Results for “networks”

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.

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.

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.

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

Agente que simula Yann LeCun — inventor das Convolutional Neural Networks, Chief AI Scientist da Meta, Prêmio Turing 2018.

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

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

Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting...

Train and analyze Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features for mechanistic interpretability research.

Produces NetworkX code with explicit graph kind, node identity, edge multiplicity, direction, attribute schema, weight semantics, and algorithm preconditions, including testing.

Networking Outreach

Create, manipulate, and analyze complex networks and graphs with the NetworkX Python package, covering graph construction, algorithms, generators, I/O, and visualization.

ENet reliable UDP skill for channels and packet fragmentation.

Creates, manipulates, and analyzes complex networks and graphs using the NetworkX Python package, including graph algorithms, synthetic network generation, I/O, and visualization.

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

DNS records, IP addressing, subnetting, common protocols, and diagnostic tools. Use when configuring DNS records, debugging resolution or connectivity, planning subnets, analyzing HTTPS/TLS errors, or diagnosing latency and routing issues.

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。

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

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.

Provides production-grade NestJS architecture patterns for modules, controllers, providers, DTO validation, guards, interceptors, config, and testing.

This skill should be used when the user asks to "set up a web server", "configure HTTP or HTTPS", "perform SNMP enumeration", "configure SMB shares", "test network services", or ne...

Remix patterns including loaders, actions, nested routing, progressive enhancement, and deployment strategies.

Detect adversary lateral movement across networks using Splunk SPL queries against Windows authentication logs, SMB traffic, and remote service abuse.

Fixes common PyTorch bugs including percentile calculations, LayerNorm for Conv1d, and buffer edge cases in reinforcement learning and neural network code.

This skill should be used when the user asks to "run pentest commands", "scan with nmap", "use metasploit exploits", "crack passwords with hydra or john", "scan web vulnerabilities with nikto", "enumerate networks", or needs essential penetration testing command references.

Identifies and exploits SMB protocol vulnerabilities using Metasploit Framework during authorized penetration tests to demonstrate risks from unpatched Windows systems, misconfigured shares, and weak authentication in enterprise networks.