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Introduction
The hardest question in security remains deceptively simple: “Are we under attack right now?” Your security tools are doing their jobs, but attackers are simply moving between them—across identities, cloud, SaaS, and networks as one connected attack surface. As attacks accelerate at AI speed, attack gaps become harder to see and faster to exploit. At Black Hat USA 2026, Vectra AI unveiled how AI-1ative security and observability help defenders uncover hidden exposure, identify attacker behavior, and take action before impact.
Learning Objectives
- Identify and remediate the three critical detection gaps that attackers consistently exploit across hybrid environments, based on four years of leaked ransomware operator chats
- Master AI-1ative threat detection techniques for uncovering attacker behavior across network, identity, cloud, and SaaS attack surfaces
- Implement practical security hardening commands and configurations for Linux, Windows, and cloud environments to close attack paths and reduce exposure
You Should Know
1. Understanding the Three Detection Gaps
What do four years of leaked ransomware chats reveal? That attackers keep winning with the same playbook: valid credentials, trusted tools, and the gaps between your security controls. The three detection gaps that make this possible are:
Gap 1: Visibility Blind Spots — Attackers exploit unmonitored traffic between cloud, identity, and on-premises environments. Vectra AI addresses this by ingesting Zscaler traffic to detect hidden attacker behaviors across internet, private access, cloud, and IoT/OT.
Gap 2: Signal-to-1oise Failure — Traditional tools generate overwhelming alerts. Vectra AI runs scores of algorithms and AI models, including pre-trained models for detecting Command and Control (C2) communications.
Gap 3: Siloed Investigation — Attackers move across domains faster than security teams can correlate evidence. The Vectra AI Platform detects and correlates behaviors across cloud, network, and identity to stop threats before they spread.
Step-by-Step: Auditing Your Environment for Attack Gaps
Linux – Check for Unusual Network Connections:
List all active network connections with associated processes sudo netstat -tunap | grep ESTABLISHED Identify listening ports and services sudo ss -tuln Monitor real-time network traffic for anomalies sudo tcpdump -i any -1 -c 100
Windows – Investigate Active Sessions and Services:
List active network connections
netstat -ano | findstr ESTABLISHED
Identify processes associated with suspicious ports
Get-Process -Id (Get-1etTCPConnection -State Established).OwningProcess
Check for unusual scheduled tasks
Get-ScheduledTask | Where-Object {$_.State -1e "Disabled"}
2. AI-1ative Threat Detection in Action
Vectra AI’s Attack Signal Intelligence analyzes in real-time to show where you’re compromised right now. The platform continuously processes telemetry as it’s generated, correlates activity across domains, and prioritizes risk based on how fast and how far an attack is progressing.
For cloud environments, the platform provides accurate attack signal detection across AWS, Google Cloud Platform, IBM Cloud, Microsoft Azure, Microsoft 365, and Oracle Cloud. It protects cloud-1ative architectures, SaaS, and hybrid environments by detecting credential abuse, command-and-control activity, and lateral movement that often evade traditional defenses.
Step-by-Step: Cloud Security Hardening Commands
AWS – Detect and Respond to Suspicious Activity:
Enable CloudTrail for comprehensive API logging aws cloudtrail create-trail --1ame SecurityTrail --s3-bucket-1ame your-bucket Start logging aws cloudtrail start-logging --1ame SecurityTrail Query for suspicious API calls (e.g., unauthorized access attempts) aws cloudtrail lookup-events --lookup-attributes AttributeKey=EventName,AttributeValue=ConsoleLogin --max-results 50
Azure – Monitor Identity and Access:
Get Azure AD sign-in logs for unusual activity
Get-AzureADAuditSignInLogs -Filter "createdDateTime ge 2026-08-01" |
Where-Object {$_.Status.ErrorCode -1e 0}
Check for privileged role assignments
Get-AzureADDirectoryRole | ForEach-Object {
Get-AzureADDirectoryRoleMember -ObjectId $_.ObjectId
}
3. Ransomware Detection and Prevention
Vectra AI detects ransomware by identifying abnormal file access and modification patterns typical of ransomware behavior, capable of detecting crypto ransomware, locker ransomware, and hybrid variants. For M365 environments, behavioral analytics identify unusual file modifications that match ransomware activity, distinguishing them from normal user actions.
The platform has expanded command-and-control detection coverage across adversary tools and frameworks including Empire, Merlin, Caldera Sandcat, and interactive beaconing activity. It also provides improved coverage for credential acquisition and attack tool activity, including detection of Ncrack-based RDP activity and Responder NTLM behavior.
Step-by-Step: Ransomware Detection Commands
Linux – Monitor for Ransomware Indicators:
Monitor for mass file modifications (common ransomware behavior) sudo inotifywait -m -r --format '%w%f' /home/ 2>/dev/null | while read file; do echo "[$(date)] Modified: $file"; done Check for suspicious processes with high CPU/memory ps aux --sort=-%mem | head -20 Look for unusual file extensions (e.g., .encrypted, .locked) find / -1ame ".encrypted" -o -1ame ".locked" -o -1ame ".crypt" 2>/dev/null
Windows – Detect Ransomware Activity:
Monitor file system changes in critical directories
$watcher = New-Object System.IO.FileSystemWatcher
$watcher.Path = "C:\Users"
$watcher.IncludeSubdirectories = $true
$watcher.EnableRaisingEvents = $true
Check for shadow copy deletions (ransomware tactic)
vssadmin list shadows
Get-WmiObject -Class Win32_ShadowCopy | Format-Table
Identify recent large-scale file modifications
Get-ChildItem -Path C:\Users -Recurse -File |
Where-Object {$_.LastWriteTime -gt (Get-Date).AddHours(-1)} |
Group-Object Extension | Sort-Object Count -Descending
4. Attack Path Visualization and Remediation
Attack path analysis is critical for understanding how attackers move through your environment. Vectra AI supports AWS, Azure, and GCP clouds along with VMware, Hyper-V, Nutanix, and KVM hypervisors. The platform’s quadrant scoring prioritizes an attack’s level of urgency based on the number of techniques used and the attack’s progression.
Privileged Access Analytics (PAA) monitor the interactions between user accounts, services, and hosts, providing continuous visibility and assessment of privileges required to enforce zero trust.
Step-by-Step: Mapping and Hardening Attack Paths
Network Path Analysis:
Linux - Trace network paths to critical assets traceroute -1 192.168.1.100 Identify all listening services and their network exposure sudo netstat -tulpn | grep LISTEN Check firewall rules for overly permissive policies sudo iptables -L -1 -v
Windows – Audit Privileged Access:
List all users with administrative privileges
Get-LocalGroupMember -Group "Administrators"
Check for service accounts with excessive permissions
Get-WmiObject -Class Win32_Service | Where-Object {$_.StartName -1e "LocalSystem"}
Audit Active Directory for privileged accounts
Get-ADUser -Filter {Enabled -eq $true} -Properties MemberOf |
Where-Object {$_.MemberOf -match "Domain Admins|Enterprise Admins"}
5. Integrating AI Agents and Automated Response
The Vectra AI Platform connects to AI assistants through MCP (Model Context Protocol) servers, enabling intelligent analysis of threat detection data, security insights, and automated incident response workflows. Vectra AI Pro, launched at Black Hat USA 2026, gives AI agents in security operations centers more reliable data on attacker behavior.
The platform correlates network, identity, and cloud data to provide complete visibility and faster investigations without added complexity. When Vectra AI detects suspicious network behavior, it can automatically query endpoint telemetry, analyze process activity, and identify the most likely process that triggered the detection.
Step-by-Step: Configuring Automated Response
API Integration Example (cURL):
Authenticate to Vectra AI API
curl -X POST https://your-vectra-instance/api/v3/auth/login \
-H "Content-Type: application/json" \
-d '{"username":"your_user","password":"your_password"}'
Query for active detections
curl -X GET https://your-vectra-instance/api/v3/detections \
-H "Authorization: Bearer YOUR_TOKEN" \
-H "Content-Type: application/json"
Automated Response Script Snippet:
import requests
import json
Configuration
API_URL = "https://your-vectra-instance/api/v3"
API_KEY = "your_api_key"
def get_high_priority_detections():
headers = {"Authorization": f"Bearer {API_KEY}"}
response = requests.get(f"{API_URL}/detections", headers=headers)
detections = response.json()
Filter for high-priority detections
high_priority = [d for d in detections if d.get('severity') in ['Critical', 'High']]
return high_priority
def trigger_response(detection_id):
payload = {"action": "investigate", "detection_id": detection_id}
response = requests.post(f"{API_URL}/respond", json=payload)
return response.status_code
6. Hidden Tunnel and Protocol Coverage
Modern attackers use stealthy communication channels to evade detection. Vectra AI has expanded Hidden Tunnel detection to identify stealthy, non-beaconing Command & Control activity over previously uncovered protocols. LDAP reconnaissance detection has also been enhanced to better identify attacker attempts to enumerate privileged accounts, delegation settings, and trust relationships within Active Directory.
Step-by-Step: Detecting Hidden Tunnels
Linux – Monitor for DNS Tunneling:
Monitor DNS queries for unusually long subdomains
sudo tcpdump -i any -1 port 53 -v | grep -E "([a-zA-Z0-9]{20,})"
Check for ICMP tunneling (ping with large payloads)
sudo tcpdump -i any -1 icmp -v | grep -E "length [0-9]{4,}"
Detect outbound connections to suspicious ports
sudo netstat -tunap | grep ESTABLISHED | awk '{print $4,$5}' |
awk -F: '{print $NF}' | sort | uniq -c | sort -1r
Windows – Monitor for Covert Channels:
Monitor DNS cache for suspicious entries
ipconfig /displaydns | Select-String -Pattern "www|http|https" -Context 0,2
Check for unusual outbound connections
Get-1etTCPConnection -State Established |
Where-Object {$_.RemotePort -1otin @(80,443,53,123)} |
Format-Table LocalAddress, RemoteAddress, RemotePort
Monitor scheduled tasks for persistence mechanisms
Get-ScheduledTask | Where-Object {$<em>.Actions -like "powershell" -or $</em>.Actions -like "cmd"}
7. Security Observability and SOC Modernization
Modern security operations require continuous observability across the entire hybrid attack surface. Vectra AI structures its platform around three connected capabilities: coverage, clarity, and control across the entire modern network. The platform’s AI models can distinguish expected AI-driven activity from attacker-driven automation, often early in the attack lifecycle before access turns into impact.
Health notifications alert significant drops in observed IPs, traffic bandwidth, and packet volume that may impact detection coverage, providing earlier awareness of visibility gaps.
Step-by-Step: Implementing Security Observability
Log Aggregation and Analysis:
Linux - Set up centralized logging with rsyslog
sudo apt-get install rsyslog
sudo systemctl enable rsyslog
sudo systemctl start rsyslog
Forward logs to SIEM
echo ". @your-siem-server:514" | sudo tee -a /etc/rsyslog.conf
Analyze auth logs for suspicious patterns
sudo grep "Failed password" /var/log/auth.log | awk '{print $1,$2,$3,$9,$11}' | sort | uniq -c
Windows – Event Log Monitoring:
Enable advanced audit logging
auditpol /set /subcategory:"Logon" /success:enable /failure:enable
Query security logs for failed logons
Get-WinEvent -LogName Security -MaxEvents 100 |
Where-Object {$_.Id -eq 4625} |
Select-Object TimeCreated, Message
Monitor for privilege escalation events (4672)
Get-WinEvent -LogName Security -MaxEvents 50 |
Where-Object {$_.Id -eq 4672}
What Undercode Say:
- Attackers exploit gaps, not vulnerabilities. The core insight from four years of leaked ransomware chats is that attackers consistently leverage valid credentials and trusted tools to move between security controls. Closing detection gaps is more critical than patching individual CVEs.
-
AI-1ative security is no longer optional. As attacks accelerate at AI speed, defenders must leverage AI to distinguish signal from noise, correlate activity across domains, and respond at machine speed. Organizations that fail to adopt AI-1ative security will be outpaced by attackers using the same technology.
The Vectra AI Platform represents a fundamental shift from traditional perimeter-based security models to continuous, behavior-driven, machine-speed cyber resilience. By providing coverage, clarity, and control across network, identity, and cloud threat surfaces, it enables security teams to answer the critical questions: Where are you exposed right now? Who and what is operating across your environment? Is attacker behavior already unfolding?
The Black Hat USA 2026 showcase demonstrated that interactive attack gap experiences, real-world attack paths, and live platform demonstrations are essential for helping defenders understand their blind spots. As AI agents, machine identities, and AI-powered attacks continue to reshape the security landscape, organizations must prepare for the Autonomous Enterprise by safely adopting AI while preparing for the wave of cyber risk.
Prediction:
- +1 AI-1ative security platforms will become the de facto standard for enterprise SOCs within 24-36 months, displacing legacy SIEM and anomaly detection tools that cannot keep pace with AI-speed attacks.
-
+1 The integration of AI agents (MCP servers) with security platforms will automate 60-70% of tier-1 SOC investigation workflows by 2028, dramatically reducing mean time to detect and respond.
-
-1 Organizations that delay adopting AI-1ative security will experience a 40-50% increase in successful breach dwell time as attackers leverage AI to automate and accelerate their campaigns.
-
+1 Attack path visualization and privileged access analytics will become mandatory components of zero trust architectures, driven by regulatory requirements and insurance underwriting standards.
-
-1 The proliferation of AI agents and machine identities will create new attack surfaces that traditional security tools cannot protect, leading to a wave of AI-targeted attacks in 2027-2028.
-
+1 The three detection gaps identified by Vectra AI’s ransomware chat analysis will inform a new generation of security frameworks and compliance standards, similar to how the MITRE ATT&CK framework transformed threat detection.
-
-1 Security teams will face increasing pressure to “keep up” with AI-1ative tools, creating a skills gap that will drive demand for AI-augmented security analysts and automated response systems.
-
+1 By Black Hat 2027, AI-1ative security will shift from detection to prediction, enabling organizations to proactively close attack paths before attackers can exploit them.
For more information, visit Vectra AI at Booth 4534 at Black Hat USA 2026 or explore the platform documentation at docs.vectra.ai.
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