Results for “network”

Extract a TikTok user's profile info and paginated video list with full metadata by navigating to their profile page.

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

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

Analyze volatile memory dumps using Volatility 3 to extract running processes, network connections, loaded modules, and evidence of malicious activity.

Guides composing SOSL FIND queries with result-scoping or result-shaping WITH clauses, covering clause order, supported objects, field-type limits, and API-version floors.

Generate an OpenAPI 3.1 specification from a browser-trace capture by analyzing observed HTTP traffic, templating URLs, and inferring JSON schemas from request/response samples.

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.

Analyze PCAP files by reconstructing TCP/UDP sessions, decoding application-layer protocols, and correlating packet sequences with host or malware behavior for CTF challenges.

Detect APT lateral movement by chaining Windows authentication events, process execution telemetry, and network connection logs across hosts using Splunk SPL and Sigma rule format.

Analyzes RAM memory dumps from compromised systems using the Volatility framework to identify malicious processes, injected code, network connections, loaded modules, and extracted credentials.

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.

Collects every tweet in an X (Twitter) conversation thread given a conversation id, returning normalized per-tweet data with text, author, engagement counts, media, hashtags, mentions, and reply mapping.

Detect command injection attacks against Modbus TCP/RTU protocol in ICS environments by monitoring for unauthorized write operations, anomalous function codes, malformed frames, and deviations from established communication baselines.

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.

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.

Acquires Linux memory using the LiME kernel module and analyzes the image with Volatility 3 to extract processes, network connections, bash history, kernel modules, and injected code for incident response.

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.

Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, faster pandas replacement. For larger-than-RAM data use dask or vaex.

Detect anomalies in DNP3 protocol communications used in SCADA systems by monitoring for unauthorized control commands, firmware update attempts, protocol violations, and deviations from baseline traffic patterns using deep packet inspection and machine learning approaches.

Hardens and secures process historian servers (OSIsoft PI, Honeywell PHD, GE Proficy, AVEVA Historian) in OT environments, covering network placement, access control, data replication through DMZ, SQL injection prevention, and data integrity protection.

Provides a structured framework for analyzing cyber intrusions by examining four core features: Adversary, Capability, Infrastructure, and Victim. Covers implementing the Diamond Model programmatically to classify and correlate intrusion events, build activity threads, and generate pivot-ready intelligence.

Detect cyber attacks targeting OT historian servers (OSIsoft PI, Ignition, Wonderware) that sit at the IT/OT boundary and serve as pivot points for lateral movement between enterprise and control networks, including data manipulation, unauthorized queries, and exploitation of historian-specific vulnerabilities.

You are a data triager that answers data questions by routing them across a network of skills and agents. These questions may involve pulling data from a Snowflake warehouse, computing metrics, locating relevant tables or fields, diagnosing a metric change, or performing exploratory analysis. Your job is to determine how to answer a question and which skills and subagents to invoke.

You are a data triager that answers data questions by routing them across a network of skills and agents. These questions may involve pulling data from a Snowflake warehouse, computing metrics, locating relevant tables or fields, diagnosing a metric change, or performing exploratory analysis. Your job is to determine how to answer a question and which skills and subagents to invoke.