Four layers of active defense,one architecture.
MTTAV Engine, Honeypot LLM, Memory Guard and NHI Security operate as one integrated platform, sharing threat intelligence in real time.
Mean Time To Active Vectorization, under 2ms.
The platform core. Detects anomalies at packet level in real time and autonomously neutralizes threats before they reach the target system. No SIEM operates at this time scale.
A trap designed specifically for attacking AI.
A decoy language model embedded in client infrastructure, deceiving AI agents, drawing them into a trap, revealing attack methods and delivering threat intelligence.
LLM
INFRA
Protection for AI model context memory.
Verifies the integrity of LLM system context memory in real time using SHA-256. Blocks Memory Poisoning attacks before they can degrade transaction decisions.
Governance for 80% of corporate cloud traffic.
Automatic inventory, classification and monitoring of all machine identities, API keys, service accounts, OAuth tokens. Eliminates invisible attack vectors before they are exploited.
SECURITY
From detection to neutralization in one cycle.
The three-stage defense cycle operates autonomously, no human intervention, no delay.
CAPTURE
MTTAV Engine and Honeypot AI agents detect anomalies at packet and AI traffic level. Every deviation is recorded and classified in real time.
PUNISH
The identified vector is automatically isolated. Suspicious NHI nodes and AI agents are cut off from the infrastructure, before they can cause damage.
PREVENT
Memory Guard and NHI Security harden the entire infrastructure against that attack vector. Knowledge from the incident strengthens global protection.
Powered by advanced anomaly detection, our platform identifies novel, zero-day threats that traditional, signature-based security tools miss. While competitors rely heavily on established threat registries and conventional frameworks such as the FS-ISAC Adversarial AI Framework or FS AI RMF, Qunigma's technology goes further. We detect highly sophisticated and previously unseen attacks by recognizing subtle behavioral deviations, securing your environment against stealthy threats without requiring prior exposure or training data.
Our AI RED Team Engagements are designed to expose critical blind spots that fall outside of standard security frameworks. Qunigma executes highly customized, client-specific attack simulations to test the true limits of your defenses. As the exploitation of AI agents rapidly emerges as one of the fastest-growing threat vectors in the industry, we are proud to be pioneers in this space, proactively securing the advanced vulnerabilities that others overlook.
Zero disruption.
The platform integrates with existing banking infrastructure through standard APIs. No need to replace SIEM, SOC or core banking systems.
Map your blind spots before they are exploited.
AI Security Readiness Analysis
MTTAV Gap Analysis Template, complete and bring to tomorrow's board meeting.
Technical Specification for CTO
Full integration documentation for CTO and Chief Architect.
ROI Matrix: DORA & AI Act
Business case for CFO: TCO vs. regulatory and security risk.