Results for “beaconing-detection”

COCO: Microsoft COCO: Common Objects in Context

Open-Vocabulary Object Detection Using Captions

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

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.

Nocaps: Novel Object Captioning at Scale

This skill provides guidance for video analysis and processing tasks using computer vision techniques. It should be used when analyzing video frames, detecting motion or events, tracking objects, extracting temporal data (e.g., identifying specific frames like takeoff/landing moments), or performing frame-by-frame processing with OpenCV or similar libraries.

Detect AI-generated audio, images, video, and text, trace synthesis sources, apply watermarks, verify speaker identity, and analyze media intelligence using the Resemble AI platform.

Embeds target and source image parquets, then mines nearest-neighbour source images for augmentation in VCN AOI workflows.

Deploys deception technology including honeypots, honeytokens, and decoy systems to detect attackers who have bypassed perimeter defenses, providing high-fidelity alerts with near-zero false positive rates.

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.

Detect and analyze heap spray attacks in memory dumps using Volatility3 plugins to identify NOP sled patterns, shellcode landing zones, and suspicious large allocations in process virtual address space.

Multimodal Few-Shot Learning with Frozen Language Models

Detect container escape attempts using runtime security tools like Falco, Sysdig, and custom seccomp/audit rules.

Mosaic Augmentation for Detection and Segmentation

Engineering privacy and data governance: PII detection, data flow mapping, consent patterns, GDPR/CCPA-compliant implementation, DPIA. Use when privacy-by-design is needed.

Detect domain fronting C2 traffic by analyzing SNI vs HTTP Host header mismatches in proxy logs and TLS certificate discrepancies using pyOpenSSL for certificate inspection.

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.

Detects lateral movement techniques including Pass-the-Hash, PsExec, WMI execution, RDP pivoting, and SMB-based spreading using SIEM correlation of Windows event logs, network flow data, and endpoint telemetry mapped to MITRE ATT&CK Lateral Movement (TA0008) techniques.

Performance regression detection using the browse daemon. Establishes baselines for page load times, Core Web Vitals, and resource sizes. Compares before/after on every PR. Tracks performance trends over time. Use when: "performance", "benchmark", "page speed", "lighthouse", "web vitals", "bundle size", "load time". (gstack) Voice triggers (speech-to-text aliases): "speed test", "check performance".

Perform time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search using a scikit-learn compatible Python toolkit.

Utilize Shodan, the search engine for Internet-connected devices, to discover exposed assets, vulnerable ports, default credentials, and specific infrastructure configurations using advanced search queries (dorks).

A股智能分析与智能选股工具。维护动态股票池(最多30支),按高科技×中小市值×好业绩原则筛选,推送买卖信号。含独立技术面择时分(-10~+10)用于判断买卖时机。A股投资、股市分析、量化选股。

SynthText: Synthetic Data for Text Detection

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GLIP: Grounded Language-Image Pre-training