Results for “network-scanning”

Configures Fail2ban with custom filters and actions to detect port scanning, SSH brute force, and network reconnaissance, automatically banning offending IPs and alerting security teams.

Conduct a comprehensive external network penetration test to identify vulnerabilities in internet-facing infrastructure using PTES methodology, reconnaissance, scanning, exploitation, and reporting.

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.

Configure and execute agentless vulnerability scanning using network protocols, cloud snapshot analysis, and API-based discovery to assess systems without installing endpoint agents.

Import object detection models from HuggingFace or NVIDIA NGC into a DeepStream pipeline with automated ONNX download, TensorRT engine build, custom parser, multi-stream benchmark, and PDF report generation.

Craft, send, sniff, and dissect network packets using Scapy for protocol analysis, network reconnaissance, and traffic anomaly detection in authorized security testing.

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

Conduct authenticated and unauthenticated vulnerability scans using Tenable Nessus to identify known vulnerabilities, misconfigurations, and missing patches, with prioritized remediation guidance.

Computer vision engineering skill for object detection, image segmentation, and visual AI systems. Covers CNN and Vision Transformer architectures, YOLO/Faster R-CNN/DETR detection, Mask R-CNN/SAM segmentation, and production deployment with ONNX/TensorRT. Includes PyTorch, torchvision, Ultralytics, Detectron2, and MMDetection frameworks. Use when building detection pipelines, training custom models, optimizing inference, or deploying vision systems.

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.

Captures and analyzes network packet data using Wireshark and tshark to identify malicious traffic patterns, diagnose protocol issues, extract artifacts, and support incident response investigations on authorized network segments.

Conducts comprehensive network penetration tests against authorized target environments using host discovery, port scanning, service enumeration, vulnerability identification, and controlled exploitation following PTES methodology.

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

Configures and troubleshoots network infrastructure: DNS records, reverse proxies, SSL certificates, firewalls, CDNs, and load balancers.

嵌入式网络调试工具，用于发现接口、抓包、分析 pcap/pcapng、做连通性测试、端口扫描和流量统计。 当用户提到 Wireshark、tshark、Npcap、抓包、网络联调、端口扫描、连通性排查、pcap 分析、 网络接口、ping 测试、traceroute、流量统计、Modbus TCP、EtherNet/IP 等网络协议调试时自动触发， 也兼容 /net 显式调用。即使用户只是说"抓个包看看"、"扫一下端口"、"网络通不通"或"分析一下这个 pcap"， 只要上下文中出现具体工具名（tshark、Wireshark、Npcap）、协议名（Modbus TCP、EtherNet/IP、ICMP 等）、 调试动作（抓包、端口扫描、连通性测试、ping、traceroute、流量统计、pcap 分析）或网络接口操作，就应触发此 skill。

Establishes recurring vulnerability scanning workflows using Nessus, Qualys, or OpenVAS, prioritizes findings with risk scoring and CISA KEV data, integrates with SIEM for exploitation detection, and tracks remediation via SLA-based dashboards and automated ticketing.

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.

NetworkX is a Python package for creating, manipulating, and analyzing complex networks and graphs.

Create, analyze, and visualize complex networks and graphs in Python with NetworkX, including graph algorithms, community detection, synthetic network generation, and multiple I/O formats.

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

NetworkX is a Python package for creating, manipulating, and analyzing complex networks and graphs.

NetworkX is a Python package for creating, manipulating, and analyzing complex networks and graphs.

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.

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.

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.

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.

Create, manipulate, and analyze complex networks and graphs using the NetworkX Python package.

Create, manipulate, and analyze complex networks and graphs using the NetworkX Python package, including algorithms, generators, I/O, and visualization.

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