Blog

In the heat of a cyberattack, seconds matter. The question isn’t if you can detect a threat, it’s whether you can contain it before it spreads.

But for most organizations, manual containment is the bottleneck. Even with a mature security stack, teams often struggle with:

• Endless approval chains
• Console-switching chaos
• Manual validation
• And time… that they don’t have

The result? Containment delays that cause ransomware outbreaks, data leaks, and compliance nightmares.

Manual containment doesn’t scale. And attackers know it.

Why Traditional Containment Fails at Scale

The failure isn’t in detection, it’s in response. Let’s break down the root causes:

Human Bottlenecks

SOC analysts must review every alert. Even basic containment actions require approvals, slowing everything down.

Tool Fragmentation

EDR, IAM, SIEM, cloud, firewalls—none of them talk to each other natively. Analysts jump between consoles.

After-Hours Blind Spots

Most breaches escalate on weekends or late nights, when Tier 1 teams lack escalation authority.

Lack of Automation

Each incident becomes a custom response. No playbook, no scale, just firefighting.

No Contextual Prioritization

All assets are treated equally, even if one is a test server and another a payment database.

The Real Cost of Containment Delay

Industry data shows how dangerous delays really are:

• Average containment time: 4.2 hours
• Cost increase from delayed response: Over $1M (IBM 2024)
• Median attacker dwell time: 22 days (Mandiant)
• 67% of IR professionals say containment is their hardest operational challenge (SANS)

The business impact is real:

• Ransomware outbreaks
• Data exfiltration
• Downtime and reputational damage
• Compliance violations
• SOC analyst burnout

Real Incidents, Real Consequences

Healthcare Provider: IoT Malware

Alert triggered at 2:30 AM → no one acted until morning → malware spread to 17 devices

Government Agency: Account Takeover

Password spray succeeded → token remained active for 3 days → internal breach occurred

Manufacturer: Ransomware Attack

Endpoint alert ignored as “low risk” → 300+ systems encrypted → operations halted for 72 hours

What Scalable Containment Should Look Like

Modern threats require a modern containment model:

• Real-Time: Actions triggered the moment high-confidence threats are detected
• Intelligent: Risk scoring considers user identity, asset value, and threat pattern
• Repeatable: Response playbooks tailored to each attack type and asset group
• Human-AI Hybrid: Automation handles speed, analysts review high-impact decisions
• Compliant: Everything is logged, audit-ready, and defensible for regulations

Peris.ai’s Containment Model: Precision at Scale

Peris.ai Cybersecurity solves containment delays with an agentic AI + human analyst hybrid model, integrating detection, response, and validation in one unified platform.

BrahmaFusion Orchestration

• Automates triage and containment
• Includes AI-driven playbook builder
• Offers three modes: fully automatic, semi-automatic, or human-reviewed

Integrated Across the Stack

• EDR/NDR: Isolate devices, kill processes
• Cloud/IAM: Revoke tokens, disable accounts, block geo-based logins
• Network: Block ports, isolate subnets, change routes dynamically

Real-Time Threat Intelligence

• Validates IOCs and threat behavior
• Enriches detection data with live attacker profiles

Audit-Ready Tracking via IRP

• End-to-end incident lifecycle visibility
• Logged actions for compliance and reporting

Want AI-driven containment without losing human control? Explore BrahmaFusion

Why the Hybrid SOC Model Works

Speed

• AI Does Best: Acts in milliseconds
• Analysts Do Best: Validates complex edge cases

Volume

• AI Does Best: Processes 10K+ alerts/day
• Analysts Do Best: Focuses on high-value signals

Consistency

• AI Does Best: Executes playbooks 24/7
• Analysts Do Best: Refines logic, adjusts for nuance

Recall

• AI Does Best: Tracks historical threats and patterns
• Analysts Do Best: Maps to business context and risk

Automation handles volume and urgency. Humans ensure precision and strategy.

If This Sounds Familiar, It’s Time to Evolve

• “Who has access to isolate that host?”
• “We need to log into three platforms to kill that session…”
• “We’ll escalate this to IR tomorrow.”

You don’t need more consoles. You need coordinated action at speed.

The Future of Containment Now With Peris.ai

Containment Delay

• Without Peris.ai: Manual, hours of lag
• With Peris.ai: AI containment in < 3 minutes

Tool Overload

• Without Peris.ai: Disconnected workflows
• With Peris.ai: Centralized orchestration

Analyst Overload

• Without Peris.ai: Alert fatigue
• With Peris.ai: AI handles L1, analysts own strategy

Inconsistency

• Without Peris.ai: Ad hoc response
• With Peris.ai: Playbook-driven, repeatable workflows

Compliance Risk

• Without Peris.ai: Poor tracking or audit logs
• With Peris.ai: Logged, traceable, audit-ready

Conclusion: Stop Letting Threats Spread While You Wait

Containment is no longer a human-only task. It’s a race and automation is your only chance to win.

With Peris.ai, your analysts don’t get replaced, they get equipped.

• Agentic AI handles the speed
• Human analysts bring the strategy
• The platform ensures it all works together

Stop letting threats spread, See how Peris.ai enables fast, compliant containment

Every modern enterprise operates in a complex digital environment—hybrid cloud deployments, SaaS sprawl, remote endpoints, mobile access, and third-party integrations. But amid this expansion lies a critical and often ignored truth:

You can’t defend what you can’t see.

While endpoint security and firewalls are well-established, network blindspots remain one of the top enablers of successful breaches. Hidden communications, unmanaged assets, lateral movements, and command-and-control (C2) traffic often go unnoticed, giving attackers the stealth they need to persist, escalate, and exfiltrate.

This article explores:

• What causes network blindspots
• Why they persist even in tool-rich environments
• The impact on detection, response, and compliance
• And how Peris.ai’s Incident Response Platform (IRP), paired with NVM, EDR, Brahma Fusion, INDRA, and BimaRed, delivers 360° visibility and response coordination—without drowning your team in alerts or dashboards.

What Are Network Blindspots?

A network blindspot is any portion of the infrastructure where:

• No traffic is being logged
• No behavior is being analyzed
• No alerts are generated—even if malicious activity occurs

These blindspots are dangerous because:

• They allow lateral movement to go undetected
• Attackers can bypass perimeter defenses and hide
• Incident responders lack visibility into the scope and impact of a compromise

Common Causes of Network Blindspots

Legacy Infrastructure

Older switches, routers, and OT/ICS systems often don’t support modern telemetry, logging, or integrations with SIEM/XDR platforms.

Cloud Silos

Many organizations run AWS, Azure, and Google Cloud workloads—each with its own telemetry and security stack, leading to:

• Fragmented visibility
• Inconsistent monitoring policies
• Missed east-west cloud traffic

Remote and BYOD Devices

Endpoints connecting via VPNs or split tunneling may bypass internal monitoring tools altogether. If EDR is not deployed (or disabled), you lose the visibility chain.

Encrypted Traffic (TLS/SSL)

Today, over 90% of internet traffic is encrypted. Without decryption strategies or behavioral monitoring, threats hidden in SSL can pass undetected.

Shadow IT and Rogue Devices

Unmanaged devices, unauthorized SaaS tools, and rogue access points introduce blindspots that:

• Don’t generate logs
• Aren’t tracked by asset inventories
• Aren’t subject to policies or detection rules

Consequences of Blindspots

Missed Detections

Without full visibility, anomalies like:

• Credential reuse
• Data exfiltration
• Internal scans
• Suspicious DNS tunneling

…can go unnoticed until a breach is confirmed—often by a third party.

Delayed Incident Response

Without knowing where an attacker has moved:

• Containment is incomplete
• Root cause analysis is flawed
• Post-breach recovery takes weeks instead of hours

Broken Compliance and Auditing

Frameworks like ISO 27001, NIST, HIPAA, and PCI-DSS require:

• Logging of access and traffic
• Timely detection of anomalies
• Demonstrable coverage of sensitive assets

You cannot prove control over what you cannot see.

Why Traditional Security Tools Fall Short

Tool Sprawl

Security teams often juggle:

• SIEMs
• Firewalls
• EDR platforms
• NetFlow/PCAP tools
• Cloud security tools

But these tools:

• Operate in silos
• Don’t share data contextually
• Require manual correlation
• Generate overwhelming false positives

Alert Fatigue and Skill Shortages

SOC analysts are overwhelmed. Without automated correlation and contextual intelligence, teams:

• Miss real threats
• Waste time investigating dead ends
• Burn out and churn

This is where a unified, intelligent platform becomes essential—not more dashboards, but one brain connecting them all.

Enter Peris.ai IRP: Unified, Intelligent Incident Response

The Peris.ai Incident Response Platform (IRP) isn’t just another SIEM or SOAR tool—it’s a centralized operating system for modern cybersecurity operations, designed to:

• Eliminate network and endpoint blindspots
• Coordinate data from multiple sources (NVM, EDR, threat intel)
• Trigger real-time triage, investigation, containment, and remediation
• Reduce MTTD and MTTR
• Empower SOC teams with intelligent automation—not more noise

Key Features:

• End-to-end visibility across endpoints and networks
• Case management and ticketing workflows built-in
• Integrated AI-powered triage with Brahma Fusion
• Threat Intelligence integration via INDRA
• Attack Surface mapping via BimaRed
• Customizable playbooks for response orchestration
• One-click containment across cloud, endpoint, and network

How Peris.ai IRP Works to Eliminate Blindspots

Data Ingestion & Normalization

IRP ingests logs and telemetry from:

• NVM (Network Visibility & Monitoring)
• EDR (Endpoint Detection & Response)
• SIEM
• Firewall/IDS/IPS
• Cloud environments (via APIs)

All data is normalized into a common schema for easy correlation.

AI-Powered Triage via Brahma Fusion

Brahma Fusion uses Agentic AI to:

• Analyze data in real-time
• Identify suspicious patterns (e.g., beaconing, lateral movement, anomalous ports)
• Trigger investigation playbooks
• Automatically escalate cases based on threat context

Analysts are no longer bottlenecks—AI performs Level 1 and Level 2 triage, reducing alert noise by up to 44%.

Threat Intelligence Integration via INDRA

Every alert and anomaly is enriched with:

• MITRE ATT&CK TTP mapping
• Known threat actor behavior
• CVE exploitability data
• Campaign context
• EPSS and trending threats

This helps security teams focus on what attackers are doing now, not just hypothetical risks.

Asset and Exposure Correlation via BimaRed

Blindspots often exist because organizations don’t know what’s exposed.

BimaRed maps:

• All external-facing assets
• Open ports, services, and vulnerabilities
• Unsecured APIs or admin panels

IRP correlates alerts with these findings to highlight real attack vectors.

Case Management, Containment, and Reporting

Once a threat is confirmed:

• IRP opens a case
• Assigns response owners
• Logs all actions and notes
• Executes remediation playbooks (via Brahma Fusion)
• Sends alerts to stakeholders
• Prepares compliance-ready reports

Everything is documented—audit trails, response timelines, and evidence are built-in.

7. Real-World Example: Ransomware in a Mid-Sized Financial Company

Situation: Unusual SMB traffic was detected from a workstation.

Without IRP:

• SIEM flagged anomaly, but lacked context
• No immediate correlation with other traffic
• Endpoint logs not available due to VPN routing
• 4 days later, ransomware was deployed

With IRP:

• NVM detects abnormal lateral SMB traffic
• Brahma Fusion auto-tags the event as potential lateral movement
• INDRA confirms this behavior aligns with active TA505 ransomware group
• Case is opened, endpoint isolated, and remediation triggered
• Incident closed within 1.5 hours

⏱ Result: 90% reduction in detection-to-containment time

Benefits for Key Stakeholders

CISOs

• Unified view of security posture
• Real-time risk visibility
• Reporting aligned to compliance frameworks
• Reduced breach risk and regulatory exposure

SOC Managers

• Triage automation
• Integrated toolsets
• Reduced analyst burnout
• Operational consistency

IT Teams

• Visibility into unmanaged assets
• Faster root cause analysis
• Integration into existing ticketing systems

9. How Peris.ai IRP Is Different from SIEM and SOAR

Ingest logs

• SIEM: ✅
• SOAR: ✅
• Peris.ai IRP: ✅

Orchestrate workflows

• SIEM: ❌
• SOAR: ✅
• Peris.ai IRP: ✅

Threat intel correlation

• SIEM: ❌
• SOAR: ❌
• Peris.ai IRP: ✅ (via INDRA)

Attack surface visibility

• SIEM: ❌
• SOAR: ❌
• Peris.ai IRP: ✅ (via BimaRed)

Endpoint + network integration

• SIEM: Partial
• SOAR: Partial
• Peris.ai IRP: ✅

AI-assisted triage

• SIEM: ❌
• SOAR: ❌
• Peris.ai IRP: ✅ (via Brahma Fusion)

Full incident lifecycle

• SIEM: ❌
• SOAR: Partial
• Peris.ai IRP: ✅

IRP is not a patchwork—it’s a connected ecosystem.

10. Steps to Start Closing Your Network Blindspots Today

1. Conduct a Blindspot Audit

• What assets lack monitoring?
• Are there network zones with no packet inspection?
• Are cloud environments being logged comprehensively?

2. Integrate Network and Endpoint Telemetry

• Break silos between EDR, NDR, and SIEM
• Normalize and centralize log data

3. Enrich Alerts with Threat Context

• Incorporate external threat intel
• Map detections to MITRE ATT&CK

4. Automate Triage and Case Management

• Use playbooks for common threats (e.g. brute force, DNS tunneling)
• Assign ownership dynamically

5. Document and Report

• Build defensible logs of every detection, decision, and action
• Maintain audit-readiness

Conclusion: Don’t Just Monitor—Understand, Correlate, Act

Security operations are no longer about chasing every log line—they’re about connecting signals to meaning, and acting fast.

Network blindspots are not a tool problem—they’re a strategy problem. Too many organizations have invested in siloed tools without building the connective tissue to see threats in real time.

Peris.ai IRP solves this not by adding another dashboard, but by becoming the central command layer across your environment.

You get:

• Real-time visibility
• Integrated response
• Context-rich decision-making
• Full lifecycle management

All with intelligent automation designed to amplify your human team—not replace it.

Are hidden threats moving through your network unseen? Take the first step toward 360° security visibility at https://peris.ai

#YouBuild #WeGuard

In today’s hybrid work environments, security teams must defend thousands—sometimes millions—of devices across corporate offices, remote locations, employee homes, cloud environments, and unmanaged personal devices. This sprawl has introduced a critical vulnerability: endpoint visibility gaps.

These are the blind spots where attackers hide, dwell, and move freely—undetected and unchallenged.

Despite heavy investment in SIEM, firewalls, and anti-malware, endpoint visibility remains the Achilles’ heel of modern cybersecurity. Without complete awareness of device behavior and security posture, detection falters, response slows, and compliance risks grow.

What Are Endpoint Visibility Gaps?

A visibility gap occurs when the security operations center (SOC) lacks awareness of a device’s status, activity, or presence on the network. These include:

• Devices not protected by endpoint detection and response (EDR) tools
• Shadow IT or bring-your-own-device (BYOD) endpoints
• Legacy assets missing endpoint agents
• Remote or offline machines operating outside internal networks
• IoT and OT devices lacking telemetry capabilities
• Systems misconfigured to bypass logging

Why These Gaps Exist:

• Inconsistent EDR agent deployment and coverage
• Poor asset inventory management
• Lax BYOD policies with no unified monitoring
• Cloud workload sprawl
• Fragmented data pipelines between EDR, SIEM, and NDR tools

Outcome: Your security team may think the environment is secure—but attackers know exactly where visibility fails.

Key Pain Points: What Visibility Gaps Break

Threat Detection Fails Without Endpoint Context

You might detect a suspicious login in the SIEM—but without EDR telemetry, you won’t know:

• If malware executed post-login
• What data the attacker accessed
• Whether privilege escalation occurred
• If the device is beaconing to an external command-and-control server

Without telemetry, detection is incomplete.

Lateral Movement Goes Undetected

Attackers exploit blind spots to pivot undetected between systems. Visibility gaps mean:

• No detection of host-to-host movement
• No tracing of credential dumping or process injection
• No historical timeline of attacker actions

“If your security map is incomplete, attackers will use the gaps to draw their own.”

BYOD and Remote Work Expand Your Attack Surface

Hybrid work is now standard—but endpoint security policies often stop at the corporate edge.

Without coverage of employee-owned or contractor devices, organizations face:

• Patch gaps
• Lack of telemetry on sensitive systems
• Inability to enforce application or data controls
• Exposure from unmanaged cloud collaboration apps

In 2025, if it’s connected, it must be protected.

Compliance and Audit Exposure

Frameworks like ISO 27001, NIST CSF, GDPR, and HIPAA all require:

• Centralized asset tracking
• Evidence of endpoint protection
• Proven response capabilities

Without proof of monitoring and protection across endpoints, you risk non-compliance—and fines.

Slower Incident Response and Forensics

You can’t contain what you can’t trace. Incomplete endpoint data leads to:

• Delayed containment actions
• Inaccurate root cause analysis
• Incomplete eradication of threats
• Missed indicators of compromise (IOCs)

Forensics depends on endpoint data. Period.

Why Traditional Solutions Fall Short

Legacy antivirus and standalone EDRs no longer meet today’s visibility demands.

Challenge: Coverage inconsistency

• Traditional EDR Response: Agents misconfigured or uninstalled
• Risk: Unknown devices remain invisible

Challenge: No offline telemetry

• Traditional EDR Response: No visibility when devices go offline
• Risk: Attackers dwell unnoticed

Challenge: Signature limitations

• Traditional EDR Response: Misses fileless and behavior-based threats
• Risk: Zero-days and insiders bypass detection

Challenge: Alert overload

• Traditional EDR Response: No correlation across tools
• Risk: False positives waste analyst time

Challenge: Siloed data

• Traditional EDR Response: No integration with SIEM/NDR
• Risk: Context is missing during triage

What Comprehensive Endpoint Visibility Looks Like

The modern enterprise must adopt visibility standards that support:

• Unified asset inventory across all device types
• Real-time telemetry from kernel to application layer
• Behavioral analytics, not just signature matching
• Cross-domain correlation between endpoints and network
• Threat context (e.g., mapping to MITRE ATT&CK, actor behaviors)

This is the new baseline for resilience.

How Peris.ai Closes the Endpoint Visibility Gap

Peris.ai EDR

Peris.ai’s endpoint detection and response platform provides:

• Continuous behavioral telemetry (file, process, registry, network)
• Real-time endpoint inventory sync with SIEM
• Active response tools (kill process, isolate host, lock accounts)
• OS-agnostic support (Windows, Linux, macOS)
• Cloud-native console for remote visibility
• Threat correlation with INDRA CTI

Peris.ai NVM (Network Visibility & Monitoring)

Works alongside EDR to deliver:

• Network-based behavioral detection (East-West and North-South)
• Visibility into unmanaged devices (BYOD, IoT, OT)
• AI-driven anomaly detection on network flows
• Integration with EDR to map attacker behavior end-to-end
• Protocol-aware analysis (DNS, HTTP, SMB, LDAP)

Together, EDR + NVM give you endpoint-to-network visibility, with deep context and automation.

Before vs. After: Visibility in Action

Metric: Endpoint visibility coverage

• Before Peris.ai: ~78%
• After Peris.ai: 99.9% (including BYOD, remote, cloud)

Metric: MTTD for endpoint-based attacks

• Before Peris.ai: >24 hours
• After Peris.ai: <15 minutes

Metric: BYOD/IoT detection rate

• Before Peris.ai: Partial
• After Peris.ai: Complete (via NVM)

Metric: Lateral movement dwell time

• Before Peris.ai: 3–5 days
• After Peris.ai: <6 hours

Metric: Time to RCA after alert

• Before Peris.ai: 2–5 days
• After Peris.ai: Same day (automated evidence correlation)

Recommendations to Improve Endpoint Visibility

1. Audit existing EDR deployment across all device classes
2. Unify telemetry between endpoint and network platforms
3. Expand to unmanaged endpoints using agentless or network detection
4. Tag assets and owners in your inventory for accountability
5. Enrich detection with threat context (e.g., INDRA or similar CTI)
6. Automate response workflows (via Brahma Fusion or other SOAR tools)
7. Benchmark and improve using KPIs: MTTD, endpoint coverage, false positives, RCA time

Conclusion: Visibility Is Resilience

In the age of distributed work and AI-powered attacks, your biggest risk isn’t the malware you haven’t seen—it’s the endpoint you didn’t know existed.

Visibility isn’t optional. It’s foundational.

Organizations that unify endpoint and network telemetry, contextualize alerts, and automate response don’t just detect threats faster—they reduce business risk, meet compliance standards, and empower their teams to operate proactively.

Explore how Peris.ai EDR and NVM can illuminate your infrastructure—and eliminate your blind spots: https://peris.ai