T1592 Elastic Security · Elastic

Detect Gather Victim Host Information in Elastic Security

This detection identifies adversary attempts to enumerate victim host information during pre-compromise reconnaissance. Because T1592 is a PRE-ATT&CK technique occurring outside the victim network, direct detection is impossible — this rule targets second-order indicators visible from the defender side: automated scanning tools and fingerprinting bots making requests to internet-facing web servers, User-Agent rotation patterns consistent with OS/browser profiling, and rapid enumeration of host-revealing paths such as /robots.txt, /.env, /phpinfo.php, and similar disclosure endpoints. The primary data source is web server access logs (IIS W3C or common log format), which record client IP, User-Agent, and requested paths — the exact data an adversary harvests to profile target host configurations before launching phishing, supply chain, or watering hole operations.

MITRE ATT&CK

Tactic
Reconnaissance
Technique
T1592 Gather Victim Host Information
Canonical reference
https://attack.mitre.org/techniques/T1592/

Elastic Detection Query

Elastic Security (Elastic)
eql
// T1592 — Gather Victim Host Information
any where event.dataset : "iis.access"
  and url.path : ("/.env", "/.git/*", "/phpinfo.php", "/server-status", "/actuator/*")
  or user_agent.original : ("masscan*", "zgrab*", "shodan*", "nuclei*")
medium severity low confidence

Elastic EQL detection for Gather Victim Host Information (T1592). Translates the Microsoft Sentinel KQL logic to Elastic Common Schema (ECS) field mappings for use in Elastic SIEM. Targets the same behavioral indicators across process creation, network, and authentication event types.

Data Sources

Web Server LogsIIS Logs

Required Tables

logs-apache_http_server.*logs-iis.access-*

False Positives & Tuning

  • Legitimate SEO crawlers such as Googlebot, Bingbot, or commercial crawlers (Screaming Frog, Ahrefs, Semrush) may trigger on path enumeration rules — allowlist known crawler IP ranges and User-Agent prefixes
  • Internal vulnerability scanners (Nessus, Qualys, Rapid7) run by the security team against web assets will generate identical patterns — exclude known scanner IP ranges via watchlist
  • Developer tooling such as curl, wget, or Python requests used legitimately by CI/CD pipelines or deployment scripts may match scanner User-Agent patterns — baseline known build server IPs
Download portable Sigma rule (.yml)

Other platforms for T1592


Testing Methodology

Validate this detection against 3 adversary techniques from Atomic Red Team. Each test below lists the behaviour to exercise and the telemetry you should expect to see. Executable commands and cleanup steps are available with Pro.

  1. Test 1Web Server Fingerprinting via Automated Scanner User-Agent

    Expected signal: Web server access log entries (IIS W3C or Apache combined format) showing requests from the test host IP with User-Agents matching masscan, python-requests, Go-http-client, and curl patterns against multiple disclosure paths. ReconScore should trigger at >= 2 given multiple fingerprinting paths and multiple scanner User-Agents.

  2. Test 2OS-Targeted User-Agent Rotation for Victim Profiling

    Expected signal: Access log entries from test IP showing 5 distinct User-Agents representing Windows, Linux, macOS, Android, and iOS across the same path set within a short window. The User-Agent rotation hunting query should fire with UniqueOSHints = 5.

  3. Test 3Nmap Service and OS Version Detection Scan

    Expected signal: Network flow records showing TCP SYN packets to multiple ports from test host. Web server access logs showing nmap User-Agent requests (if HTTP ports scanned). IDS/IPS logs showing port scan detection. Network baseline anomaly for rapid sequential port connections.

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Response PlaybookInvestigation GuideHunting QueriesAtomic Red Team TestsTuning Guidance

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