Nebulock

What Nebulock does

Nebulock provides an agentic contextual security analytics platform that continuously hunts, understands, and stops threats before they become incidents. It helps security teams hunt threats across endpoint, identity, cloud, network, and SaaS from a single platform. By focusing on behaviors and TTPs rather than IOCs, teams can correlate weak signals into actionable hypotheses and turn discoveries into automated coverage. The agentic approach brings expert-level threat hunting without additional headcount or specialized expertise. Nebulock is designed to eliminate unknown unknowns and false negatives created by disjointed tools and fragmented processes, bringing proactivity at scale by correlating threat intelligence with organizational context and memory.

Products

• NebulockAn agentic contextual security analytics platform that continuously hunts, understands, and stops threats before they become incidents. It identifies, surfaces, and enriches endpoint and identity-based threats such as credential theft, privilege escalation, and lateral movement, providing proactive findings to reduce dwell time and eliminate false negatives.

Key capabilities

• Hunt-First security operations
• Context Graph for behavioral analysis
• Agentic hunting across the entire threat hunting lifecycle
• Autonomous and continuous hunting across infrastructure
• Deployment of validated detection rules
• AI agents continuously learn and refine detection rules
• AI agents carry context and memory from hunt to hunt
• Operationalization of global threat intelligence
• Hunting for TTPs, not just IOCs
• Telemetry data ingestion and cross-referencing with threat intelligence, past hunts, documentation, governance, and allowlists
• Normalization and resolution of raw events to a single entity across data sources
• Context baselining behavior to quickly detect anomalies
• Continuously updated behavioral graph
• Transparent reasoning on conclusions and durable detection rules
• Integration with existing SOC and SOAR workflows

Use cases

• Close coverage gaps
• Detect insider threats (human and agentic)
• Prevent detection drift
• Baseline normal behavior to understand anomalous activity
• Accelerate investigations
• Proactively find threats others miss
• Correlate weak signals into actionable hypotheses
• Turn discoveries into automated coverage
• Identify credential theft
• Identify privilege escalation
• Identify lateral movement

AI approach

Nebulock uses AI agents for continuous threat hunting, detection, and investigation. The platform ingests telemetry data, cross-references it with threat intelligence, and builds a continuously updated behavioral graph. AI agents act on the entire threat hunting lifecycle, bringing in external threat intelligence, running against the Context Graph, and delivering transparent reasoning on conclusions and durable detection rules. They continuously learn and refine detection rules automatically and carry context and memory across hunts.

Tech named: AI agents, Context Graph, agentic hunting

What it says sets it apart

• Focus on behaviors and TTPs rather than IOCs
• Agentic approach for expert-level threat hunting without additional headcount
• Continuous and context-aware coverage across the security stack
• Correlation of weak signals into actionable hypotheses
• Elimination of unknown unknowns and false negatives
• Proactivity at scale by correlating threat intelligence with organizational context and memory
• Ability to hunt across endpoint, identity, cloud, network, and SaaS from a single platform
• AI agents continuously learn and refine detections, carrying contextual memory

Funding rounds we track

From the AI funding tracker — rounds as reported by the linked publications.