they act according to procedures and within trusted structures, but the history of technology and information security shows that even the most restrictive environments are not free from abuse, human error or the actions of the state apparatus.
An additional element of risk is the potential actions of external parties who may seek to obtain information covertly. In extreme scenarios, hacker groups, cybercriminals or even intelligence services may try to reach the infrastructure, operating in conditions where local regulations may have limited effectiveness.
The risk is also increased by the fact that modern services use machine-learning mechanisms which themselves require the processing of enormous amounts of data. Some of it is processed in real time, some archived in systems forming an analytical back end. The user has no influence over how long such data is stored or what archiving rules a given platform applies. The result is a complex web of dependencies in which data — although formally secured — may physically exist in the system longer than the user assumes, without their knowledge, while various layers of the infrastructure remain beyond their control.
It is worth being aware that digital development brings enormous benefits, but also carries real threats. A user of modern services should understand that even in a very secure environment there are areas where a full guarantee of confidentiality cannot be given. This results not from anyone's ill will, but from the very architecture of contemporary systems, which must remain serviceable, scalable and resilient to failures. And this means that between the user and their data there are always areas where the human factor comes into play.
Awareness of these dependencies is crucial. It allows a better understanding of the technological reality, more considered decisions about sharing data, and a recognition that security in the digital world is not merely the result of trust in manufacturers' declarations, but also the effect of a complex, multi-layered ecosystem that is not free from limitations and threats. Modern technology gives enormous power, but at the same time requires users to have a basic awareness of risk — including the risk that does not lie on the surface, but is hidden deep in the structures of the IT infrastructure that are not talked about day to day.
Below are the key issues that may affect the security and confidentiality of users' data in contemporary digital services.
1. Privileged administrative access – a risk invisible to the user
Every data-processing environment – no matter how modern or distributed – relies on a series of technical elements that must work even when the user is unaware of their existence. Systems require periodic maintenance reviews, administrative accounts that make it possible to carry out service tasks, and mechanisms for creating backups. In practice this means that beneath the layer visible to the user there is a whole support infrastructure: tools for monitoring the state of machines, services collecting logs, configuration-distribution systems and environments for analysing failures and recovering the system after damage.
In every such technical ecosystem there are privileged accounts that have the ability to view the structure of databases, perform operations on records, inspect sensitive application logs and access intermediate layers such as message queues or transmission buffers. Backup mechanisms also need to read and copy data in order to be able to restore the system after a failure. This is not an aberration – it is a fundamental element of the architecture of any serious system.
Even if every administrative access should be logged and audited, the mere existence of such privileges introduces risk. A system administrator sees far more than a user; they have insight into logs, data structures and the processes of copying information between layers of the system. The user has no way of independently verifying who administers their data, what the backup procedures look like, where the data goes in the backup–restore process, whether all repositories are encrypted and who can read the archived material.
In modern architectures there are often intermediate elements – passive stores, data replicas maintained only for disaster recovery, highly detailed historical logs, or network-traffic monitoring systems that may store dumps or fingerprints of data. Although in principle they serve to ensure stability and operational security, from a risk standpoint they are a potential source of leakage. This is precisely the category of threats referred to as an insider threat: the possibility of privileges being abused by a person with privileged access, or by an entity that has taken over such an account.
The result is a situation that is paradoxical but typical of large production environments: the end user trusts the system, but has no real way of assessing what operations the technical layers perform or who actually has access to them. The system has to work, so it must have administrators, logs, backups and diagnostic procedures. And this means that there are places where data may be processed, copied or stored, even if this is not visible from the service recipient's point of view.
2. Backups and the persistence of data
Contrary to popular belief, data processed in cloud systems or complex server environments is not temporary in nature. To maintain continuity of services, guarantee the ability to restore the environment after a failure and meet legal requirements, every production environment maintains a multi-level, recursive backup structure. These copies form a deep tree of snapshots, replicas and incremental backups that may be duplicated between different layers of the infrastructure – from virtual machines, through storage layers, to distributed systems and object services. The end user has no visibility into this process: they have no access to backup metadata, do not know on what media they are stored, what retention cycle they have, or whether they are actually deleted after the declared time. This lack of transparency is unavoidable, because the layer managing backups operates at a level inaccessible to the user's application.
In a typical infrastructure, backups exist in parallel in many places — at the file-system level, in databases, in cluster-replication systems, in blob-storage layers, and also in low-cost archiving services intended for long-term storage. They may be kept for weeks, months or even years, depending on the retention policy. Importantly, this policy may differ from the manufacturer's declarations if the system administrator uses additional archiving mechanisms, for example low-level LVM snapshots, Ceph cluster snapshots, copies in AWS Glacier, Azure Vault or similar services.
In an unfavourable variant — for example, in the case of a security breach by a privileged administrator, a misconfiguration of permissions, the takeover of service accounts, or the actions of a hacker with access to the storage layer — the deep backup structure becomes a complete, unremovable source of the user's data. These copies can be restored offline, outside the production infrastructure, which allows the data to be analysed without leaving traces in the monitoring systems. In practice this means that even if data is deleted from the application's perspective, it may still exist in many historical snapshots that are not under the user's control.
It is precisely this multi-layered nature of backups that makes the risk associated with unauthorised access to data in the cloud real and often underestimated. Even in environments compliant with security standards, providers must maintain a back end for diagnostics and data recovery, which technically means the existence of places where the user's data may be accessible for a long time — regardless of their knowledge and intentions.
3. Intelligence services and government entities
In many jurisdictions, state services have the ability to obtain data from IT systems – sometimes directly on the basis of regulations, and sometimes through procedures that users never see and cannot verify. In practice this means that data stored in cloud environments or data centres may be disclosed without the knowledge of the entity using the service, if the infrastructure operator receives an appropriate request. Such access may concern both the logical layers – through administrative interfaces or data-production orders – and the physical layer, including control over servers, disk arrays or network elements.
In some cases, the services also have technical means allowing them to interfere with the infrastructure directly, for example by taking control of the physical location of the systems, installing monitoring devices at network junction points (within the limits of the applicable law), or exploiting vulnerabilities in hardware. Such operations may be overt or covert, and the end user has no real way of establishing whether they were carried out and what their scope was.
Service providers' declarations of full data privacy do not eliminate these risk vectors, because privileged access – whether from administrators or state institutions – exists in many architectures and is difficult to eliminate entirely (although techniques such as end-to-end encryption, customer-managed keys or confidential computing significantly limit it). Even if formal procedures provide for the control, logging and auditing of requests, there is always a space in which actions may be carried out outside the standard flow, using infrastructural privileges, passive archives or data-recovery mechanisms. This is a real threat in any architecture based on privileged administrative roles and physical access to devices, regardless of official assurances of security.
4. Attacks on the infrastructure layers below the application
For the end user, the application is merely an interface – a window through which they send and receive information. From an engineering perspective, this is only the shallowest layer of an enormous technological ecosystem in which data can appear and move around in many additional places. In a typical distributed environment, information is recorded or persisted not only in the application's database, but also in system logs, in buffering mechanisms, in the caches of computing nodes, in event-monitoring systems, and in telemetry and diagnostic tools used to analyse performance and failures. Data is sometimes duplicated to intermediate layers, such as message queues, stream-processing systems or analytical platforms that operate on working copies, keeping them in operating memory, disk segments or private spaces belonging to maintenance teams.
Each of these layers is a potential leakage vector – both in the case of the infrastructure being taken over by an external attacker, and in the case of a breach by a malicious administrator or maintenance engineer with privileged access. In corporate environments and large-scale data centres, there is also the possibility of information being obtained by entities with significant technical resources, who may break through the layer isolation or intercept data at the physical level. Ultimately this means that even if the main database remains protected, the whole ecosystem in which the user's data is processed has many places where the data can be temporarily persisted, copied or exported beyond the user's control.
5. The most dangerous variant: a silent data leak by a technical person
The most dangerous scenario concerns a situation in which a person with privileged access operates in layers inaccessible to the end user. Such an entity may copy data outside the production infrastructure, using the environment's native mechanisms, such as backup systems, inter-node replication, volume snapshots or database exports. The use of a service account with a broad scope of privileges – including access to the data layer, storage, transaction logs and diagnostic tools – makes it possible to carry out operations that do not generate anomalies in the user interface or in the application's processing paths.
Such an attack does not require breaking any cryptographic safeguards, because it takes place in the layer before encryption or within systems that have the right to decrypt data during normal operation. A caveat: this concerns services in which the provider holds the keys — in solutions with genuine end-to-end encryption or client-side encryption (e.g. Signal, iMessage, data encrypted with the user's key), this vector is significantly limited. It also does not require an external break-in, since it uses an existing, legitimate access path provided for administrative purposes. Importantly, operations of this type can take place in the background, without leaving traces visible to the user – data can be exported within standard service mechanisms, and its movement may look like routine maintenance activity.
For this reason, this vector is considered the most difficult to eliminate. This is because it relies on legitimate, essential elements of the architecture: privileged accounts, system-maintenance tools, backup and diagnostic processes. The risk results not from a flaw in the technology, but from an inherent feature of every system – the need to have service access enabling its operation, restoration and reconfiguration. It is precisely this class of threats that is the most difficult to detect and practically impossible to eliminate entirely in systems that must operate continuously and under human control.
Many modern services – cloud, online office suites, artificial intelligence and automation systems – operate on a complex infrastructure that the user does not see. The client sees only the application window, but in the background there are servers, databases, backups, monitoring systems and technical tools to which administrators and maintenance teams have access.
For these services to work reliably, there must be mechanisms such as backups, system logs, caches or intermediate processing layers. The user's data may temporarily remain in them, even if it is not visible in the application. Nor does the user have any influence over where their data is physically located or who has access to it at the technical level.
The risk arises when someone who should not comes into contact with the data: an administrator with too broad privileges, an employee abusing their role, a hacker, or the state services, which in many countries can obtain data without informing the people concerned. In such a situation, access to the information may occur without the user's knowledge and outside the standard application interface.
Therefore, when using AI, cloud, Office 365, AWS or any online system, it is worth adopting a simple principle: everything we send to external services may be stored longer than we expect, and may theoretically be read by people we do not know and over whom we have no influence. This is not about giving up technology, but about using it consciously – not sending sensitive information whose disclosure could cause harm, and remembering that full control over data ends the moment it enters someone else's system.