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Agent Skill · 研究检索

analyzing-network-traffic-for-incidents(分析网络流量以查找事件)

analyzing-network-traffic-for-incidents 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

analyzing-network-traffic-for-incidents 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 40,912。

总安装 1,236周安装 52GitHub Stars 5,868下载 433核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:analyzing-network-traffic-for-incidents(分析网络流量以查找事件)
来源仓库:https://github.com/mukul975/anthropic-cybersecurity-skills
仓库路径:skills/analyzing-network-traffic-for-incidents
安装命令:
npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill analyzing-network-traffic-for-incidents
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill analyzing-network-traffic-for-incidents

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

从网络流量中识别潜在安全事件并提取关键证据。analyzing-network-traffic-for-incidents 属于研究检索类 Skill,可作为该场景下的辅助能力补充。适用于 SIEM 告警验证、C2 通信确认和数据外泄量统计。可追踪横向移动路径并通过包级分析增强检测准确性。

依赖完整的 PCAP 捕获文件作为输入源进行分析。不适用于主机端取证,需结合其他工具综合判断。

来源仓库内路径:skills/analyzing-network-traffic-for-incidents

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skil…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

analyzing-network-traffic-for-incidents 怎么安装?

在终端执行 npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill analyzin…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

analyzing-network-traffic-for-incidents 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

analyzing-network-traffic-for-incidents 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

analyzing-network-traffic-for-incidents 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

analyzing-network-traffic-for-incidents 用的人多吗?

公开数据是累计安装 1,236 次,近一周安装 52 次,下载 433 次,GitHub 5,868 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

analyzing-network-traffic-for-incidents 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 来源仓库有 5,868 星,维护活跃度相对可查。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
analyzing-network-traffic-for-incidents

分析网络流量以查找事件 · 本页

1,2365,868需要联网未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Analyzing Network Traffic for Incidents

When to Use

  • SIEM alerts on anomalous network traffic patterns requiring deeper investigation
  • C2 beaconing is suspected and needs confirmation through packet-level analysis
  • Data exfiltration volume or destination must be quantified from network evidence
  • Lateral movement between systems needs to be traced through network connections
  • An IDS/IPS alert requires packet-level validation to confirm or dismiss

Do not use for host-based forensic analysis (process execution, file system artifacts); use endpoint forensics tools instead.

Prerequisites

  • Full packet capture (PCAP) infrastructure or on-demand capture capability (network tap, SPAN port)
  • Wireshark installed on the analysis workstation with appropriate display filters knowledge
  • Zeek (formerly Bro) deployed for network metadata generation (conn.log, dns.log, http.log, ssl.log)
  • NetFlow/IPFIX collection from network devices for traffic flow analysis
  • Network architecture diagram showing VLAN layout, firewall placement, and monitoring points
  • Threat intelligence feeds for correlating observed network indicators

Workflow

Step 1: Capture or Acquire Network Traffic

Obtain the relevant traffic data for the investigation:

Live Capture (if incident is active):

# Capture on specific interface filtering by host
tcpdump -i eth0 -w capture.pcap host 10.1.5.42

# Capture C2 traffic to specific external IP
tcpdump -i eth0 -w c2_traffic.pcap host 185.220.101.42

# Capture with rotation (1GB files, keep 10)
tcpdump -i eth0 -w capture_%Y%m%d%H%M.pcap -C 1000 -W 10

From Existing Infrastructure:

  • Export PCAP from full packet capture appliance (Arkime/Moloch, ExtraHop, Corelight)
  • Pull Zeek logs from the Zeek cluster for the investigation timeframe
  • Export NetFlow data from network devices for high-level traffic analysis

Step 2: Identify C2 Communications

Detect command-and-control traffic patterns:

Beaconing Detection (Zeek conn.log):

# Extract connections to external IPs with regular intervals
cat conn.log | zeek-cut ts id.orig_h id.resp_h id.resp_p duration orig_bytes resp_bytes \
  | awk '$4 ~ /^185\.220/' | sort -t. -k1,1n -k2,2n

Wireshark Beacon Analysis:

# Filter for traffic to suspected C2 IP
ip.addr == 185.220.101.42

# Filter HTTPS traffic to non-standard ports
tcp.port != 443 && ssl

# Filter DNS queries for suspicious domains
dns.qry.name contains "evil" or dns.qry.name matches "^[a-z0-9]{32}\."

# Filter HTTP POST (common C2 check-in method)
http.request.method == "POST" && ip.dst == 185.220.101.42

Beaconing characteristics to identify:

  • Regular time intervals between connections (e.g., every 60 seconds with 10-15% jitter)
  • Consistent packet sizes in requests and responses
  • HTTPS to external IPs not associated with legitimate CDNs or services
  • DNS queries with high entropy subdomains (DNS tunneling indicator)

Step 3: Analyze Lateral Movement Traffic

Trace adversary movement between internal systems:

Key protocols for lateral movement detection:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
SMB (TCP 445):     PsExec, file share access, ransomware propagation
RDP (TCP 3389):    Remote desktop sessions
WinRM (TCP 5985):  PowerShell remoting
WMI (TCP 135):     Remote command execution
SSH (TCP 22):      Linux lateral movement
DCE/RPC (TCP 135): DCOM-based lateral movement

Wireshark Filters for Lateral Movement:

# SMB lateral movement
smb2 && ip.src == 10.1.5.42 && ip.dst != 10.1.5.42

# RDP connections from compromised host
tcp.dstport == 3389 && ip.src == 10.1.5.42

# Kerberos ticket requests (potential pass-the-ticket)
kerberos.msg_type == 12 && ip.src == 10.1.5.42

# NTLM authentication (potential pass-the-hash)
ntlmssp.auth.username && ip.src == 10.1.5.42

Step 4: Detect Data Exfiltration

Identify unauthorized data transfers leaving the network:

# Identify large outbound transfers in Zeek conn.log
cat conn.log | zeek-cut ts id.orig_h id.resp_h id.resp_p orig_bytes \
  | awk '$5 > 100000000' | sort -t$'\t' -k5 -rn

# DNS tunneling detection (high volume of TXT queries)
cat dns.log | zeek-cut query qtype | grep TXT | cut -f1 \
  | rev | cut -d. -f1,2 | rev | sort | uniq -c | sort -rn | head

# Unusual protocol usage (ICMP tunneling, DNS over HTTPS)
cat conn.log | zeek-cut proto id.resp_p orig_bytes | awk '$1 == "icmp" && $3 > 1000'

Wireshark Exfiltration Filters:

# Large HTTP POST uploads
http.request.method == "POST" && tcp.len > 10000

# FTP data transfers
ftp-data && ip.src == 10.0.0.0/8

# DNS with large TXT responses (tunneling)
dns.resp.type == 16 && dns.resp.len > 200

Step 5: Extract and Correlate IOCs

Pull network-based indicators from traffic analysis:

  • External IP addresses contacted by compromised hosts
  • Domains resolved via DNS during the incident timeframe
  • URLs accessed via HTTP/HTTPS (if SSL inspection is in place)
  • TLS certificate details (subject, issuer, serial number, JA3/JA3S hashes)
  • User-Agent strings from HTTP requests
  • File transfers captured in PCAP (extract using Wireshark Export Objects)

Step 6: Document Network Forensic Findings

Compile analysis into a structured report with evidence references:

  • Reference specific PCAP files, frame numbers, and timestamps for each finding
  • Include packet captures of key evidence as screenshots or exported PDFs
  • Map network activity to the incident timeline
  • Correlate network findings with host-based evidence from endpoint forensics

Key Concepts

TermDefinition
PCAP (Packet Capture)File format storing raw network packets captured from a network interface for offline analysis
BeaconingRegular, periodic network connections from a compromised host to a C2 server, identifiable by consistent timing intervals
JA3/JA3STLS client and server fingerprinting method based on the ClientHello and ServerHello parameters; unique per application
NetFlow/IPFIXNetwork traffic metadata (source, destination, ports, bytes, duration) collected by routers and switches without full packet capture
DNS TunnelingTechnique encoding data in DNS queries and responses to exfiltrate data or maintain C2 through DNS protocol
Network TapHardware device that creates an exact copy of network traffic for monitoring without impacting network performance
Zeek LogsStructured metadata logs generated by the Zeek network analysis framework covering connections, DNS, HTTP, SSL, and more

Tools & Systems

  • Wireshark: Open-source packet analyzer for deep inspection of network protocols at the packet level
  • Zeek (formerly Bro): Network analysis framework generating structured metadata logs from live or captured traffic
  • Arkime (formerly Moloch): Open-source full packet capture and search platform for large-scale network forensics
  • NetworkMiner: Network forensic analysis tool for extracting files, images, and credentials from PCAP files
  • RITA (Real Intelligence Threat Analytics): Open-source beacon detection and DNS tunneling analysis tool for Zeek logs

Common Scenarios

Scenario: Confirming C2 Beaconing and Quantifying Exfiltration

Context: EDR detects a suspicious process on a workstation but cannot determine the volume of data exfiltrated. Network team provides PCAP from the full packet capture appliance covering the incident timeframe.

Approach:

  1. Filter PCAP to traffic from the compromised host IP to external destinations
  2. Identify the C2 channel by analyzing connection timing patterns (beacon detection)
  3. Extract TLS certificate and JA3 hash from the C2 connection for IOC generation
  4. Calculate total bytes transferred to C2 infrastructure over the incident duration
  5. Check for additional exfiltration channels (DNS tunneling, cloud storage uploads)
  6. Extract any unencrypted files transferred using Wireshark Export Objects feature

Pitfalls:

  • Analyzing only HTTP traffic when C2 is operating over HTTPS without SSL inspection
  • Missing DNS tunneling because the data volume per query is small (but total over time is significant)
  • Not correlating network timestamps with endpoint timestamps (timezone mismatches)
  • Overlooking legitimate cloud services abused for exfiltration (OneDrive, Google Drive, Dropbox)

Output Format

NETWORK TRAFFIC ANALYSIS REPORT
=================================
Incident:         INC-2025-1547
Analyst:          [Name]
Capture Source:   Arkime full packet capture
Analysis Period:  2025-11-15 14:00 UTC - 2025-11-15 18:00 UTC
Total PCAP Size:  4.7 GB

C2 COMMUNICATIONS
Source:           10.1.5.42 (WKSTN-042)
Destination:      185.220.101.42:443 (HTTPS)
Beacon Interval:  60 seconds ± 12% jitter
Sessions:         237 connections over 4 hours
JA3 Hash:         a0e9f5d64349fb13191bc781f81f42e1
TLS Certificate:  CN=update.evil[.]com (self-signed)
Total Data Sent:  147 MB (outbound)
Total Data Recv:  2.3 MB (inbound - commands)

LATERAL MOVEMENT
10.1.5.42 → 10.1.10.15 (SMB, TCP 445) - 14:35 UTC
10.1.5.42 → 10.1.10.20 (RDP, TCP 3389) - 14:42 UTC
10.1.5.42 → 10.1.1.5  (LDAP, TCP 389) - 15:10 UTC

EXFILTRATION SUMMARY
Protocol:         HTTPS to C2 server
Volume:           147 MB outbound
Duration:         14:23 UTC - 18:00 UTC
Files Extracted:  [list if recoverable from unencrypted channels]

DNS ANALYSIS
Suspicious Queries: 0 DNS tunneling indicators
DGA Detection:      0 algorithmically generated domains

EVIDENCE REFERENCES
PCAP File:        INC-2025-1547_capture.pcap (SHA-256: ...)
Zeek Logs:        /logs/zeek/2025-11-15/ (conn.log, ssl.log, dns.log)

平台分布

Codex

39.17%
按下载量换算170

Claude

27.13%
按下载量换算117

Cursor

18.89%
按下载量换算82

Gemini CLI

9.03%
按下载量换算39

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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