Results for “network”

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

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

Create, analyze, and visualize complex networks and graphs in Python, covering graph construction, algorithms, generators, I/O, and visualization.

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.

Creates, analyzes, and visualizes complex networks and graphs in Python with NetworkX. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing topologies — applicable to social, biological, transportation, citation, and any pairwise-relationship networks. This is classical graph analytics, not deep learning — for training graph neural networks (GCN/message passing, node/edge/graph classification on Cora-style data) use alterlab-torch-geometric instead. Part of the AlterLab Academic Skills suite.

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

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

Build network traffic baselines from NetFlow/IPFIX data using Python pandas for statistical analysis, z-score anomaly detection, and hourly/daily traffic pattern profiling.

Automate IPinfo.io IP geolocation and network data lookups through Composio's toolkit via Rube MCP.

Infer gene regulatory networks from gene expression data using scalable algorithms (GRNBoost2, GENIE3) with support for distributed computation.

Create, validate, and improve IP geolocation feeds in CSV format with RFC 8805 compliance and opinionated best practices for network operators.

Predict molecular properties, train graph neural networks, and run drug discovery workflows using DeepChem's featurizers, models, and MoleculeNet benchmarks.

Build and train graph neural networks for drug discovery, protein modeling, and molecular science using PyTorch-native tools.

Provides a standardized interface for ingesting raw data across domains such as genomics, network analysis, document review, and spatial mapping, converting it into semantic vectors for agent use.

Build and train graph neural networks with PyTorch Geometric, covering node/link/graph classification, message passing layers, heterogeneous graphs, and custom datasets.

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.

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

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

Profiles application performance across database queries, API call chains, memory usage, bundle sizes, network waterfalls, and frontend rendering, then produces ranked optimization recommendations with estimated impact.

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.

Parse and analyze Cobalt Strike Malleable C2 profiles using dissect.cobaltstrike and pyMalleableC2 to extract C2 indicators, detect evasion techniques, and generate network detection signatures.

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

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.

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.

Database development and operations workflow covering SQL, NoSQL, database design, migrations, optimization, and data engineering.

Analyze Windows Shellbag registry artifacts to reconstruct folder browsing activity, detect access to removable media and network shares, and establish user interaction with directories even after deletion using SBECmd and ShellBags Explorer.

Executes malware samples in Cuckoo Sandbox to observe runtime behavior including process creation, file system modifications, registry changes, network communications, and API calls. Generates comprehensive behavioral reports for malware classification and IOC extraction.

Integracao completa com Instagram via Graph API. Publicacao, analytics, comentarios, DMs, hashtags, agendamento, templates e gestao de contas Business/Creator.

Retrieves the current public IP address and geolocation details using curl-based web services, with fallback options and clear display formatting.

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