本文へ移動
cccskills

「beaconing」の検索結果

27 件 ・ 関連度順

概要と使いどころ

Performs statistical analysis of Zeek conn.log connection intervals to detect C2 beaconing patterns. Uses the ZAT library to load Zeek logs into Pandas DataFrames, calculates inter-arrival time standard deviation, and flags periodic connections with low jitter. Use when hunting for command-and-control callbacks in network data.

日本語の概要は準備中です。原文の説明を表示しています。

mukul975/Anthropic-Cybersecurity-Skills3.4万2026年8月31日 更新

Detects command-and-control beacons in network logs by analyzing connection timing: measuring inter-arrival intervals, accounting for jitter, and scoring regularity per source/destination pair to surface periodic callbacks. Activates for requests to hunt C2 beaconing, find periodic callbacks, or analyze connection-interval regularity.

日本語の概要は準備中です。原文の説明を表示しています。

meltedinhex/analyst-ai-pack222026年7月7日 更新

Performs statistical analysis of Zeek conn.log connection intervals to detect C2 beaconing patterns. Uses the ZAT library to load Zeek logs into Pandas DataFrames, calculates inter-arrival time standard deviation, and flags periodic connections with low jitter. Use when hunting for command-and-control callbacks in network data.

日本語の概要は準備中です。原文の説明を表示しています。

andycungkrinx91/konoha92026年10月9日 更新

Performs statistical analysis of Zeek conn.log connection intervals to detect C2 beaconing patterns. Uses the ZAT library to load Zeek logs into Pandas DataFrames, calculates inter-arrival time standard deviation, and flags periodic connections with low jitter. Use when hunting for command-and-control callbacks in network data.

日本語の概要は準備中です。原文の説明を表示しています。

micsapp/micstec-skills42026年3月20日 更新

Performs statistical analysis of Zeek conn.log connection intervals to detect C2 beaconing patterns. Uses the ZAT library to load Zeek logs into Pandas DataFrames, calculates inter-arrival time standard deviation, and flags periodic connections with low jitter. Use when hunting for command-and-control callbacks in network data.

日本語の概要は準備中です。原文の説明を表示しています。

aniket2348823/Vul-Agent22026年6月9日 更新

Identify ransomware-related network indicators, including C2 beaconing patterns, TOR exit node connections, data exfiltration flows, and encryption key exchange, by analyzing Zeek conn.log and NetFlow data. Use when threat hunting for active ransomware network activity or investigating suspected pre-encryption exfiltration during incident response.

日本語の概要は準備中です。原文の説明を表示しています。

mukul975/Anthropic-Cybersecurity-Skills3.4万2026年8月31日 更新

Captures and analyzes malware network traffic from a detonation: extracting C2 endpoints, HTTP/DNS patterns, TLS metadata (JA3/SNI), and beaconing from a PCAP to build network IOCs and detection. Activates for requests to analyze malware PCAP, extract C2 from traffic, or study network behavior.

日本語の概要は準備中です。原文の説明を表示しています。

meltedinhex/analyst-ai-pack222026年7月7日 更新

Builds Zeek-based network hunting analytics by writing scripts and analyzing Zeek logs (conn, dns, http, ssl, files) to surface long connections, rare JA3s, suspicious downloads, and beaconing. Activates for requests to build Zeek analytics, write a Zeek hunting script, or analyze Zeek logs for threats.

日本語の概要は準備中です。原文の説明を表示しています。

meltedinhex/analyst-ai-pack222026年7月7日 更新

Identify ransomware network indicators including C2 beaconing patterns, TOR exit node connections, data exfiltration flows, and encryption key exchange via Zeek conn.log and NetFlow analysis

日本語の概要は準備中です。原文の説明を表示しています。

andycungkrinx91/konoha92026年10月9日 更新

Identify ransomware network indicators including C2 beaconing patterns, TOR exit node connections, data exfiltration flows, and encryption key exchange via Zeek conn.log and NetFlow analysis

日本語の概要は準備中です。原文の説明を表示しています。

micsapp/micstec-skills42026年3月20日 更新

Identify ransomware network indicators including C2 beaconing patterns, TOR exit node connections, data exfiltration flows, and encryption key exchange via Zeek conn.log and NetFlow analysis

日本語の概要は準備中です。原文の説明を表示しています。

aniket2348823/Vul-Agent22026年6月9日 更新

Detects early-stage ransomware indicators in network traffic before encryption begins, including initial access broker activity, command-and-control beaconing, credential harvesting, reconnaissance scanning, and staging behavior. Uses network detection tools (Zeek, Suricata, Arkime), SIEM correlation rules, and threat intelligence feeds to identify ransomware precursor patterns such as Cobalt Strike beacons, Mimikatz network signatures, and RDP brute-force attempts. Activates for requests involving pre-ransomware detection, network-based ransomware indicators, or early warning ransomware monitoring.

日本語の概要は準備中です。原文の説明を表示しています。

mukul975/Anthropic-Cybersecurity-Skills3.4万2026年8月31日 更新

Detect command-and-control (C2) traffic tunneled over DNS from tools like Iodine, dnscat2, dns2tcp, and Cobalt Strike DNS beacon, using Shannon entropy analysis of query subdomains, ML-based DGA classification, passive DNS correlation, and Zeek/Suricata signatures. Use when investigating suspected DNS tunneling, classifying DGA domains, detecting DNS beaconing, or building DNS anomaly rules for a SOC/SIEM.

日本語の概要は準備中です。原文の説明を表示しています。

mukul975/Anthropic-Cybersecurity-Skills3.4万2026年8月31日 更新

Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning, data exfiltration, and C2 beaconing patterns. Uses the Python netflow library to decode flow records, builds traffic baselines, and applies statistical analysis to identify flows with abnormal byte counts, connection durations, and periodic timing patterns.

日本語の概要は準備中です。原文の説明を表示しています。

mukul975/Anthropic-Cybersecurity-Skills3.4万2026年8月31日 更新

Exact detection thresholds for identifying malicious network patterns including port scans, DoS attacks, and beaconing behavior.

日本語の概要は準備中です。原文の説明を表示しています。

benchflow-ai/skillsbench1,8422026年10月13日 更新

Conduct proactive, hypothesis-driven threat hunts — search SIEM / EDR / logs for adversaries who haven't tripped an alert yet. ATT&CK-driven, hypothesis-based methodology. Use when the user mentions 'threat hunting,' 'proactive hunt,' 'TaHiTI,' 'PEAK framework,' 'MITRE ATT&CK hunt,' 'hypothesis-driven hunt,' 'hunt hypothesis,' 'living off the land,' 'LOLBins,' 'beaconing,' 'lateral movement detection,' 'data staging,' 'persistence hunting,' or wants to find threats that have evaded existing detections.

日本語の概要は準備中です。原文の説明を表示しています。

briiirussell/cybersecurity-skills4192026年5月27日 更新

Use when hunting threats or engineering detections — ATT&CK Detection-Strategies, Sigma + correlation with Detection-as-Code CI, Windows endpoint hunting (Sysmon/ETW/LSASS/LOLBins), network C2 hunting (JA4+, beaconing, DNS tunneling), cloud-identity hunting, Atomic Red Team purple-team validation

日本語の概要は準備中です。原文の説明を表示しています。

hypnguyen1209/offensive-claude3902026年9月28日 更新

Use when reverse-engineering or detecting malware — static triage + capa/YARA-X, emulation/DBI/.NET unpacking, dynamic/fileless/Volatility 3 memory analysis, C2 config extraction (Cobalt Strike/CAPE), C2 traffic detection (JA4+, beaconing)

日本語の概要は準備中です。原文の説明を表示しています。

hypnguyen1209/offensive-claude3902026年9月28日 更新

Detects early-stage ransomware indicators in network traffic before encryption begins, including initial access broker activity, command-and-control beaconing, credential harvesting, reconnaissance scanning, and staging behavior. Uses network detection tools (Zeek, Suricata, Arkime), SIEM correlation rules, and threat intelligence feeds to identify ransomware precursor patterns such as Cobalt Strike beacons, Mimikatz network signatures, and RDP brute-force attempts. Activates for requests involving pre-ransomware detection, network-based ransomware indicators, or early warning ransomware monitoring.

日本語の概要は準備中です。原文の説明を表示しています。

andycungkrinx91/konoha92026年10月9日 更新

Detects command-and-control (C2) communications tunneled through DNS protocol including DNS tunneling tools (Iodine, dnscat2, dns2tcp, Cobalt Strike DNS beacon), domain generation algorithms (DGA), encoded payload delivery via TXT/CNAME records, and DNS beaconing patterns. Covers Shannon entropy analysis of query subdomains, statistical anomaly detection, ML-based DGA classification, passive DNS correlation, and Zeek/Suricata signature development. Activates for requests involving DNS-based C2 detection, DNS tunnel identification, suspicious DNS traffic investigation, or DGA domain classification.

日本語の概要は準備中です。原文の説明を表示しています。

andycungkrinx91/konoha92026年10月9日 更新

Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning, data exfiltration, and C2 beaconing patterns. Uses the Python netflow library to decode flow records, builds traffic baselines, and applies statistical analysis to identify flows with abnormal byte counts, connection durations, and periodic timing patterns.

日本語の概要は準備中です。原文の説明を表示しています。

andycungkrinx91/konoha92026年10月9日 更新

Detects early-stage ransomware indicators in network traffic before encryption begins, including initial access broker activity, command-and-control beaconing, credential harvesting, reconnaissance scanning, and staging behavior. Uses network detection tools (Zeek, Suricata, Arkime), SIEM correlation rules, and threat intelligence feeds to identify ransomware precursor patterns such as Cobalt Strike beacons, Mimikatz network signatures, and RDP brute-force attempts. Activates for requests involving pre-ransomware detection, network-based ransomware indicators, or early warning ransomware monitoring.

日本語の概要は準備中です。原文の説明を表示しています。

micsapp/micstec-skills42026年3月20日 更新

Detects command-and-control (C2) communications tunneled through DNS protocol including DNS tunneling tools (Iodine, dnscat2, dns2tcp, Cobalt Strike DNS beacon), domain generation algorithms (DGA), encoded payload delivery via TXT/CNAME records, and DNS beaconing patterns. Covers Shannon entropy analysis of query subdomains, statistical anomaly detection, ML-based DGA classification, passive DNS correlation, and Zeek/Suricata signature development. Activates for requests involving DNS-based C2 detection, DNS tunnel identification, suspicious DNS traffic investigation, or DGA domain classification.

日本語の概要は準備中です。原文の説明を表示しています。

micsapp/micstec-skills42026年3月20日 更新

Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning, data exfiltration, and C2 beaconing patterns. Uses the Python netflow library to decode flow records, builds traffic baselines, and applies statistical analysis to identify flows with abnormal byte counts, connection durations, and periodic timing patterns.

日本語の概要は準備中です。原文の説明を表示しています。

micsapp/micstec-skills42026年3月20日 更新