Results for “detection”

Turns any folder of files into a navigable knowledge graph with community detection, producing interactive HTML, GraphRAG-ready JSON, and a plain-language report.

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

Query Solana blockchain data with USD pricing — wallet balances, token portfolios with values, transaction details, NFTs, whale detection, and live network stats. Uses Solana RPC + CoinGecko. No API key required.

Run machine learning and generative AI tasks directly in BigQuery SQL using built-in functions for forecasting, anomaly detection, key driver analysis, and text generation.

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.

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

Reduces SOC alert fatigue by tuning detection rules, consolidating duplicate alerts, implementing risk-based alerting, and measuring alert quality metrics to maintain analyst effectiveness.

Build video analytics pipelines using NVIDIA DeepStream SDK 9.0 with Python pyservicemaker API, including GStreamer-based video processing, TensorRT inference integration, object detection/tracking, and Kafka/message broker integration.

Detects cyber attacks targeting SCADA systems, including man-in-the-middle, command injection, HMI compromise, historian manipulation, and DoS, using OT-specific intrusion detection and protocol anomaly analysis.

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.

Deploys anomaly detection for industrial control environments using machine learning models trained on OT network baselines, physics-based process models, and behavioral analysis of industrial protocol communications.

Parse Apache and Nginx access logs to detect SQL injection, LFI, XSS, scanner fingerprints, and brute-force patterns using regex-based detection, GeoIP enrichment, and statistical anomaly analysis.

Detect Cobalt Strike beacon network activity using TLS certificate signatures, JA3/JA3S/JARM fingerprints, HTTP C2 profile matching, beacon jitter analysis, and named pipe detection via Zeek, Suricata, and Python PCAP analysis.

High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.

Analyzes Zeek conn.log connection intervals using statistical methods to detect C2 beaconing patterns, flagging periodic connections with low jitter.

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.

Detect suspicious Windows service installations (MITRE ATT&CK T1543.003) by parsing System event logs for Event ID 7045, analyzing service binary paths, and identifying indicators of persistence mechanisms.

Extracts selected metadata from a DICOM file and flags standard-tag PHI presence. Not for anonymization or clinical use.

Quantifies market top probability using O'Neil Distribution Days, Minervini leading stock deterioration, and Monty defensive sector rotation, producing a 0-100 composite score with risk zone classification for tactical 2-8 week timing signals.

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.

Process whole slide images for digital pathology: detect tissue, extract tiles, and prepare datasets for deep learning pipelines.

Detect and extract hidden data embedded in images, audio, and other media files using steganalysis tools to uncover covert communication channels.

Automatically detect and analyze scientific data files across 200+ formats, generating detailed markdown reports with quality metrics and analysis recommendations.

Create, analyze, and visualize complex networks and graphs in Python using NetworkX, including graph construction, algorithms, generators, I/O, and plotting.

Detects anomalies in Modbus/TCP and Modbus RTU communications in industrial control systems using Zeek, Suricata, and custom Python analysis.

Analyze CJA dimensions for cardinality, distribution, trends, anomalies, data quality, comparisons, and forecasting, producing an interactive HTML dashboard or markdown report.

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

Cleans datasets, detects anomalies, generates reports, and creates visualizations using pandas, scikit-learn, and plotting libraries to turn raw data into client-ready deliverables.

Integrates multi-dimensional health data to detect anomalies, predict risks (hypertension, diabetes, cardiovascular), and generate personalized recommendations and interactive HTML reports.

Analyzes AWS billing data with anti-hallucination guardrails, covering cost breakdowns, trends, anomaly detection, RI/SP utilization, forecasting, and multi-account comparisons using Cost Explorer.