Agent Nautilus™ for IBaseIT
Empowering IBaseIT's Cyber Security Practice
with the most precise threat detection on the market.
with the most precise threat detection on the market.
The Growing Cyber Security Crisis: From Vulnerabilities to Impact
The path from system vulnerabilities to financial damage reveals an increasingly concerning picture of cybersecurity in 2024.
1
Initial Vulnerabilities
Only 2% of disclosed vulnerabilities are weaponized, but this small fraction drives massive impact. 31% have public proof-of-concept exploits available.
2
Growing Exploitation
38% of intrusions gained access through vulnerability exploitation in 2023 - a 6% increase from previous year. 97 zero-day vulnerabilities were exploited in the wild, marking a 56% surge from 2022.
3
Attack Vectors Diversification
Beyond vulnerabilities, credential theft through infostealers and social engineering remains a primary attack vector, creating multiple paths for breaches.
4
Devastating Financial Impact
- $4.88M: Average cost per data breach incident in 2024
- $9.5T: Worldwide cybercrime damages projected for 2024
- $2M: Average ransomware payout, a 5x yearly increase
This escalating crisis is further amplified by inherently insecure systems and the emerging use of AI in cyber attacks, creating a perfect storm of cyber insecurity.
Introducing Agent Nautilus
The First Cyber Transformer
Agent Nautilus, first deployed in 2020, employs an auto-regressive transformer model pre-trained on cyber data. This advanced model is designed after biological structures, assigning genomes to digital actors and mapping the genes that form their behaviours.
Through the identification and assignment of disease markers and environmental variables, Agent Nautilus enriches the genome and forms a high dimensional picture of your digital world. The transformer analyses the context of each datapoint and differentiates between critical and non-essential, bypassing irrelevant information for enhanced efficiency and speed in threat detection.
Tailored for cybersecurity, and continuously trained on operational and network data from IT to OT, critical infrastructure, public institutions and even cyber battle-zones, the Agent Nautilus transformer can leverage nearly any time-series data to identify and focus on actionable intelligence, ensuring precise detection of cyber threats.
Agent Nautilus: Advanced Genomic AI Architecture
Powered by the high-dimensional ICG transformers, Agent Nautilus represents the most sophisticated threat detection engine in cybersecurity, combining hundreds to thousands of dimensions of data analysis with real-time behavioral learning.
1
High-Dimensional Data
Each dimension encodes nuanced telemetry data across IT, OT, and IoT systems, processing device behaviors, time-series interactions, and communication patterns simultaneously. Self learning models expand and contract based on environmental needs.
2
Self Learning
Integrates historical data to map cyber genes and disease markers, creating a deep context of beharvioural information and identifying potential vulnerabilities through sophisticated pattern analysis and behavioral markers forming the foundation for threat detection.
3
Real-Time Behavioral Analysis
Leverages transformer's self-attention capabilities to process massive time-series datasets in parallel, adapting the model and detecting subtle modifications indicative of security breaches.
4
Advanced Threat Detection
Outperforms traditional tools by identifying and neutralizing sophisticated threats through deep behavioral analysis, exposing even stealthy actors using legitimate credentials.
Disrupting The Cyber Kill Chain
Agent Nautilus™ delivers unmatched speed, outperforming outdated threat detection tools reliant on heuristics or legacy ML models that act only after obvious impact. Its deep behavioral analysis identifies and neutralizes sophisticated threats by detecting subtle anomalies, exposing even the stealthiest actors — including those leveraging legitimate tools and credentials to live off the land.
Operational Impact & Business Value
Agent Nautilus delivers transformative value across the enterprise security landscape, enabling organizations to detect and respond to threats with unprecedented precision and speed.
Enhanced Threat Detection
Reduces false positives by up to 90% while increasing detection rates across sophisticated attack vectors, including zero-day threats and advanced persistent threats (APTs).
Operational Efficiency
Streamlines security operations by automating complex analysis tasks and providing actionable insights, reducing mean time to detect (MTTD) and respond (MTTR) to incidents.
Scalable Protection
Seamlessly adapts to growing infrastructure needs while maintaining consistent performance across distributed environments and diverse technology stacks.
By leveraging its advanced capabilities, organizations can significantly strengthen their security posture while optimizing resource utilization and operational costs.
Summary: Empowering Dynamic Cybersecurity
Real-Time Threat Detection
Advanced AI-powered analytics identify and alert on potential security risks and vulnerabilities as they emerge.
Complete Asset Visibility
Discover and monitor all digital assets across your infrastructure, including cloud, on-premise, and hybrid environments.
Communication & Transparency
Dashboards and reports provide real-time visibility for security teams and executives.
Seamless Integration
Effortlessly connects with existing IBaseIT tools and security infrastructure for enhanced operational efficiency.
Disambiguate and normalize any time series data source or event log. Find the threats other systems miss without any of the noise.
Part II
Powering Cyber Agentic Architectures
Speed, Resilience and Efficient Access to Data
Architecture for Cyber Agentic Workflows enables powerful, adaptable systems through interconnected intelligent components driven by Agent Nautilus.
1
Scalability & Flexibility
Agents can be scaled and customized to meet specific needs and adapt to changing environments.
2
Modularity & Integration
Extensible and specialized agents operate as discrete entities within a cohesive system.
3
Holistic Intelligence
The behaviour engine contextualizes activities and provides agents an orchestrated intelligence.
4
Continuous Evolution
Models evolve over time, achieving greater accuracy while testing new forecasts.
5
Governance & Compliance
Comprehensive orchestration logs capture an end-to-end record of every decision.
Cyber Agent Architecture: Models & Implementation
Behavioral Models
Response & Goal-Based Agents
Autonomous agents executing threat responses and planning goal-oriented actions.
Utility & Reflex Models
Combines simple reflexes with utility optimization for balanced decision-making.
Model-Based & Hierarchical
Internal environment modeling within multi-level decision hierarchies.
Super-Agent Implementation
Core Detection & Integration
Agent Nautilus™ for threat detection and Data Tapestry™ for cross-platform integration.
Orchestration & Defense
Orchestrator Super Agent coordinates workflow while Cyber Defender provides automated response.
Security Validation
Cyber Red Team Level 1 conducts automated penetration testing and security validation.
A Shift to AI Driven Agentic Cybersecurity
AI-Driven Automation
AI can automate threat detection, orchestrate incident response, and manage security tasks, freeing up human experts for strategic initiatives.
RLHF: Human Capabilities
Human expertise and feedback is crucial for training, and governing AI-driven security and provides the foundations for training the models and evolving their capabilities.
Better Threat Detection Through Continuous Learning & Adaptation
Enhanced Contextual Awareness: Self-attention allows the model to capture long-range dependencies enabling it to better understand the context and relationships between different parts of your cyber space.
Improved Feature Extraction: By selectively focusing on relevant parts of the input, self-attention helps extract more meaningful data, leading to faster and more accurate vulnerability detection.
Agent Nautilus: A Harmony of Three
Behavioral Analysis AI
The core of the solution is an AI driven engine that models normal and abnormal behavior to detect threats and anomalies.
Specialized Security Agents
Agents make the analysis actionable, taking on specific security tasks, such as threat detection, event correlation, incident orchestration or automated response.
Agent Aurea Data Tapestry™
The Tapestry™ enables the right agents to seamlessly access and act on the right information, functioning as an interconnected, multidimensional framework that dynamically integrates and contextualizes diverse data streams, facilitating real-time, bi-directional communications across boundaries and through both serial and parallel relationships.
Human Interaction with the System
Communication and Publishing Layer
GenAI and publishing tools have enabled a constant evolving publishing platform. Our LLM bridges the gap, enabling integration with nearly any visualization or reporting tools as well as rich workflow enablement. The system also bridges the AI-to-Machine divide via the same channels. Agent Bartok regularly exchanges with Co-Pilot, Gemini, Mistral and more.
Agent Bartok via Teams
Agent Barok via Web
Talking Avatars
synthesia.io
Agents can be run within the ICG LLM framework, the ICG SaaS Platform & SOA, or interfaced with via any web standard into SIEMs, dashboard solutions, automation or any other publishing tool.
Data Pipelines & Compatibility
1
Time Series Models
Analyzes historical security data for trending anomalies or suspicious spikes.
2
Compatibility Framework
Ensures seamless integration with diverse security tools, logs, and endpoints.
3
Threat Intel / Benchmark Partners
Ingests curated threat intelligence feeds or industry benchmarks, like CVE databases and ISACs.
Attribution Engines
Training Attribution Engine
Trainings and agents developed within the system are attributed to their authors and derivatives are tagged downstream.
Threat Attribution Engine
Traces threats and their impact back to their origins, identifying responsible actors and their motivations.
App Store-like Solution
Offers a centralized marketplace for AI models and agents, facilitating discovery, deployment, and monetization.
AI Workflow with Data Management
Getting Alerts Where they Need to Go and RLHF
1
Data Science Management & Training
Builds and updates the ML models behind threat detection, anomaly identification, and other security tasks.
2
Workflow & Inference
Operational layer that runs inference in real-time, connecting to live traffic logs, EDR, or SIEM systems.
3
Governance & Orchestration
Enforces access control and entitlement, compliance requirements, orchestrates agent actions, and logs activities for auditing.
Part III: A Deeper Review of Cyber Agentic Workflows.
Cyber Agentic Architecture
Agent Nautilus & ICG Dataflows: A Closer Look
1
Data Sources & Initial Collection
2
Compatibility Framework
3
Data Pipelines & Trend Analysis
4
AI Workflow & Behavioral Context Engine
5
Agentic Workflow Orchestrator
6
Communication & Publishing Layer
7
Continuous Feedback & Enhancement
8
Storage & Long-Term Archives
1. Data Sources & Initial Collection
Sensor Observations
Network traffic logs, security events, endpoint activity, and other sensor data.
Raw Security Logs / SIEM
Logs from firewalls, intrusion detection systems (IDS), endpoint protection (EDR), and other security devices.
Any Time Series Data Source
Agent Nautilus can disambiguate and de-noise any time series dataset. The contextual analysis capabilities enable the rapid identification and correlation of actors via the ICG Genome, quickly and efficiently cutting through data that provides no value to the targeted outcome.
2. Compatibility Framework: Normalization & Disambiguation
1
Schema Alignment
Maps varying fields into a consistent format for seamless processing by downstream modules.
2
Disambiguation
Resolves conflicting identifiers, ensuring that all events refer to the same entities.
3
Metadata Tagging
Assigns standardized labels to events, providing clear context for downstream analytics.
3. Data Pipelines & Trend Analysis: Heuristic Models & Threat Intel
Heuristic Models
Leverage heuristic models and analyze historical data to establish baselines and identify suspicious patterns using threat intel and market CTI.
Threat Intel Integration
Cross-references ingested data with known IoCs and threat intelligence feeds to identify potential threats.
4. AI Workflow & Behavioral Context Engine (Agent Nautilus)
Behavioral Context Engine
Continuously learns from data, identifying normal behavior and flagging anomalies.
Workflow & Inference
Interprets anomaly signals in real-time, deciding whether to escalate, log, or correlate further.
5. Agentic Workflow Orchestrator: Central Coordination & C2 Channels
1
Receiving Alerts
Monitors the system for suspicious activity, receiving alerts from the behavioral context engine and heuristic models.
2
Task Routing
Dispatches tasks to specialized agents based on the nature of the alert and the required response actions.
3
Feedback Loop
Receives status updates from agents, enabling continuous learning and adaptation to new threats.
6. Communication & Publishing Layer: Transparent Visibility for All Stakeholders
1
Security Posture Report
Provides up-to-date insights on an organization's security posture, enabling informed decision-making.
2
Incident Response Playbook
Auto-updates with recommended remediation steps, guided by active incidents identified by the orchestrator.
3
Real-Time Threat Scoreboard
Displays ongoing threats, newly detected anomalies, and their current status in real-time dashboards.
7. Continuous Feedback & Enhancement: Learning from Experience
Incident Outcomes
Learns from confirmed alerts and false positives, enhancing future anomaly detection.
Model Refresh
Periodically retrains AI models with new data, ensuring they stay current with evolving threats.
Self-attention enables the model to capture context and extract meaningful features, enabling better understanding of data and more accurate threat detection.
8. Storage & Long-Term Archives: Data Retention and Compliance
1
Model Repository
Stores all active ML models and past versions for rollback or compliance checks.
2
Compliance Logs & Records
Logs every action taken for regulatory audits, ensuring compliance with relevant standards.
3
Forensic Data Archives
Retains high-detail event traces for in-depth investigations and legal evidence.
Part IV
Enabling the Cyber Agentic Framework
The market contains and is quickly evolving a comprehensive suite of cyber agents. ICG Agent Nautilus enables works in harmony to protect, detect, and respond to threats across your entire ecosystem by empowering C2 and incident response.
Functional, Detection & Monitoring Agents
1
Scanning & Asset Discovery
Maps threat surfaces, discovers assets, and continuously monitors network activity for comprehensive visibility.
2
Data Processing & Analysis
Ingests and normalizes logs, processes data, and performs analysis to support informed decision-making.
3
Risk Assessment
Evaluates potential business impact of threats and provides risk mitigation strategies based on NIST 2.0 and MITRE ATT&CK frameworks.
4
Correlation & Intelligence
Combines signals from multiple sources and maintains continuous learning feedback loops for improved threat detection.
Behavarioual Agents
1
Alert & Communication
Manages the alerting pipeline and facilitates system-wide communication for coordinated responses.
2
Threat Response
Executes incident response playbooks and automates containment and remediation actions.
3
Compliance & Documentation
Creates audit trails, generates compliance reports, and maintains comprehensive security documentation.
4
Orchestration & Coordination
Oversees workflow management, task allocation, and collaboration between different agent systems.
Evolution of Cyber Agents: From Basic Models to Super Agents
The cyber agent ecosystem encompasses multiple levels of sophistication, from fundamental behavioral models to advanced super-agents, creating a comprehensive security framework.
1
Foundation: Basic Agent Models
- Simple Reflex Agents: Direct threat response without state maintenance
- Model-Based Reflex Agents: Internal environment modeling for informed decisions
- Goal-Based Agents: Action planning for specific security objectives
- Utility-Based Agents: Risk-reward optimization through utility functions
2
Functional Implementation
- Scanning & Monitoring Agents: Network surveillance
- Data & Analysis Agents: Threat detection and processing
- Task & Response Agents: Automated operation execution
- Communication & Coordination Agents: System-wide orchestration
3
Advanced Integration
- Hierarchical Agents: Multi-level decision making
- Directed Acyclic Graphs: Optimized task execution
- Cross-functional Teams: Combined monitoring and response capabilities
4
Super Agent Evolution
- Agent Nautilus™: Advanced threat detection engine
- Data Tapestry™: Cross-platform integration
- Cyber Defender & Red Team: Automated security operations
This hierarchical structure enables comprehensive cybersecurity coverage, from basic threat response to sophisticated system-wide protection.
ICG Cyber Super-Agent Library: Advanced AI for Enhanced Security
1
Threat Detection Super Agent (Agent Nautilus™)
The core behavioral analysis engine, providing advanced threat detection and anomaly analysis.
2
Data Tapestry ™ Super Agent
Connects and integrates diverse security tools, across language, vendor, timezone and platform, enabling seamless communication and data sharing.
3
Orchestrator Super Agent
Coordinates and manages the overall workflow, orchestrating the actions of various agents to optimize security operations.
4
Cyber Defender Agent Level 1
Automated threat response agent, working alongside SOC operators to quickly and effectively contain threats.
5
Cyber Red Team Level 1
Automated pen testing and security development validation, ensuring the robustness of an organization's security posture.
ICG Cyber Agent Library: Agent Bartok - Intelligent Web Integration via Synthesia
Key Capabilities
- Direct integration of the Agent Nautilus threat detection capabilities and alerting via the Synthesia workflow
- Llama 3.2 LLM powered with the ICG Nautilus network observations and threat detection capabilities.
- Deliver key observations and alerts to staff via the video avatar workflow.
- Generate GRC and reporting by querrying the system in natural language
ICG Cyber Agent Library: Agent Bartok via Web
- Direct integration of the Agent Nautilus threat detection capabilities and alerting.
- Llama 3.2 LLM powered with the ICG network observations and threat detection capabilities.
- Directly query and interrogate your entire network stack directly from Teams.
- Generate GRC and reporting by querrying the system in natural language.
- Build integrations and APIs directly from the chatbot into approved python sandboxes..
Cyber Agent Library: Agent Bartok via Co-Pilot
- Direct integration of the Agent Nautilus threat detection capabilities and alerting.
- Co-Pilot powered LLM interaction with the ICG network observations and threat detection capabilities.
- Directly query and interrogate your entire network stack directly from Teams.
- Co-mingle Sharepoint folders and stacks, such as your IR manuals or specifications.
- Generate GRC and reporting directly from inside Teams to Business Central.
Risk Value Cyber Agent
Return on Resilience
Demonstrate the value of your cyber investments. Understand the implications and financial value of cyber projects and incidents.
Vulnerability Analysis
Understand the financial implication of vulnerabilities, risks, and threats on your organization.
Financial Implications
Evaluate the cost of remediation, risk mitigation, and the potential financial impact of a cyberattack.
Return on Resilience Models
The LLM facilitates rapid ingestion of financial models and calculations. Here we have trained the LLM on the Accenture Return on Resilience model.
Example ticket using the Threat Attribution and Price Value Engine Co-Mingled with a Real Alert:
A data privacy violation involving ACME Integrator's power customer in Texas, Big Energy Co, could have significant consequences for both companies. Based on the Accenture Return on Resilience (RoRes) model and market trends, we can assess the potential impact:
Financial Impact
- Direct Costs: The average cost of a data breach in the energy sector was estimated at $4.78 million in 2023. For a major utility like Big Energy Co, this figure could be substantially higher.
- Regulatory Fines: Energy companies face strict data privacy regulations. Violations can lead to substantial fines, potentially reaching millions of dollars per incident.
- Lost Business: Cyber-resilient companies experience 16% higher incremental revenue growth. A major breach could reverse this advantage, leading to significant revenue loss.
Operational and Reputational Consequences
- Service Disruption: While the data breach doesn't represent risk to power systems, it does potentially impact individual customers through account compromise.
- Trust Erosion: Cybersecurity breaches severely damage trust between energy companies and their stakeholders, impacting customer retention and investor confidence.
- Long-term Impact: The reputational damage from a significant breach can have lasting effects on both Big Energy Co's and ACME Integrator, potentially affecting future contracts and partnerships.
Broader Implications for ACME Integrator
- Contract Loss: ACME Integrator's contract with Big Energy Co, valued at $173.5 million in 2019, could be at risk if a major breach occurs due to ACME Integrator's services.
- Industry Reputation: As a key IT service provider in the energy sector, a significant breach could damage ACME's reputation across the entire industry.
- Legal Liability: ACME could face legal action from Big Energy Co or affected customers, leading to additional costs and reputational damage.
- Market Value Impact: ACME Integrator's stock value could be negatively affected, as evidenced by the 3.44% drop following a recent ransomware incident.
Cyber Agent Library: Agent 16.18 Network Sensors
Plant & Field Sensor Agents
Software Based Sensor Agents
SNAP
Prioritized workflow management with automated ticket assignment and orchestration
Windows
Smart playbooks and correlation engines to accelerate threat investigation and remediation
Open Source
Available via git hub, simply run packet capture capabilities to a directory accessible by the agent and feed time series data into ICG and Agent Nautilus.
Together, these agents provide end-to-end coverage from physical sensor monitoring to intelligent ticket management, creating a unified security operations framework.
SaaS Ticket Management Agent
Prioritized alerts
Management and delivery workflow, ticket assignment and follow-up via a event orchestration system.
Recommended playbooks
Improve productivity and response time to investigate, mitigate, and remediate threats.
Aggregation and correlation of events
Global visibility and streamlined event triage: disrupt the progression of the cyber kill chain.
Accurate Assets, Inventory & Threat Surfaces
Not just a list - assets categorized by device type for pinpoint insight.
Cyber Agent Library: Visualization & Publishing via Mermaid.live
Flow Diagrams
Create dynamic flowcharts and process diagrams to visualize cyber workflows.
Sequence Mapping
Map complex sequences and interactions between system components.
Architecture Visualization
Generate clear visual representations of system architectures and relationships via natural language interactions.
Thank you
Turn the tide with Genomic AI
Casey S. POTENZONE | cp@insightcyber.com
Casey S. POTENZONE | cp@insightcyber.com