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THREAT-Recon-AutomatedVulnScannerSweep CrowdStrike LogScale · LogScale

Detect Automated Vulnerability Scanner Sweep Against External Attack Surface in CrowdStrike LogScale

Before exploitation, most intrusions begin with active scanning of the target's external attack surface using automated vulnerability scanning tools such as sqlmap, Nikto, Nuclei, Acunetix, Nessus, OpenVAS, or WPScan. Attackers run these tools against internet-facing web applications, APIs, and edge devices to fingerprint software versions, enumerate misconfigurations, and identify exploitable CVEs before committing to an intrusion attempt. This scanning is typically noisy at the HTTP layer: high-volume requests for known vulnerable paths (e.g. /.env, /.git/config, /wp-login.php, /actuator/health, /phpmyadmin), distinctive scanner user-agent strings, and rapid sequential probing of many distinct URIs from a single source in a short window. Nation-state actors such as Volt Typhoon and APT41 routinely scan edge devices and web infrastructure ahead of exploitation attempts, while eCrime groups like FIN7 and Scattered Spider use commodity scanning frameworks to identify soft targets at scale. Detecting the scanning phase gives defenders a window to harden or patch before the attacker moves to Initial Access.

MITRE ATT&CK

Tactic
Reconnaissance

LogScale Detection Query

CrowdStrike LogScale (LogScale)
cql
// Alert 1: Known vulnerability scanner signature (CrowdStrike Falcon LogScale / Next-Gen SIEM)
#event_simpleName = "HttpRequest"
| vendor = /(?i)(f5|imperva|fortiweb|akamai|cloudflare|netscaler)/i
| (httpUserAgent = /(?i)(sqlmap|nikto|nuclei|acunetix|nessus|openvas|wpscan|dirbuster|gobuster)/i OR uriPath = /(?i)(\.env|\.git\/config|wp-login\.php|actuator\/env|phpmyadmin|\.aws\/credentials)/i)
| eval ThreatType := "AutomatedVulnScannerSweep_KnownSignature"
| eval Severity := "MEDIUM"
| select([timestamp, sourceIP, destinationIP, uriPath, httpUserAgent, ThreatType, Severity])
| sort(timestamp, order=desc, limit=1000)

// Alert 2: Behavioral URI enumeration sweep
#event_simpleName = "HttpRequest"
| vendor = /(?i)(f5|imperva|fortiweb|akamai|cloudflare|netscaler)/i
| groupBy([sourceIP, destinationIP, bucket(field=@timestamp, span=5m)], function=[
    count(aid, as=TotalRequests),
    count(distinct=uriPath, as=DistinctURIs),
    count(where=[statusCode=404], as=NotFoundCount)
  ],
  limit=max, start=24h
)
| DistinctURIs >= 25 AND TotalRequests >= 30
| eval NotFoundRatio := NotFoundCount / TotalRequests
| NotFoundRatio >= 0.5
| eval ThreatType := "AutomatedVulnScannerSweep_BehavioralEnumeration"
| eval Severity := if(DistinctURIs >= 100, "HIGH", "MEDIUM")
| sort(DistinctURIs, order=desc, limit=1000)
medium severity medium confidence

Two-part CrowdStrike Falcon LogScale (Next-Gen SIEM) detection: known scanner user-agent/sensitive-path signature matching, plus a behavioral aggregation over 5-minute buckets flagging a source IP that enumerates 25+ distinct URIs with a majority-404 response ratio.

Data Sources

Third-party WAF/reverse-proxy syslog ingested via Falcon LogScale collectorF5 ASM, Imperva, FortiWeb, Akamai, Cloudflare, Citrix NetScaler via syslog forwarder

Required Tables

HttpRequest

False Positives & Tuning

  • Authorised vulnerability scanning tools operating from a known internal source IP not yet excluded
  • Synthetic monitoring or uptime-check services generating high request volume against health-check endpoints
  • Search engine crawlers or SEO audit tools generating a burst of 404s for stale links
  • Bug bounty or contracted penetration testing traffic

Other platforms for THREAT-Recon-AutomatedVulnScannerSweep


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 1Vulnerability Scanner User-Agent Simulation via curl

    Expected signal: WAF/reverse-proxy logs record inbound requests with the scanner user-agent strings in the Message or http_user_agent field.

  2. Test 2Sensitive Path Probing Simulation

    Expected signal: WAF/reverse-proxy logs show requests to each sensitive path, mostly resulting in 404 responses.

  3. Test 3Behavioral URI Enumeration Simulation via ffuf-style Loop

    Expected signal: WAF/reverse-proxy logs record 40 distinct URIs requested from the test source IP within a single 5-minute window, nearly all returning 404.

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