AI is undoubtedly speeding up software development. It helps teams write code, run tests, analyse data and understand complex projects faster. Attackers are gaining many of the same advantages.
At Google Cloud Summit 2026, one of the key messages from the security sessions was that AI is changing cyberattacks in three ways: their scale, speed and technical sophistication are all increasing. For companies running an online store, portal, internal system or customer-facing application, the implication is clear: security needs to become a much more proactive part of product development.
How AI is changing the security landscape
1. Vulnerabilities can be found faster
AI can process large volumes of publicly available information at once. When the developer of a plugin, library or service discloses a security vulnerability, that information becomes available to both development teams and attackers. From that moment, the clock starts ticking.
The development team needs to determine whether the vulnerability affects its project and deploy a fix. At the same time, attackers can search for websites and systems using the affected technology that have not yet been patched and try to exploit the weakness.
2. There is less time to respond
During an attack or suspicious activity, the first few minutes matter. An alert appears, a suspicious URL is detected or something unusual happens in the administration interface, and the team needs to understand what is happening and where to look first.
AI increases that pressure. Attackers can connect the dots faster and move through possible next steps more quickly. Meanwhile, the development team needs to identify which part of the project is affected and decide on the right response.
This is where a clear understanding of the project becomes critical. The better the team knows its most sensitive areas and responsibilities, the faster it can move from suspicion to a concrete action.
3. Attacks are becoming more sophisticated
AI helps attackers combine technical details into a bigger picture more efficiently. On their own, these details may seem minor: an older part of the system, a loosely configured permission or an outdated plugin. Combined, however, they can create a path to the part of the project that directly affects customers or sensitive data.
That is why security needs to be considered in the context of the entire project.
4. Faster development can mean less visibility into the codebase
AI-powered development is a clear business advantage, but it also introduces new risks. If generated code reaches production without proper review, it may include overly broad permissions, weaker input validation or logic that does not account for the wider security context of the project.
As development speeds up, code quality, access control and the impact of every new change on the wider system become even more important.
What does this mean for your digital product?
Security needs to be reviewed more regularly, and potential weaknesses need to be identified earlier and more deliberately.
For a digital product, the most important areas to review include:
- technologies and third-party services,
- administration access,
- authentication and user accounts,
- integrations with external systems,
- areas where customer data is processed,
- publicly accessible parts of the system,
- the response process for suspicious activity.
Where to start
Addressing security weaknesses as part of planned development is far less costly than dealing with them under the pressure of an active incident. The team has more time to prepare a fix, schedule it properly and implement it with less disruption to day-to-day operations.
A proactive review also helps a company understand its own system better. It reveals which areas are critical, where sensitive data is handled and which parts of the project deserve more regular attention.
That visibility matters more than ever in the AI era. Attackers are moving faster, digital products are changing faster, and security needs to keep pace.
Talk to us about the security of your digital product
As part of a security review, we assess the technical solution, codebase, access controls, configuration and handling of sensitive data. We identify potential weaknesses, prioritise them by risk and recommend concrete next steps that make sense from both a technical and business perspective.
After the review, you will have a clear picture of which improvements we can incorporate directly into development and which areas would benefit from deeper assessment by a specialised cybersecurity provider.
Get in touch and let us review the security of your project before someone else puts it to the test.
Frequently asked questions about digital product security
How can I tell whether our website, online store or internal system has security vulnerabilities?
Security weaknesses are not always visible from the outside. A thorough review should therefore look at the codebase, technologies and libraries in use, configuration, user permissions, authentication, integrations with external services, handling of sensitive data and publicly accessible parts of the system. The result should be a clear overview of specific findings prioritised by risk.
Does a security review make sense even if we have never had an incident?
Yes. The purpose of a proactive review is to identify weaknesses before they cause a problem. The team can then address them as part of planned development, schedule fixes appropriately and avoid making major decisions under the pressure of an active incident.
Is a security review the same as a penetration test?
No. A security review can include an assessment of the codebase, configuration, access controls, architecture, integrations and data handling. A penetration test is a specialised form of testing in which the possibility of exploiting vulnerabilities is actively assessed within an agreed scope. If our review identifies an area that requires this level of testing, we will recommend a deeper assessment by a specialised cybersecurity provider.
Is AI-generated code automatically a security risk?
Not automatically, but code created with the help of AI should still go through proper review before deployment. It may work correctly and pass basic tests while still containing overly broad permissions, weak input validation or logic that fails to account for the wider security context of the project. It should therefore undergo the same code review and security checks as any other code.
What should be reviewed in AI-generated code?
Key areas include input and data handling, authentication and permissions, access to sensitive parts of the system, passwords and secrets, external libraries and services, API integrations, error handling and testing. It is equally important to assess how the new code fits into the architecture and security rules of the specific project.
How often should a digital product undergo a security review?
There is no single interval that works for every project. The right frequency depends on the level of risk, the size of the system and how quickly it changes. Particular attention should be paid after major product changes, new integrations, changes to authentication or permissions, the introduction of new types of data and significant updates to technologies or dependencies.
Do cybersecurity risks affect smaller online stores and digital products too?
Yes. Attackers do not necessarily target a specific company. They may instead search for systems using a particular technology, vulnerable library, plugin or misconfigured service and then attempt to exploit any weaknesses they find. The way a project is built and protected therefore matters more than the size of the company behind it.
What will we receive after a security review?
The outcome should be a clear overview of identified weaknesses, their severity and the recommended next steps. For bart.sk projects, we also distinguish between improvements that can be implemented directly as part of ongoing development and areas that would benefit from deeper assessment by a specialised cybersecurity provider.
