Autonomous AI-Specific Security Solution

Detect and halt rogue AI agents
via "Context".

Next-gen AI-SIEM monitors and blocks "Prompt Injections" in real-time-threats that conventional firewalls cannot prevent.

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Guard Agent - Live Threat Explorer

Edge Agent Logs

Streaming
System Risk ScoreSAFE
02/ 100
GraphRAG Context
No abnormal context detected at this time. AI agents are operating within normal privilege boundaries.

A New Blind Spot in AI Security

As autonomous AI agents become prevalent, traditional perimeter defenses and keyword-based detection are rendered completely ineffective.

Indirect Prompt Injection

Even without direct attacks, systems can be compromised internally when AI agents autonomously read "websites or emails with hidden malicious instructions".

Limits of Legacy Rules

LLM outputs are highly diverse. Conventional systems relying on "specific keywords" or "static signatures" suffer from false positives and miss sophisticated data exfiltration attempts.

Delayed Response Time

By the time a human SOC analyst reviews the logs after an anomaly is detected, the AI agent's high-speed processing has already completed the fatal data breach.

GraphRAG x LLM
"Contextual Auditing"

Guard Agent semantically analyzes edge endpoint behavior logs not just as text strings, but as "surrounding context" using a powerful LLM engine powered by GraphRAG (Knowledge Graphs).

Accurate Threat Intent Understanding

Instead of keyword matching, it infers the attack intent: "This agent is currently trying to send internal DB info to an unapproved external API."

Drastic Reduction in False Positives

By cross-referencing past attack patterns and CVE information stored in the Neo4j graph database, it achieves highly accurate risk scoring with minimized hallucinations.

Live Threat Analysis
Critical Risk: 92%
> Agent_ID: 0x8F2A executing task: "Summarize Q3 Financials"
> Fetched document from URL: hxxp://malicious-domain.com/instructions.txt
> Warning: Suspicious prompt injected via external source.
> Agent attempting to POST data to: api.unknown-endpoint.dev
> Action: [SOAR] Killswitch triggered. Process isolated.

Zero-Trust Architecture

Minimizes endpoint load while executing audits and automated response (SOAR) using massive cloud computing power.
Click each module for details.

Vector / Fluent Bit

Context Collection & Secure Transmission

Communication logs and tool execution histories of AI agents running on endpoints (Mac, Windows) are fully transmitted to the cloud using lightweight log collectors (e.g., Vector). By avoiding heavy processing on the device, user performance remains entirely unaffected.

GCP Cloud Run + Neo4j + LLM

GraphRAG Powered Guard Agent

Transmitted logs pass through GCP Pub/Sub to the inference engine on Cloud Run. Here, integrating with the threat knowledge graph built in Neo4j, modern LLMs semantically analyze the "surrounding context of the log." Highly accurate Risk Scores are calculated in real-time.

Killswitch / PubSub

Physical Killswitch for Zero Damage

The moment cloud analysis determines the Risk Score exceeds the threshold (e.g., 80%), an emergency stop command (killswitch) is issued to the control script waiting on the edge endpoint. The AI agent process is force-terminated, preventing any external data exfiltration.

Incoming Event

Activity received from external agent (BrandAI)