Artificial intelligence requires a new kind of security. In recent days, we have witnessed the public emergence of systems such as OpenClaw. And beyond the headlines and grandiloquent, marketing-driven statements, there is a clear reality that I have been warning about for a long time: classical cybersecurity is no longer sufficient, and new approaches are required.
No, classical cybersecurity has not become obsolete primarily because of quantum computing—although that will also have an impact in the near future—but because modern artificial intelligence has introduced new paradigms that break with traditional security models.
OpenClaw is merely a symptom. It is the “trend” of the moment. But behind this trend—and behind all the “jokes” such as MoltBook, MoltMatch, RentAHuman, and those yet to come—there is an evident reality: these trends have far more substance than they appear to have, and they clearly point the way forward. A path we must learn to navigate, one that demands new tools for new systems.
We are no longer talking about incremental improvements to previous security solutions. We are talking about new elements and new solutions that, quite simply, did not exist until now.
I have been saying this for a long time to my client companies, to my students, to anyone who asks me, and in all my public talks: traditional security is no longer enough. It still serves certain purposes, but in increasingly limited and often automated ways, and it is clearly insufficient to protect advanced AI systems. Artificial intelligence requires a new form of security. And this is where my work is focused: cognitive cybersecurity for artificial intelligences.
The Cognitive Security Approach for AIs
If AI is becoming increasingly “human” in the way it reasons, interacts, and makes decisions, we should treat it as quasi-human. If its “mind” presents clear analogies to the human mind, then we should also approach it from a psychological perspective, much as we would a patient.
This principle underpins my thinking, my work, and the services and products I develop and bring to the AI security market.
This is not about doing psychology of AI for speculative purposes, nor about engaging in purely philosophical or metaphysical debates. It is not about discussing abstract questions or determining whether an AI has consciousness or not. This is about real, applicable security.
We are talking about audits, diagnostics, and security solutions based on human psychology concepts adapted to the psychology of machines. And we are not talking about theoretical research detached from business reality: we are talking about applying these approaches directly at the core of any organization that uses AI in its daily operations, regardless of the model, system, product, or service, as long as it relies on LLMs or exhibits emergent cognitive behavior.
Ultimately, this is not about knowing whether an AI will ever be alive. It is about ensuring that it is functional, secure, and reliable; that it operates within clearly defined parameters; that it is explainable, aligned, and controllable. And to measure, evaluate, and guarantee all of this, the traditional tools are no longer sufficient. We need new solutions for entirely new challenges.
Differences and Advantages of Cognitive Security for AIs
Cognitive security applied to artificial intelligence represents a radical paradigm shift compared to classical cybersecurity.
Rather than focusing exclusively on external vectors, perimeters, exploits, or technical vulnerabilities, cognitive security analyzes the internal behavior of the system: how it reasons, how it responds to adversarial stimuli, how it manages conflicts, contradictions, external pressure, or attempts at manipulation.
This approach makes it possible, among other things, to:
Detect cognitive instabilities, emerging biases, or dangerous response patterns.
Evaluate the mental resilience of AI systems against techniques such as prompt injection, jailbreaking, or contextual manipulation.
Measure the system’s coherence, alignment, and self-control in real-world scenarios.
Audit AI not only for what it does, but for how and why it does it.
It is within this context that CiberIA is positioned as a global system, and AIsecTest as a key tool for cognitive evaluation and internal security assessment of artificial intelligences. Not as a complement to traditional security, but as an essential layer for this new reality.
Artificial intelligence is no longer just software. It is an operational cognitive system. And as such, it requires security that is equal to its nature and its impact.
@gcjordi - CibraLAB
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