Results for “network-traffic-analysis”

Detect C2 beaconing patterns in network traffic using frequency analysis, jitter detection, and domain reputation to identify compromised endpoints communicating with adversary infrastructure.

Analyzes network traffic captures and flow data to identify adversary activity during security incidents, including command-and-control communications, lateral movement, data exfiltration, and exploitation attempts.

Automates packet capture analysis using tshark and pyshark to extract protocol statistics, detect suspicious flows, identify IOCs, and analyze DNS anomalies from PCAP files.

Analyzes malware-generated network traffic from PCAP files to identify C2 protocols, data exfiltration, DNS tunneling, and beaconing patterns using Wireshark, Zeek, Suricata, and Python.

Identify command-and-control beaconing patterns in network traffic by applying statistical frequency analysis, jitter calculation, and coefficient of variation scoring to detect periodic callbacks from compromised endpoints.

Capture and analyze network traffic using Wireshark and tshark to reconstruct network events, extract artifacts, and identify malicious communications.

Analyze network packet captures (PCAP/PCAPNG) using Wireshark, tshark, tcpdump, and Python to reconstruct communications, extract files, and identify malicious traffic.

Internal network assessment. VLAN hopping, ARP spoofing detection, broadcast protocol abuse (LLMNR/NBT-NS/mDNS), network segmentation verification, SNMP enumeration, NFS exposure, router/switch audit, and internal service mapping. Assumes attacker has network access. Uses nmap, arp-scan, nbtscan, snmpwalk, onesixtyone, smbmap, nfs-common, masscan, hping3, and netexec.

Analyze network traffic, logs, and data flows to detect potential data exfiltration via DNS tunneling, cloud storage uploads, encrypted channels, and other indicators of compromise.

Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning, data exfiltration, and C2 beaconing patterns using the Python netflow library.

Hunt for unusual network connections by analyzing outbound traffic patterns, rare destinations, non-standard ports, and anomalous connection frequencies from endpoints.

Analyze Zeek conn.log and NetFlow data to detect ransomware network indicators including C2 beaconing, TOR exit node connections, data exfiltration, and suspicious DNS patterns.

Detects DNS-based data exfiltration, tunneling, and DGA communication by analyzing query logs with entropy analysis, volume anomalies, and subdomain length detection in SIEM platforms.

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

Simulates bandwidth throttling and network degradation attacks using tc, iperf3, and Scapy in authorized environments to test quality-of-service controls, application resilience, and network monitoring detection of traffic manipulation attacks.

Detect and analyze covert communication channels used by malware, including DNS tunneling, ICMP exfiltration, and protocol abuse for C2 and data exfiltration.

Detect data exfiltration through DNS tunneling by analyzing query entropy, subdomain length, query volume, TXT record abuse, and response payload sizes using passive DNS monitoring.

Identifies lateral movement techniques in enterprise networks by analyzing authentication logs, network flows, SMB traffic, and RDP sessions using Zeek, Velociraptor, and SIEM correlation rules to detect attackers moving between systems.

Analyze Zeek network logs to detect lateral movement techniques including SMB admin share access, DCE/RPC remote service creation, NTLM account spray, Kerberos anomalies, and large internal data transfers.

Detects DNS tunneling by computing Shannon entropy of DNS query names, analyzing query length distributions, inspecting TXT record payloads, and identifying high subdomain cardinality using scapy for packet capture analysis.

Detect domain fronting C2 traffic by analyzing SNI vs HTTP Host header mismatches in proxy logs and TLS certificate discrepancies using pyOpenSSL for certificate inspection.

Detect and prevent ARP spoofing attacks using ARPWatch, Dynamic ARP Inspection, Wireshark analysis, and custom Python monitoring scripts to protect against man-in-the-middle interception.

Detect network reconnaissance and port scanning using Suricata and Snort IDS signatures, threshold-based detection rules, and traffic anomaly analysis to identify Nmap, Masscan, and custom scanning activity.

Analyzes malware command-and-control (C2) communication protocols to understand beacon patterns, command structures, data encoding, and infrastructure for detection development and threat intelligence.

Analyzes mobile applications for malicious behavior through static analysis, runtime monitoring, and network traffic inspection to identify malware indicators.

Performs interactive dynamic malware analysis using the ANY.RUN cloud sandbox to observe real-time execution behavior, interact with malware prompts, and capture process trees, network traffic, and system changes.

Detect and respond to unauthorized cryptocurrency mining in AWS and Azure environments using cost anomalies, compute utilization, network traffic analysis, and runtime monitoring.

Detect DCOM-based lateral movement by correlating Sysmon process creation and network connection events, WMI event analysis, and RPC endpoint mapper traffic to identify abuse of MMC20.Application, ShellBrowserWindow, and ShellWindows COM objects.

Design and implement security zones and conduits for industrial automation and control systems per IEC 62443-3-2, including zone partitioning, firewall configuration, and validation through traffic analysis and penetration testing.