Autonomous Threat Response Platform

Autonomous
Threat Response Platform

AEGIS is the first platform that autonomously converts live threat intelligence into validated, infrastructure-specific risk findings and remediation guidance — in under 60 seconds.

aegis — autonomous threat response
$ aegis respond --target prod-environment
[INGEST] Parsing 12 threat feeds... ✓
[TRIAGE] Scored 847 indicators → 23 high-relevance
[SIMULATE] Running polymorphic attack chain simulations...
  → 5 polymorphic mutation strategies applied
  → 142 unique kill chain variants generated
[DETECT] 3 coverage gaps identified in EDR rules
[RESULT] P_breach: 0.034 (95% CI: 0.021–0.048)
[ADVISE] Prioritized advisory delivered → Sigma rules + remediation steps
  → End-to-end: 43.2 seconds | No human initiation
The Problem

The Threat Has Evolved

Your threat intel team discovers a vulnerability. They enrich it, triage it, hand it to the red team. Days later, the SOC gets a report. Attackers using AI move in hours.

71%

of security leaders expect AI-driven attacks in 2026

< 4 hrs

average time from AI-generated exploit to first breach attempt

300%

increase in automated attack campaigns since 2024

The Gap: The intelligence platforms stop before simulation. The simulation platforms start after intelligence. Defenders need a system that closes the intelligence-to-action loop autonomously.

The Solution

Autonomous Threat Response

AEGIS is the first platform that autonomously converts live threat intelligence into validated, infrastructure-specific risk findings and remediation guidance — in under 60 seconds.

Intelligence-Driven

Every simulation starts from live threat data, not static playbooks. AEGIS tests you against what's actually targeting your sector right now.

Fully Autonomous

AI agents execute the full pipeline with no human initiation. Analysts supervise and decide; the system does the analytical heavy lifting.

Action-Complete

The output isn't a risk score or a report. It's a prioritized advisory with specific detection rules, remediation steps, and compound risk analysis.

Safe by Design

Non-destructive simulations with cryptographic scope locking, kill switches, and full audit trail. No production systems harmed.

The Pipeline

How It Works

From raw threat intelligence to a validated, prioritized advisory — autonomous AI agents, zero human initiation.

01

INGEST

Ingestion Agent parses live feeds, resolves entities via LLM-powered extraction from 12+ threat intelligence sources.

02

TRIAGE

Triage Agent scores relevance to YOUR infrastructure — only high-value, contextually relevant threats proceed.

03

SIMULATE

Simulation Agent runs polymorphic attack chain simulations across your infrastructure — fully autonomous.

04

DETECT

Detection Agent maps gaps in your SIEM, EDR, and NDR coverage. Generates Sigma rules for blind spots.

05

ADVISE

Advisory Agent delivers prioritized remediation with Sigma rules, SPL queries, and specific detection guidance.

45 seconds from CVE publication to actionable advisory
Core Technology

Polymorphic Attack Chains

Real attackers don't follow a script. They adapt, pivot, and mutate. AEGIS generates every viable variant of an attack chain — not just the textbook path.

Five Mutation Strategies

Vuln-First

Anchors kill chains on confirmed CVEs in your environment. Prioritizes paths that weaponize known, unpatched vulnerabilities.

TTP-Rotation

Swaps equivalent ATT&CK techniques at each stage. Models attackers who vary tooling to evade signature-based detection.

Actor-Emulation

Constrains mutations to the known TTP repertoire of a specific threat group like APT29 or LockBit.

Evasion-Optimized

Selects technique variants that minimize detection probability. Finds the paths your SIEM/EDR stack is most likely to miss.

Lateral-Expansion

Maximizes blast radius from a given entry point. Models how attackers spread across network segments to reach high-value targets.

Why This Matters

78%

of real-world breaches used technique variants not in the original threat intel report

+34%

average increase in attack chain success rate when polymorphic variants exploit unpatched CVEs

5x

more attack paths discovered vs. static playbook simulation — exposing hidden blind spots

5 polymorphic mutation strategies · Bayesian updating from live adversarial intelligence · Infrastructure-specific risk context
Competitive Edge

Why AEGIS

Every vendor answers a question. The question defines the value ceiling.

Threat Intelligence
What's out there?

Aggregates threats but doesn't evaluate your exposure.

Vulnerability Management
What's unpatched?

Identifies CVEs but doesn't validate exploitability.

BAS / Pentest
Can this attack succeed?

Tests specific paths but disconnected from live intel.

AEGIS

“What attacks are coming for us, how would they play out, where are we blind, and what should we do about it right now?”

Legacy Pen TestBAS PlatformsAEGIS
Frequency
Annual / quarterly
Scheduled scans
Continuous 24/7
Intelligence Source
Manual research
Static playbooks
Live adversarial intelligence
Risk Quantification
Severity ratings
Binary pass/fail
Probabilistic P_breach
Attack Modeling
Single path
Pre-defined chains
Polymorphic attack chains
Remediation Output
PDF report
Technique count
Sigma rules + remediation steps
Autonomous Coverage
None
Limited
Full intelligence-to-advisory loop
Human Initiation
Required
Required
Zero — fully autonomous

Moat: Autonomous threat response is a fundamentally different paradigm — not an incremental feature. Three patented technologies protect the moat. The Bayesian attack graph engine and simulation framework are built on 12,000+ labeled adversarial intelligence training examples.

The Future of Defense
Is Autonomous

Intelligence-driven. Fully autonomous. Action-complete. From raw threat data to prioritized advisory — in under 60 seconds.