SOAR · SOC + SOAR Product Overview

Forensic CyberTech Pvt. Ltd.
SOAR

From alert to closed ticket, automated.

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0k

Tickets per minute — load-tested benchmark, zero drop

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SOAR connectors across firewalls, EDR, threat-intel, email

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Pre-built playbook actions, ready to drop in and use

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Data leakage between client tenants — by architecture

01 — Executive Summary

One platform. Two engines. The complete MSSP security stack.

EagleEyes Platform is a unified Security Operations suite built for Managed Security Service Providers. It combines two purpose-built engines that work in tandem: a high-performance SOC ticketing backend that ingests, enriches, and triages every security alert — and a SOAR automation engine that acts on those alerts the moment they arrive, executing playbooks across your entire security toolset without any analyst keystrokes.

Most MSSPs stitch these two capabilities together from separate vendors, creating hand-off gaps that slow response and complicate audits. EagleEyes builds the bridge into the platform itself: the ticketing engine is the SOAR's native trigger and the SOAR's results are first-class data on every ticket. No webhooks to maintain between them, no mapping fields between schemas, no blame-the-integration debugging when something breaks.

Both engines are fully multi-tenant — a single EagleEyes deployment serves every one of your client organisations with complete data isolation. Built in Rust for the ticketing core, the platform has been load-tested at 50,000 tickets per minute with zero drops.

The Problem

What goes wrong with point solutions and manual workflows?

MSSPs running a SOC face the same three problems, regardless of what tools they use. They're not detection problems — they're operational problems that compound under volume.

Security operations center with unmatched threat detection and response capabilities

Alert volume outpaces human triage

Analysts manually gather context for every alert — IP reputation, geolocation, MITRE mapping — before they can even assess severity. At scale, critical threats sit in a queue while the team works through noise.

Enterprise-scale high-speed security performance visualization

Response is slow, inconsistent, and lives in analysts' heads

Containment means jumping between firewalls, EDR consoles, threat-intel portals, and ticketing tools by hand. Under pressure, steps get skipped. When senior analysts are off-shift, quality drops and there is no repeatable record of what happened.

Lossless network visibility and deep traffic inspection

Stitched-together tools create integration debt

Separate ticketing and SOAR vendors mean maintaining the webhook bridge between them, mapping mismatched schemas, debugging failures across two support contracts, and explaining to clients why a playbook result never made it onto the ticket.

Key Features

What the EagleEyes Platform does.

Two engines — ticketing and SOAR — wired together natively so that every alert becomes an enriched, triaged, and actioned ticket without analyst intervention.

  • Rust core: 50,000 tickets/min, zero drops, no GC pauses
  • Spec-driven connectors: any tool live in hours
  • AI triage on every ticket before analyst eyes land on it

50,000 tickets/min — Rust-powered, zero drop

Tested benchmark

Native SOAR with spec-driven connectors

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AI-powered automated triage

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Zero-code incident report generation

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Native multi-tenancy, standard

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HMAC-verified SOAR callbacks

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Hybrid SOAR execution model

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Playbook library with 1,000+ actions

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Structured audit trail on every ticket

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Phishing mailbox triage at scale

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How It Works

The full journey from alert to closed ticket.

An alert fires in your SIEM. By the time an analyst looks at it, EagleEyes has already enriched it, triaged it with AI, triggered an automated containment playbook, and posted the results back onto the ticket — all without a single keypress.

Security operations center receiving and processing SIEM alerts
Step 01SOC Engine

SIEM fires an alert → ticket created instantly

ElastAlert (Wazuh, OpenSearch, Elastic) sends a webhook to your tenant's inbound endpoint. The Rust engine creates a structured ticket in under a millisecond and acknowledges the source — no backpressure at 50k/min.

Contextual threat data enrichment and correlation visualization
Step 02SOC Engine

Automatic enrichment runs in parallel

VirusTotal IP reputation (multi-key rotation), geolocation for both source and destination IPs, MITRE ATT&CK technique and tactic mapping, and endpoint details — all attached to the ticket before any analyst opens it.

AI-powered alert triage and correlation engine
Step 03AI Service

AI triage fires async → verdict arrives via callback

The ticket data is sent to the AI analysis service (fire-and-forget). Minutes later, the AI posts its verdict back: Benign / Suspicious / Malicious, confidence score, threat level, key indicators, and recommended next step. The ticket updates automatically with a system comment.

Automated SOAR playbook trigger and orchestration workflow
Step 04SOAR Engine

SOAR auto-trigger rules evaluated → playbook fires

Per-tenant rules are checked — "severity Critical", "AI verdict Malicious >85% confidence", "VirusTotal detections >50". A matching rule fires the SOAR engine: the payload is assembled and sent to the playbook endpoint. The ticket records the execution as Pending.

Automated threat containment and response actions executing
Step 05SOAR Engine

Playbook executes — IP blocked, endpoint isolated, IOCs enriched

The SOAR runs the matched playbook: enriches indicators across VirusTotal, GreyNoise, AbuseIPDB; blocks the attacker IP on FortiGate / Cloudflare; isolates the host in CrowdStrike Falcon; or runs any other configured action sequence.

Verified callback updating ticket with full audit trail
Step 06SOC + SOAR

SOAR callback → ticket updated, audit trail complete

When the playbook finishes, it posts results to the ticket's callback endpoint. The HMAC-SHA256 signature is verified, then the ticket is updated with execution status, timestamps, actions taken, and a system comment summary — before any analyst has touched it.

Analyst reviewing a pre-enriched incident ticket in the dashboard
Step 07Analyst workflow

Analyst reviews a pre-contained, pre-documented incident

The analyst opens a ticket with AI verdict, full enrichment, and SOAR execution results already attached. They verify findings, set the verdict, and draft the incident report — no context gathering, no tool-switching, no copy-pasting.

Structured incident report delivered to client contacts
Step 08SOC Engine

Incident report approved and sent to client

The analyst drafts, a team lead approves, and EagleEyes emails the polished HTML report to the client's incident contacts. Daily and weekly summary digests go out automatically on schedule — no manual effort required.

Use Cases

Who uses EagleEyes Platform and how?

Use Case 01

MSSP running a full SOC for multiple clients from one deployment

An MSSP monitors 20+ client organisations from a single EagleEyes instance. Each client's tickets, users, SOAR configurations, and data are fully isolated by tenant. Platform admins can support across all clients when needed; each client's analysts only ever see their own environment. One deployment, zero cross-contamination, linear scale.

Use Case 02

Automated malicious-indicator response end-to-end

A SIEM alert fires on a suspicious IP. Before any analyst looks at it: VirusTotal verdict is attached, MITRE technique mapped, the AI returns "Malicious 91%", SOAR fires and blocks the IP at the firewall, endpoint is isolated in CrowdStrike. The analyst sees a pre-contained, fully documented ticket.

Use Case 03

Phishing mailbox triage at scale

Reported phishing emails are pulled from Gmail or Outlook, headers and links extracted, indicators enriched automatically. The SOAR playbook quarantines the message, blocks the sender, and opens a ticket with the full evidence trail attached — without any analyst touching a mail client.

Use Case 04

Structured incident reporting for regulated clients

Confirmed True Positives go through a formal Draft → Preview → Approve → Send pipeline. The client receives a full HTML report with timeline, IOCs, impact assessment, and remediation steps. Audit logs capture every action, approval, and send — a complete chain of custody for compliance.

Use Case 05

Custom automation for bespoke client environments

A client runs a stack with tools not yet in the connector catalogue. Using the no-code framework, the MSSP team describes the API once — the tool is live as a playbook action that afternoon, without any development work or vendor support ticket.

Why EagleEyes Platform

What sets us apart.

50k/min

The only SOC platform load-tested at 50,000 tickets per minute with zero drops

Most ticketing platforms degrade silently under alert spikes — queues back up, webhooks time out, and analysts don't know what they missed. EagleEyes is built in Rust on an async runtime with no garbage-collection pauses and no memory leaks. The 50k/min figure is a tested benchmark, not a theoretical ceiling.

Hybrid

No forced migration — new execution model alongside legacy Docker apps

Many SOAR platforms deprecate their older execution model when a new one ships, forcing a rewrite of every existing integration. EagleEyes SOAR is hybrid: the traditional Docker-based app model continues to work alongside the lightweight native runner.

No-code

Any tool live in hours, not a development sprint

Describe a tool's API — auth, actions, parameters — and it's a live playbook action. No engine code to write, no SDK to learn, no redeployment. Competitors require a Python app or a proprietary code module for every new integration.

Native

Isolation built into the foundation, not gated behind enterprise tier

Per-tenant MongoDB collection namespacing, JWT-scoped API access, and per-tenant SOAR configurations are standard across all plans. Competitors typically gate multi-tenancy behind expensive enterprise licences — EagleEyes makes it the default.

HMAC

Cryptographic verification on every SOAR callback — no spoofing

Every inbound SOAR result is validated with an HMAC-SHA256 signature before the ticket is updated. A spoofed or replayed callback is rejected at the perimeter. Credentials in the SOAR vault are AES-256-GCM encrypted at rest.

Market Comparison

EagleEyes SOAR vs. the market

Every column other than EagleEyes represents a real published limitation. Sources available on request.

CapabilityShuffleSplunk SOARTrend Micro XSOAREagleEyes SOAR
Add a new tool without writing code
App builder + code required
Python app per integration
Ecosystem-bound
Spec-driven, zero code
Ticketing + SOAR in one platform
SOAR only
Separate SKU
Separate product
Unified, natively wired
Native multi-tenancy (MSSP-grade)
Workspace-based
Enterprise tier
Limited
Full isolation, all plans
AI triage on every ticket
Not built-in
Add-on
Partial
Automatic, every ticket
Ingestion throughput (tested)
Not published
High
Not published
50,000 tickets/min, zero drop
Cryptographic SOAR callback verification
No
Partial
No
HMAC-SHA256 on every callback
Formal incident report pipeline
No
Manual
Basic
Draft → Preview → Approve → Send
Deployment complexity
Medium
High
High
Docker Compose, standard Linux host
Legacy Docker app compatibility
Yes
Own format
Deprecated
Hybrid — both models run together
★ denotes a capability unique to, or significantly stronger in, EagleEyes SOAR. Comparison based on publicly available product documentation. All claims available on request.
Getting Started

One deployment. Alerts flowing in days.

EagleEyes deploys as a set of containers in your own environment. There is no specialist infrastructure required — a standard Linux host is enough to go live.

Spin up a Linux host (or VM)

Any standard Linux host with Docker installed. 8 vCPUs and 16 GB RAM for a production starter node. A single docker-compose up starts all services.

Step 01

Point your SIEM at EagleEyes

Configure ElastAlert (or any webhook-compatible SIEM) to send alerts to your EagleEyes tenant endpoint. A single URL, a single secret. First ticket arrives in minutes.

Step 02

Create your first tenant and users

Log into the admin panel, create a client tenant, add analyst accounts, and set their role (analyst, senior analyst, admin, platform admin). All scoped to that tenant by default.

Step 03

Connect your tools via the SOAR catalogue

Browse the connector library. For tools already in the catalogue, one click and an API key. For anything custom, write a spec file — the tool is live as a playbook action the same day.

Step 04

Build or import a playbook

Use the visual playbook editor to chain actions: enrich → AI triage → block at firewall → isolate endpoint → notify Slack → update ticket. Import a starter playbook from the library and modify to fit.

Step 05

Go live — alerts flow, playbooks run

From first host to first contained ticket: typically under one working day for a standard deployment. Our implementation team is available for assisted onboarding for MSSPs bringing multiple tenants live at once.

Step 06
Specifications

System Requirements & Performance

Deployment prerequisites, sizing guidance, scalability characteristics, and benchmark figures for planning a production rollout.

Minimum Hardware Requirements

CPU8 vCPUs (x86-64)
Memory16 GB RAM
Storage — OS & containers50 GB SSD (root volume)
Storage — Ticket data & attachments500 GB+ (expandable; depends on retention policy)
Network1 Gbps NIC (10 Gbps recommended for high-volume deployments)

Ready to automate your SOC?

Book a live demo and we'll walk you through 50,000 tickets/min, end-to-end playbook execution, and multi-tenant architecture — all in one session.

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