Detect Employee Names in Splunk
Adversaries may gather employee names that can be used during targeting. Employee names can be used to derive email addresses as well as to help guide other reconnaissance efforts and craft more-believable lures. Adversaries may easily gather employee names since they may be readily available and exposed via online or other accessible data sets such as social media, LinkedIn, corporate websites, and press releases. Real-world threat actors including Kimsuky, Sandworm Team, and Silent Librarian have been observed collecting victim employee name information to support subsequent phishing campaigns, credential attacks, and social engineering operations. Detection is inherently challenging because this activity primarily occurs outside the victim's environment on public platforms. Effective detection pivots to monitoring organization-owned web properties for automated scraping, tracking OSINT tool execution on monitored endpoints, and identifying downstream artifacts such as systematic user enumeration via authentication systems.
MITRE ATT&CK
- Tactic
- Reconnaissance
- Technique
- T1589 Gather Victim Identity Information
- Sub-technique
- T1589.003 Employee Names
- Canonical reference
- https://attack.mitre.org/techniques/T1589/003/
SPL Detection Query
| multisearch
[ search index=proxy sourcetype=squid OR sourcetype="cisco:wsa:squid" OR sourcetype="bluecoat:proxysg:access:syslog" OR sourcetype="zscaler:proxy"
(url="*/team*" OR url="*/about-us*" OR url="*/about*" OR url="*/staff*" OR url="*/employees*"
OR url="*/directory*" OR url="*/people*" OR url="*/our-team*" OR url="*/leadership*"
OR url="*/management*" OR url="*/bios*" OR url="*/meet-the-team*" OR url="*/board*")
| eval branch="proxy_scraping"
| eval src=src_ip
| eval dest=site
| eval details=url ]
[ search index=wineventlog sourcetype="XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" EventCode=1
(CommandLine="*theHarvester*" OR CommandLine="*recon-ng*" OR CommandLine="*CrossLinked*"
OR CommandLine="*linkedin2username*" OR CommandLine="*phonebook.cz*" OR CommandLine="*spiderfoot*"
OR Image="*theHarvester*" OR Image="*crosslinked*")
| eval branch="endpoint_harvesting"
| eval src=host
| eval dest="local"
| eval details=CommandLine ]
| eval EventTime=_time
| stats
count as EventCount,
dc(details) as UniqueTargets,
earliest(_time) as FirstSeen,
latest(_time) as LastSeen,
values(details) as DetailsSample,
values(branch) as DetectionBranches
by src, dest
| eval WindowSeconds=LastSeen-FirstSeen
| eval RequestsPerMin=if(WindowSeconds>0, EventCount/(WindowSeconds/60), EventCount)
| eval ScrapeRisk=case(
match(DetectionBranches, "endpoint_harvesting"), "HIGH - known harvesting tool on managed endpoint",
RequestsPerMin > 15, "HIGH - rapid automated scraping rate",
EventCount > 60 AND UniqueTargets > 8, "MEDIUM - high volume directory enumeration",
EventCount > 30, "MEDIUM - elevated directory page access",
true(), "LOW"
)
| where ScrapeRisk!="LOW"
| eval FirstSeenReadable=strftime(FirstSeen, "%Y-%m-%d %H:%M:%S")
| eval LastSeenReadable=strftime(LastSeen, "%Y-%m-%d %H:%M:%S")
| table FirstSeenReadable, LastSeenReadable, src, dest, EventCount, UniqueTargets, RequestsPerMin, ScrapeRisk, DetectionBranches, DetailsSample
| sort - EventCountMulti-search detection combining proxy/web access logs and Sysmon endpoint telemetry to surface employee name harvesting activity. The proxy branch analyzes web access logs from common proxy sourcetypes (Squid, Cisco WSA, Blue Coat ProxyAVG, Zscaler) for high-rate access to known employee directory URL patterns from single source IPs. The endpoint branch searches Sysmon Event ID 1 (Process Create) for known OSINT and employee harvesting tools. Results are merged, aggregated per source, and scored based on request rate and volume. The multisearch approach allows detection even in environments where only one data source is available. Risk scoring provides tiered alerting from medium to high severity.
Data Sources
Required Sourcetypes
False Positives & Tuning
- Search engine crawlers (Googlebot, Bingbot, Semrush) legitimately indexing public corporate web pages at high rates
- SEO and web audit tools operated by the organization's marketing team performing scheduled crawls
- Authorized red team or penetration testers conducting OSINT reconnaissance — verify against active engagement schedule
- HR sourcing platforms with approved integrations scanning competitor or partner company directories
- Security researchers performing sanctioned threat intelligence work on organizational exposure
Other platforms for T1589.003
Testing Methodology
Validate this detection against 5 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.
- Test 1theHarvester Employee Name and Email Enumeration
Expected signal: Sysmon Event ID 1 (Linux auditd equivalent): process creation for 'theHarvester' or 'python3' with command line arguments '-d example.com -b google'. Sysmon Event ID 3 / auditd SYSCALL: outbound network connections to Google APIs and search endpoints. Sysmon Event ID 11: creation of /tmp/harvest_output.json. On Windows endpoints: DeviceProcessEvents with FileName=python.exe and ProcessCommandLine containing 'theHarvester' and '-b google'.
- Test 2CrossLinked LinkedIn Employee Name to Email Permutation
Expected signal: Sysmon Event ID 1: process create for python3 with CommandLine containing 'CrossLinked' or 'crosslinked' and '-f' and '{first}.{last}'. Sysmon Event ID 3: outbound DNS and TCP connections to linkedin.com and www.linkedin.com on port 443. Sysmon Event ID 11: file creation at /tmp/crosslinked_names.txt. DeviceProcessEvents (MDE): ProcessCommandLine containing 'crosslinked' or '{first}.{last}'.
- Test 3Corporate Team Page Automated Scraping Simulation
Expected signal: Sysmon Event ID 3 (Network Connect): repeated outbound connections to httpbin.org:443. Process creation for curl. In a real environment targeting a corporate web property: WAF/proxy logs showing 30+ requests to /team, /about-us, /staff URLs from the same source IP within 60 seconds with User-Agent 'Python-urllib/3.9'. CommonSecurityLog entries with RequestURL matching directory patterns.
- Test 4recon-ng LinkedIn Contacts Module Employee Enumeration
Expected signal: Sysmon Event ID 1: process create for recon-ng binary or python3 with recon-ng in command path. Sysmon Event ID 11: file creation in ~/.recon-ng/workspaces/employee_hunt/ including SQLite database data.db. Sysmon Event ID 3: outbound connections to linkedin.com, api.linkedin.com on port 443. DeviceProcessEvents: FileName containing 'recon-ng' or ProcessCommandLine containing 'recon-ng'.
- Test 5Hunter.io API Employee Name and Email Harvesting
Expected signal: Sysmon Event ID 3: outbound DNS query for api.hunter.io and TCP connection to api.hunter.io:443. Process creation for curl or python3 with api.hunter.io in command line arguments. In proxy/web access logs: GET requests to api.hunter.io/v2/domain-search with domain parameter. If monitoring DNS (Sysmon Event ID 22): DNS query for api.hunter.io.
References (10)
- https://attack.mitre.org/techniques/T1589/003/
- https://www.opm.gov/cybersecurity/cybersecurity-incidents/
- https://www.justice.gov/opa/pr/nine-iranians-charged-conducting-massive-cyber-theft-campaign-behalf-islamic-revolutionary
- https://www.cisa.gov/sites/default/files/publications/AA20-296A-Kimsuky_0.pdf
- https://github.com/laramies/theHarvester
- https://github.com/m8sec/CrossLinked
- https://github.com/lanmaster53/recon-ng
- https://docs.microsoft.com/en-us/azure/active-directory/reports-monitoring/reference-sign-ins-error-codes
- https://hunter.io/api-documentation/v2
- https://www.mandiant.com/resources/blog/apt29-domain-fronting-with-tor
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