How Vectra AI Detects AI Threats in Infrastructure

According to public research by Vectra AI, cybercriminals increasingly rely on operations based on the Model Context Protocol (MCP). This approach allows for the creation of architectures where numerous autonomous agents work simultaneously in a ‘swarm behavior’ format.

Some components focus exclusively on reconnaissance of the target environment, while others look for vulnerabilities or prepare the infrastructure for data exfiltration. This model transforms cyberattacks into an asynchronous, event-driven mode, where agents connect only as needed to quickly complete local tasks and exchange intelligence.

The most difficult challenge for security professionals is the almost perfect masking of such activity. These operations generate traffic that appears as legitimate inquiries to corporate AI tools, negating the use of traditional signature detection methods.

Moreover, the ‘swarm approach’ enhances the capabilities of attacks. Thanks to the parallel work of agents, they quickly exchange information and can continue executing tasks even when one of them is detected or blocked.

The effectiveness of automated tools for attacks is also confirmed by practical experiments in large working networks. Researchers led by Stanford University deployed the AI agent ARTEMIS in a real network with approximately 8000 hosts and tasked it with searching for vulnerabilities alongside professional analysts.

As a result, the artificial intelligence system identified 9 real security issues. It ranked second overall and performed better than 9 out of 10 experts who participated in the study.

Another confirmation of large-scale automation came from a case reported by the company Anthropic. They announced the shutdown of a major espionage group that used AI to manage its operations.

All this indicates that AI-driven attacks are no longer just a theoretical concept—such approaches have begun to be used in real cyber incidents.

Despite their high autonomy and ability to self-learn, cybercriminal tools have an important limitation—they cannot achieve their goal without interacting with the corporate infrastructure.

Attack stages such as reconnaissance, lateral movement within the network, and access to sensitive data always occur through network connections. Therefore, regardless of whether it’s a person or an AI-based system, any attack ultimately goes through the network.

Autonomous agents can act faster and require less manual control, but to complete their tasks, they still use the same network channels.

That’s why analyzing network behavior remains a reliable way to detect threats: it focuses not on the attack tools, which constantly change, but on suspicious actions within the network.

Stopping modern agent threats is impossible through detecting specific prompts or classifying new types of malware.

The AI-based NDR solution (Network Detection and Response) from Vectra AI exclusively focuses on analyzing network behavior. The platform uses advanced machine learning models to extract genuine threats from overall informational noise, enabling response to malicious activities before damage occurs.

Additionally, the Vectra AI toolkit addresses the issue of shadow applications. The platform ensures the necessary visibility of internal AI usage by company employees.

Thanks to this, security specialists can monitor both authorized and hidden services in complex hybrid environments.

The integration of autonomous systems radically accelerates and masks cyberattacks, allowing complex multi-step campaigns to unfold almost without human intervention. The asynchrony of communication and masquerading as legitimate requests make agent threats invisible to outdated signature-based control systems.

iIT Distribution is a Value-Added distributor and a reliable partner that helps implement modern information security solutions, including Vectra AI technologies.

Our team supports projects at all stages: from technical consultations and IT infrastructure assessments to training specialists and full-fledged implementation of NDR systems.

Thanks to experience and direct cooperation with manufacturers, the company helps organizations create a reliable system for detecting and countering cyber threats in modern hybrid networks.