The attack no longer keeps to human timescales
AI4Business argues that the idea of being able to prevent every cyber breach is now outdated. For a CISO, prevention remains central, through timely updates, network segmentation, reduction of the exposed surface, and continuous monitoring. However, according to the source, building the entire strategy on the assumption of blocking any threat is a bet that does not hold up in the current technology landscape.
The factor that changes the rules, the outlet writes, is the speed of artificial intelligence. When Anthropic presented Claude Mythos, described as a system capable of identifying zero-day vulnerabilities and turning them into operational exploits in a very short time, the signal to the market was clear: the gap between the existence of a flaw and unauthorized access tends to disappear. This is not, the source warns, a matter of giving in to catastrophism, but of assessing a cyber risk that travels at machine speed.
The barrier falls: what matters is getting back to operational status
AI4Business recalls that historically the bottleneck for cybercriminals was not the discovery of vulnerabilities, but the development of effective exploits and their large-scale distribution—activities that required skills, time, and resources. Tearing down this barrier compresses execution times, multiplying attempts and the number of targets hit simultaneously. Security teams, for their part, remain constrained by maintenance windows, partial automation, and trade-offs dictated by business continuity.
The source clarifies a point it considers often misunderstood: backup is not prevention. A backup copy does not stop an exploit, does not block a zero-day, and a recovery plan does not act as a firewall. According to AI4Business, those who present backup as a preventive shield are offering a misleading view. But once the perimeter barrier is breached, it is recovery that becomes the decisive control: the concrete danger for organizations is not the abstract idea of a breach, but its consequences—namely interrupted services, encrypted or deleted data, reputational damage, and challenges from authorities.
The second threat: AI vandalism
Alongside external attacks, the source identifies a frequently underestimated risk in the growing adoption of autonomous AI agents with broad operational privileges in IT, designed to optimize systems, migrate archives, clean repositories, or correct configurations. If an agent misinterprets a command or acts on imprecise context, it can corrupt or delete large volumes of data in moments, bypassing traditional perimeter controls.
AI4Business calls this phenomenon AI vandalism: a risk to data integrity that arises from internal automation. The protection strategy must therefore address two parallel threats: the speed of external attacks and the possible excesses of internal automation. The key question becomes whether, in the event of an incident, the company knows how to restore systems quickly, completely, and verifiably. The source sets out four principles for effective protection in a SaaS environment, without detailing them in the text. The specific contents and the scope of the claims about Claude Mythos therefore remain to be verified.
