AI for Security: AI-Native Cyber Defense for LLMs, RAG and Agentic AI

AI for cybersecurity uses AI to improve security reasoning, correlation, threat detection, hunting, response, and evidence work while keeping people in control of security decisions. In Cygeniq's AI for Security solution, CyberTix AI also secures the AI you run, LLMs, RAG pipelines, and agents, and defends against AI-powered attacks on the wider enterprise.

Side one is AI-native defense: CyberTix Secure discovers every LLM, RAG pipeline, and agent you run, blocks prompt injection, RAG poisoning, agent abuse, and data egress inline, and detects and contains threats at runtime, across 15 capabilities. Side two is protection against AI-powered attacks: CyberTix Defend detects and stops AI phishing and business email compromise, deepfakes, AI-authored malware, and autonomous intrusions, contains confirmed incidents under human control, and keeps defenses effective as attackers adopt AI, across 12 capabilities. Both share one runtime backbone, one telemetry stream, and the same SOC integrations, and on both sides people still decide. The AI does the volume work under graduated authority.

It moves reasoning ahead of escalation. Instead of an analyst opening dozens of raw alerts, the platform groups them into one candidate incident, checks it against evidence, and returns an explained incident with attribution and a recommended action. That cuts alert fatigue and raises coverage per analyst without adding a data feed the SOC has to watch.

An AI-native SOC is a security operations model where AI does clustering, hypothesis generation, evidence testing, and attribution before a human sees the incident, working inside the SIEM, XDR, and ticketing already in place. Analysts approve actions and set how much autonomy the platform has, per action type, system, or environment.

CyberTix Secure discovers LLMs, RAG pipelines, and agents, including shadow AI, then applies inline protection against prompt injection, jailbreaks, sensitive-data egress, RAG poisoning, retrieval abuse, agent tool misuse, non-human identity risk, and model abuse. Behavioral analytics, traceability, containment, red teaming, policy enforcement, and audit evidence operate from the same runtime backbone.

It means the platform can cluster, reason, recommend, and, where authority is explicitly granted, contain incidents automatically. Autonomy is graduated by action type, system, or environment, and can start in monitor mode before moving to block. Every automated step is logged with its evidence, and analysts remain in control of approvals.

No. It layers on top. CyberTix AI reasons over the telemetry your SIEM and XDR already collect and sends prescriptive actions into your existing SOAR and ticketing for human approval. There is no rip and replace. CyberTix AI deploys inline where enforcement matters and out of band where visibility matters, and integrates with SIEM and SOAR, IAM and non-human identity, DLP, CI/CD, and model gateways or MCP.

Yes. Verity detects cloned voices and synthetic video used to impersonate executives and vendors, and Sentinel monitors brand, domain, and executive impersonation. Because CyberTix Defend shares a backbone with the rest of the platform, those signals are correlated with email, identity, and endpoint telemetry, so a deepfake call and the payment request that follows it are handled as one incident.