
Detecting Lateral Movement with Zeek
FreeIdentify lateral movement techniques in network traffic.
Free · Opens the source repo
What Detecting Lateral Movement with Zeek does
Detecting Lateral Movement with Zeek is a skill designed for cybersecurity professionals who need to analyze network traffic for signs of lateral movement within an organization. By utilizing Zeek's powerful log analysis capabilities, this skill focuses on parsing specific log files such as conn.log, smb_mapping.log, and dce_rpc.log to uncover activities indicative of potential security breaches. It identifies key lateral movement techniques including SMB file transfers, NTLM account spray activities, and unauthorized remote service executions.
This skill is particularly useful in post-compromise investigations, where it aids in hunting for lateral movement after an initial compromise is detected on a single endpoint. It enables security analysts to monitor SMB traffic for unauthorized access to administrative shares and detect anomalies in Kerberos ticket usage. By leveraging the data from Zeek logs, users can reconstruct timelines of suspicious activities, enhancing their ability to respond to incidents effectively.
To use this skill, organizations must have Zeek deployed in their network environment, along with the necessary analyzers enabled for SMB, DCE/RPC, and Kerberos protocols. The skill provides a series of scripts and commands to facilitate the identification of lateral movement patterns, making it easier for security teams to set up alerts and respond to potential threats. However, it is important to note that this skill should not be used as a standalone detection mechanism; it works best when combined with endpoint telemetry for comprehensive visibility into security incidents.
In summary, Detecting Lateral Movement with Zeek is an essential tool for cybersecurity professionals focused on network forensics, providing the means to detect and analyze lateral movement techniques effectively.
When to use it
Use this skill when investigating potential lateral movement after an initial compromise or when monitoring for suspicious internal network activity.
When not to use it
This skill is not suitable as a standalone detection tool; it should be used in conjunction with endpoint telemetry for full visibility.
What you can build with it
Post-Compromise Investigation
Use this skill to analyze network traffic after detecting an initial compromise, helping to identify lateral movement.
Monitoring SMB Traffic
Implement this skill to monitor SMB traffic for unauthorized file transfers to administrative shares.
Detecting Credential Spraying
Utilize this skill to analyze NTLM logs for signs of account spraying activities across the internal network.
How to install Detecting Lateral Movement with Zeek
View source1. Install with the skills CLI
npx skills add mukul975/anthropic-cybersecurity-skills/detecting-lateral-movement-with-zeek --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by mukul975Detecting Lateral Movement with Zeek
Analyze Zeek network logs to identify lateral movement techniques including SMB admin share access, DCE/RPC remote service creation, NTLM account spray, Kerberos ticket anomalies, and large internal data transfers indicative of staging or exfiltration between hosts.
When to Use
- Hunting for lateral movement after an initial compromise indicator is found on one endpoint
- Investigating suspected NTLM account spray or Pass-the-Ticket attacks across the internal network
- Monitoring SMB traffic for unauthorized file transfers to admin shares (C$, ADMIN$, IPC$)
- Detecting remote service execution via DCE/RPC (PsExec, schtasks, WMI lateral patterns)
- Building alerting rules for internal network anomalies in a Zeek-based NSMP deployment
- Performing post-incident timeline reconstruction using Zeek logs as a network-level evidence source
Do not use as a standalone detection mechanism. Zeek sees network traffic only; combine with endpoint telemetry (Sysmon, EDR) for full visibility. Encrypted SMB3 traffic may limit Zeek's visibility into file-level details.
Prerequisites
- Zeek 6.0+ deployed on a network tap or SPAN port monitoring internal VLAN traffic
- Zeek SMB analyzer enabled (loaded by default:
@load base/protocols/smb) - Zeek DCE/RPC analyzer enabled (
@load base/protocols/dce-rpc) - Zeek Kerberos analyzer enabled (
@load base/protocols/krb) - Python 3.8+ (standard library only)
- Access to Zeek log directory (default:
/opt/zeek/logs/current/) - Familiarity with Zeek TSV log format (fields separated by
\t, header lines prefixed with#)
Workflow
Step 1: Verify Zeek Log Collection
Confirm that Zeek is producing the required log files for lateral movement detection:
# Check that all required analyzers are producing logs
ls -la /opt/zeek/logs/current/conn.log
ls -la /opt/zeek/logs/current/smb_mapping.log
ls -la /opt/zeek/logs/current/smb_files.log
ls -la /opt/zeek/logs/current/dce_rpc.log
ls -la /opt/zeek/logs/current/kerberos.log
ls -la /opt/zeek/logs/current/ntlm.log
# Quick field check on conn.log
zeek-cut id.orig_h id.resp_h id.resp_p proto service < /opt/zeek/logs/current/conn.log | head -20
Step 2: Parse conn.log for Internal Lateral Patterns
Identify connections between internal hosts on lateral-movement-associated ports:
# Extract SMB connections (port 445) between internal hosts
zeek-cut ts id.orig_h id.orig_p id.resp_h id.resp_p proto service duration orig_bytes resp_bytes \
< /opt/zeek/logs/current/conn.log \
| awk '$5 == 445 && $7 == "smb"'
# Extract DCE/RPC connections (port 135)
zeek-cut ts id.orig_h id.resp_h id.resp_p service \
< /opt/zeek/logs/current/conn.log \
| awk '$4 == 135'
# Extract WinRM connections (port 5985/5986)
zeek-cut ts id.orig_h id.resp_h id.resp_p service \
< /opt/zeek/logs/current/conn.log \
| awk '$4 == 5985 || $4 == 5986'
Step 3: Analyze SMB Admin Share Access
Detect access to administrative shares (C$, ADMIN$, IPC$) which is the primary vector for tools like PsExec:
# Check smb_mapping.log for admin share access
zeek-cut ts id.orig_h id.resp_h path share_type \
< /opt/zeek/logs/current/smb_mapping.log \
| grep -iE '(C\$|ADMIN\$|IPC\$)'
# Check smb_files.log for file writes to admin shares
zeek-cut ts id.orig_h id.resp_h action path name size \
< /opt/zeek/logs/current/smb_files.log \
| grep -i 'SMB::FILE_WRITE'
Deploy the following Zeek script to generate notice.log alerts on admin share access:
@load base/protocols/smb
@load base/frameworks/notice
redef enum Notice::Type += {
Admin_Share_Access
};
event smb1_tree_connect_andx_request(c: connection, hdr: SMB1::Header, path: string, service: string) {
if ( /\$/ in path )
NOTICE([$note=Admin_Share_Access,
$msg=fmt("Admin share access: %s -> %s (%s)", c$id$orig_h, c$id$resp_h, path),
$conn=c]);
}
Step 4: Detect DCE/RPC Remote Service Operations
Monitor for remote service creation and scheduled task registration via DCE/RPC:
# Look for service control manager operations (PsExec pattern)
zeek-cut ts id.orig_h id.resp_h endpoint operation \
< /opt/zeek/logs/current/dce_rpc.log \
| grep -iE '(svcctl|atsvc|ITaskSchedulerService)'
Step 5: Detect NTLM Account Spray
Analyze ntlm.log for authentication anomalies indicating credential reuse. Zeek's ntlm.log does not expose password hashes, so this detection identifies a single account authenticating to many hosts in a short window — the network signature of credential spraying tools like CrackMapExec:
# Extract NTLM authentications
zeek-cut ts id.orig_h id.resp_h username domainname server_nb_computer_name success \
< /opt/zeek/logs/current/ntlm.log
# Failed NTLM authentications (brute force or credential testing)
zeek-cut ts id.orig_h id.resp_h username success \
< /opt/zeek/logs/current/ntlm.log \
| awk '$5 == "F"'
# Sort by timestamp for timeline analysis
zeek-cut ts id.orig_h id.resp_h username success \
< /opt/zeek/logs/current/ntlm.log \
| sort -k1,1
Deploy the following Zeek script to generate notice.log alerts when a single
account touches more hosts than the threshold in a rolling window:
@load base/protocols/ntlm
@load base/frameworks/notice
redef enum Notice::Type += {
NTLM_Account_Spray
};
global ntlm_tracker: table[string] of set[addr] &create_expire=5min;
const spray_threshold = 3 &redef;
event ntlm_log(rec: NTLM::Info) {
if ( ! rec?$username || rec$username == "-" )
return;
if ( rec$username !in ntlm_tracker )
ntlm_tracker[rec$username] = set();
add ntlm_tracker[rec$username][rec$id$resp_h];
if ( |ntlm_tracker[rec$username]| >= spray_threshold )
NOTICE([$note=NTLM_Account_Spray,
$msg=fmt("NTLM account spray: %s -> %d hosts", rec$username, |ntlm_tracker[rec$username]|),
$sub=rec$username,
$conn=rec$id]);
}
Step 6: Run the Automated Analysis Agent
Use the provided agent.py for comprehensive lateral movement detection:
python3 agent.py /opt/zeek/logs/current/
python3 agent.py /opt/zeek/logs/2026-03-18/ # Analyze a specific date
Verification
- Confirm conn.log captures internal SMB (port 445) and DCE/RPC (port 135) connections with correct field parsing
- Verify smb_mapping.log correctly logs admin share paths (C$, ADMIN$, IPC$)
- Test with a known PsExec execution in a lab: expect to see SMB FILE_WRITE of the service binary followed by DCE/RPC svcctl CreateService
- Validate NTLM log parsing by performing a test authentication and confirming username, domain, and success fields are captured; verify the NTLM Account Spray Zeek script generates a
notice.logentry when the spray threshold is exceeded - Cross-reference Zeek alerts with Sysmon Event ID 1 (Process Creation) on the target host to confirm end-to-end detection
- Verify the agent correctly handles both TSV and JSON Zeek log formats
Frequently asked questions about Detecting Lateral Movement with Zeek
Similar skills
Asset Criticality Scoring for Vulns
Prioritize vulnerabilities based on asset criticality.
Performing Alert Triage with Elastic SIEM
Streamline alert triage processes in Elastic Security.
Active Directory Vulnerability Assessment
Secure your Active Directory with comprehensive assessments.
Active Directory Investigation
Streamline your Active Directory compromise investigations.
Parsing Artifacts with Eric Zimmerman Tools
Efficiently parse Windows forensic artifacts for analysis.
Operationalizing MISP Threat Feeds
Enhance threat detection with curated MISP feeds.
