Listen to this Post
Endpoint Detection and Response (EDR) solutions have revolutionized enterprise security by providing extensive pre-built detections. Deploying an EDR agent across endpoints significantly improves detection capabilities, often surpassing what internal security teams can achieve manually. However, certain legitimate tools—such as Remote Access Trojans (RATs) and Remote Monitoring and Management (RMM) software—are frequently abused by attackers (MITRE ATT&CK T1219) but rarely flagged due to their valid use cases.
A compound detection approach combining behavioral analytics and statistical indicators can identify malicious activity without relying on static signatures. For example, tracking low-prevalence or anomalous behavior (e.g., new RAT tools in the network) provides defenders with an early advantage.
Key Takeaways:
✔ Prioritize Detection Backlog: EDR vendors will eventually cover common threats, but custom detections are critical for business-specific risks.
✔ Leverage Advanced Telemetry: Tools like Microsoft Defender XDR (MDE) offer rich endpoint data—use it to fill detection gaps.
✔ Master Security Analytics: Statistical baselines and query languages (e.g., KQL) are essential for identifying zero/low-prevalence threats.
You Should Know:
1. Behavioral Detection with EDR
Modern EDRs like CrowdStrike, SentinelOne, and Microsoft Defender use behavioral analysis to detect malicious activity. Example commands to investigate endpoints:
Linux (Auditd & EDR Commands)
Monitor process execution auditctl -a exit,always -F arch=b64 -S execve Check suspicious child processes ps aux --forest | grep -i "sh|curl|wget|python" Investigate network connections netstat -tulnp | grep ESTABLISHED
Windows (PowerShell & Defender)
List processes with network activity
Get-NetTCPConnection | Select-Object LocalAddress, RemoteAddress, State, OwningProcess | ft
Check Defender detection history
Get-MpThreatDetection | Where-Object { $_.InitialDetectionTime -gt (Get-Date).AddDays(-1) }
Hunt for RMM/RAT artifacts
Get-WmiObject -Query "SELECT FROM Win32_Process WHERE CommandLine LIKE '%teamviewer%'"
2. Building Custom Detections
Use SIEM queries (e.g., Microsoft Sentinel KQL) to track anomalies:
SecurityEvent | where EventID == 4688 // Process creation | where CommandLine contains "powershell -nop -enc" | summarize Count=count() by Computer, CommandLine | where Count > 3 // Baseline threshold
3. Threat Hunting with Baselines
Establish baselines for normal activity to spot deviations:
Linux: Check cron jobs against baseline crontab -l > current_cron.txt diff baseline_cron.txt current_cron.txt Windows: Compare autoruns autorunsc.exe -accepteula > current_autoruns.csv Compare-Object (Import-Csv baseline_autoruns.csv) (Import-Csv current_autoruns.csv)
What Undercode Say
EDR solutions are powerful, but their out-of-the-box detections must be supplemented with custom analytics. Focus on:
– Behavioral anomalies (e.g., unusual process trees, rare command-line arguments).
– Statistical outliers (e.g., spikes in rare RMM tool usage).
– Continuous baselining (UEBA for endpoints).
Leverage tools like Sysmon, Osquery, and Elastic Agent for deeper visibility. For Defender XDR users, explore Advanced Hunting with KQL.
Expected Output:
- Alerts on suspicious RAT/RMM usage.
- Custom detection rules for business-critical apps.
- Improved threat hunting with ephemeral baselines.
Further Reading:
- Baselines 101: Building Resilient SIEM Detections
- Threat Hunting: Collecting Web Shells with Baselines
References:
Reported By: Inode Edr – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
