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Set up Zeek to observe network traffic and produce structured logs for security analysis. Create custom detection scripts, investigate suspicious DNS activity and repeated external connections, and forward logs to a central security monitoring system.

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• Set up passive monitoring at key network points
• Create detection scripts for suspicious DNS and repeated connections
• Forward Zeek logs to a central security monitoring system

Analyze Zeek network logs to find lateral movement, when an intruder spreads between internal computers. Examine administrative file sharing, authentication across multiple hosts, and remote service operations to identify suspicious connections and reconstruct incident timelines.

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• Tracing spread to other computers after an initial compromise
• Investigating unauthorized transfers to administrative shares
• Finding one account authenticating to many internal hosts

Examine Zeek connection logs for regular callbacks that may indicate communication with an attacker’s control server. Use ZAT and Pandas to group connections, measure timing variation, and identify source and destination pairs for further investigation.

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• Hunting for periodic callbacks in Zeek connection logs
• Comparing connection timing across source and destination pairs
• Developing beaconing detection rules and hunting queries

Analyze Zeek DNS logs for possible data theft hidden in domain queries. The skill examines unusual character patterns, long labels, distinct subdomains, and query volume, then ranks suspicious domains and produces a JSON evidence report.

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• Investigating suspected DNS tunneling
• Finding possible data leaks hidden in DNS queries
• Ranking suspicious domains and identifying source IPs

Analyze Zeek and NetFlow records for ransomware-related activity, including regular callbacks to attacker infrastructure, TOR connections, and possible data exfiltration. Combine indicators into risk scores and structured reports with timelines to support threat hunting and incident investigation.

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• Hunting for active ransomware network activity
• Investigating possible data theft before encryption
• Checking periodic callbacks and TOR connections

Builds Zeek-based network hunting analytics by writing scripts and analyzing Zeek logs (conn, dns, http, ssl, files) to surface long connections, rare JA3s, suspicious downloads, and beaconing. Activates for requests to build Zeek analytics, write a Zeek hunting script, or analyze Zeek logs for threats.

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Investigate captured network traffic and connection records with Wireshark, Zeek, and NetFlow analysis. Identify communications with attacker infrastructure, trace movement between internal systems, estimate data transfers, and produce findings linked to packet evidence and timestamps.

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• Investigating suspicious periodic connections
• Measuring the volume and destination of data transfers
• Tracing attacker movement between internal systems

Develop network monitoring for signs that may precede ransomware encryption. Uses detection rules, linked log events, and threat intelligence to identify suspicious activity and define how alerts should be investigated, prioritized, and escalated.

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• Creating detection rules for activity before ransomware encryption
• Linking suspicious logins, scans, and file share access
• Investigating unusual internal network communications

Investigate attackers moving between internal systems by correlating login records with network traffic. Supports detection rules, suspicious SMB and RDP activity analysis, and reports showing attack timelines, affected hosts, and monitoring gaps.

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• Investigating attacker movement across internal systems
• Creating rules for suspicious authentication patterns
• Tracing affected hosts after a PsExec alert

Analyze DNS logs for signs of hidden command traffic and data theft. Use character randomness, query timing, TXT record inspection, and machine learning to identify suspicious domains and support security monitoring rules.

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• Investigating suspected DNS tunneling
• Classifying algorithmically generated domains
• Detecting periodic DNS beacon traffic

Performs statistical analysis of Zeek conn.log connection intervals to detect C2 beaconing patterns. Uses the ZAT library to load Zeek logs into Pandas DataFrames, calculates inter-arrival time standard deviation, and flags periodic connections with low jitter. Use when hunting for command-and-control callbacks in network data.

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Analyze Modbus industrial network traffic to identify unauthorized commands, write operations, and unusual polling intervals. Compare activity with normal traffic patterns and allowed operations, then report anomalies by type and severity.

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• Investigating suspicious Modbus traffic
• Establishing normal polling patterns
• Defining allowed Modbus function codes

Analyze DNS logs to find signs of hidden data transfers. Use query length, character randomness, traffic volume, and response sizes to identify suspicious domains and support monitoring rules with Python, Suricata, and Splunk examples.

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• Investigating possible data theft through DNS traffic
• Ranking suspicious domains found in DNS logs
• Creating DNS tunneling detection rules

Analyze malware network captures to investigate command-and-control traffic, data theft, and downloaded files. Use packet analysis tools to identify suspicious destinations and recurring connections, extract artifacts, and create detection rules from observed patterns.

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• Analyzing malware sandbox network captures
• Investigating command-and-control traffic
• Tracing data theft and file downloads

Deploys and configures Zeek (formerly Bro) network security monitor to passively analyze network traffic, generate structured logs, detect anomalous behavior, and create custom detection scripts for threat hunting and incident response.

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Detect lateral movement in network traffic using Zeek (formerly Bro) log analysis. Parses conn.log, smb_mapping.log, smb_files.log, dce_rpc.log, kerberos.log, and ntlm.log to identify SMB file transfers, NTLM account spray activity, remote service execution, and anomalous internal connections.

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Detect DNS-based data exfiltration by analyzing Zeek dns.log for high-entropy subdomains and anomalous query patterns

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Detect lateral movement in network traffic using Zeek (formerly Bro) log analysis. Parses conn.log, smb_mapping.log, smb_files.log, dce_rpc.log, kerberos.log, and ntlm.log to identify SMB file transfers, Pass-the-Hash activity, remote service execution, and anomalous internal connections.

中文简介正在准备中。当前显示原文说明。

Deploys and configures Zeek (formerly Bro) network security monitor to passively analyze network traffic, generate structured logs, detect anomalous behavior, and create custom detection scripts for threat hunting and incident response.

中文简介正在准备中。当前显示原文说明。

Detect DNS-based data exfiltration by analyzing Zeek dns.log for high-entropy subdomains and anomalous query patterns

中文简介正在准备中。当前显示原文说明。

Performs statistical analysis of Zeek conn.log connection intervals to detect C2 beaconing patterns. Uses the ZAT library to load Zeek logs into Pandas DataFrames, calculates inter-arrival time standard deviation, and flags periodic connections with low jitter. Use when hunting for command-and-control callbacks in network data.

中文简介正在准备中。当前显示原文说明。

Detect lateral movement in network traffic using Zeek (formerly Bro) log analysis. Parses conn.log, smb_mapping.log, smb_files.log, dce_rpc.log, kerberos.log, and ntlm.log to identify SMB file transfers, NTLM account spray activity, remote service execution, and anomalous internal connections.

中文简介正在准备中。当前显示原文说明。

Deploys and configures Zeek (formerly Bro) network security monitor to passively analyze network traffic, generate structured logs, detect anomalous behavior, and create custom detection scripts for threat hunting and incident response.

中文简介正在准备中。当前显示原文说明。

Detect DNS-based data exfiltration by analyzing Zeek dns.log for high-entropy subdomains and anomalous query patterns

中文简介正在准备中。当前显示原文说明。