Offensive tools powered by artificial intelligence make it possible to automatically chain attack steps, transforming simple low-critical vulnerabilities into major threats.
The landscape of the cybersecurity has reached a tipping point. The time required to compromise a system has gone from months to minutes, requiring a profound rethinking of our security approaches. It’s not just an increase in the volume of threats; we are witnessing a real paradigm shift.
For years, the industry lived with technical debt, implicitly relying on the know-how and rigor of attackers which gave organizations time to correct discovered vulnerabilities. This balance has just been brutally disrupted by artificial intelligence. It is now possible to carry out attacks at machine speed, transforming the slightest configuration error or unpatched vulnerability into a real opportunity for intrusion.
The “Patchpocalypse” refers to this new reality: companies know how to apply patches, but offensive artificial intelligence identifies, qualifies and exploits vulnerabilities faster than they can be fixed.
Faced with the constant discovery of new vulnerabilities, IT and cybersecurity teams find themselves faced with a queue that has become impossible to resolve: an uninterrupted succession of vulnerabilities to address. There are approximately 15 times more vulnerabilities to address than in the past.
However, applying corrective measures requires testing “non-regression”, ensuring the ability to “backtrack” in the event of side effects, and finding a time to do so without impacting (or as little as possible) the company’s businesses. This exponential growth in the number of vulnerabilities makes these operations impossible in a reasonable time.
The priority is therefore no longer just to prevent a compromise, but above all to limit its consequences and prevent its propagation. Cybersecurity must gradually move from a logic of remediation to a logic of isolation and containment.
The first step consists of drastically reducing the exhibition space: anything that is not intended to be accessible directly from the Internet simply should not be. For all other assets, the objective is clear: favor modern architectures, making it possible to isolate resources, manage, inspect and filter access, and to avoid any “lateral propagation”.
In the era of attacks carried out at machine speed, the survival of a company therefore requires the adoption of a Zero Trust model applied down to its finest level of granularity. Anthropic also made the same recommendation in its document “Zero Trust for AI agents | Claude by Anthropic” In such a model, the existence of “incoming flows from the Internet” on the company’s networks must disappear. Conversely, the use of “deception”, that is to say discouraging attackers, becomes essential.
True Zero Trust is also based on the principle of least privilege, with segmentation of access down to the level of the application, service or workload concerned. This requires strengthening identity management. This very fine granularity today constitutes one of the few truly effective defense mechanisms against lateral movements, transforming a potential compromise of the entire network into an incident limited to a single asset.
Obviously, having dynamic inventories and maps (i.e. permanently up-to-date and exhaustive) is no longer a luxury but a necessity. Particularly in the age of agentic AI.
Finally, the availability of a system is no longer sufficient without ensuring its ability to continue operating despite an attack, which is called “resilience”. The real issue is therefore no longer whether an organization will be targeted, but whether it will be able to prevent a localized incident from turning into a general compromise. Zero Trust is no longer just one transformation strategy among others: it is becoming a condition of operational survival.
