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使用NetFlow分析網路流量資料

解析 NetFlow v9 和 IPFIX 記錄,以偵測流量異常、連接埠掃描及資料外洩。

使用NetFlow分析網路流量資料 是什麼?

這個技能專門用於分析網路流量資料,協助安全團隊透過 NetFlow v9 及 IPFIX 協定解析封包,找出潛在的安全威脅。它支援常見的異常偵測場景,例如連接埠掃描(單一來源對多個目的地相同連接埠)、資料外洩(高位元組數量的對外流量流向異常目的地)、C2 通訊(固定間隔的週期性連線)以及流量突增等容積異常。使用者可以透過 pip 安裝 netflow 套件,啟動內建的收集器監聽連接埠 9995,並使用 netflow.parse_packet() 解析擷取的流量。此技能可搭配 Python 程式碼與 CLI 命令執行,最後產出包含優先順序的發現報告。支援平台為任何可執行 Python 3.8+ 的環境,是 SOC 分析師進行威脅狩獵與監控覆蓋驗證的實用工具。

相容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-network-flow-data-with-netflow

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開啟一個已預先載入此 Agent Skill 的新對話。

說明文件

使用NetFlow分析網路流量資料 是做什麼的?

使用時機

  • 調查需要以NetFlow分析網路流量資料的安全事件時
  • 建立此領域的偵測規則或威脅狩獵查詢時
  • SOC分析師需要此分析類型的結構化程序時
  • 驗證相關攻擊技術的安全監控覆蓋範圍時

前置條件

  • 熟悉網路安全概念與工具
  • 可存取測試或實驗環境以安全執行
  • Python 3.8+ 並安裝所需依賴套件
  • 已取得進行任何測試活動的適當授權

指示

  1. 安裝依賴套件:pip install netflow
  2. 從路由器收集NetFlow/IPFIX資料,或使用內建收集器:python -m netflow.collector -p 9995
  3. 使用 netflow.parse_packet() 解析擷取的流量資料
  4. 分析流量中是否有以下情況:
    • 連接埠掃描:單一來源對多個目的地使用相同連接埠
    • 資料外洩:高位元組數量的對外流量流向異常目的地
    • C2通訊:固定間隔的週期性連線
    • 容積異常:超出基線閾值的流量突增
  5. 產出包含優先順序的發現報告。
python scripts/agent.py --flow-file captured_flows.json --output netflow_report.json

範例

解析NetFlow v9封包

import netflow
data, _ = netflow.parse_packet(raw_bytes, templates={})
for flow in data.flows:
    print(flow.IPV4_SRC_ADDR, flow.IPV4_DST_ADDR, flow.IN_BYTES)

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

abusing-dpapi-for-credential-access

Extract and decrypt Windows DPAPI-protected secrets (Credential Manager, browser logins/cookies, Wi-Fi credentials, KeePass keys) online or offline using SharpDPAPI, SharpChrome, Mimikatz, or Impacket

abusing-shadow-credentials-for-privesc

Take over Active Directory accounts by writing attacker-controlled public keys to msDS-KeyCredentialLink (Shadow Credentials) with pyWhisker, Whisker, or Certipy, then authenticate via PKINIT to recover the target

achieving-cmmc-level-2-compliance

>-

acquiring-disk-image-with-dd-and-dcfldd

Create forensically sound bit-for-bit disk images with dd or dcfldd on a Linux forensic workstation, preserving evidence integrity through hash verification (MD5/SHA) during acquisition. Use when imaging a suspect drive, USB device, or memory card for investigation, preserving volatile disk evidence during incident response, or producing a verified copy for legal or law-enforcement proceedings before any destructive analysis.

analyzing-active-directory-acl-abuse

Detect dangerous ACL misconfigurations in Active Directory using ldap3

analyzing-android-malware-with-apktool

Perform static analysis of Android APK malware using apktool for resource decompilation, jadx for Java source recovery, and androguard for manifest inspection, dangerous permission-combination detection, and identification of obfuscated code, dynamic code loading, and reflection-based API calls. Use to statically triage a suspicious APK without executing it or to build mobile malware detection rules.

analyzing-api-gateway-access-logs

Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect

analyzing-apt-group-with-mitre-navigator

Query ATT&CK data with attackcti, mitreattack-python, and stix2, then build MITRE ATT&CK Navigator layers and multi-layer heatmap overlays mapping one or more APT groups

analyzing-azure-activity-logs-for-threats

Queries Azure Monitor activity logs and sign-in logs via azure-monitor-query

analyzing-bootkit-and-rootkit-samples

Analyzes bootkit and advanced rootkit malware infecting the Master

analyzing-browser-forensics-with-hindsight

Parse Chromium-based browser databases with Hindsight to extract and correlate browsing history, downloads, cookies, cached content, autofill data, saved passwords, and extensions from Chrome, Edge, Brave, Opera, and Vivaldi into a unified timeline (XLSX, JSON, or SQLite output). Use during incident response, insider-threat investigations, or criminal cases when you need to reconstruct a user

analyzing-campaign-attribution-evidence

Systematically evaluate cyber-campaign evidence to attribute an operation to a threat actor, using the Diamond Model and Analysis of Competing Hypotheses (ACH) to weigh infrastructure overlaps, TTP consistency, malware code similarity, and timing/language artifacts into confidence-weighted attribution assessments. Use when an incident investigation needs a defensible attribution confidence level.

analyzing-certificate-transparency-for-phishing

Monitor Certificate Transparency logs using crt.sh and Certstream to

analyzing-cloud-storage-access-patterns

Detect abnormal access in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics for after-hours bulk downloads, new-IP access, and API-call spikes (e.g. GetObject) via statistical baselines and time-series anomaly detection. Use when investigating suspected cloud data exfiltration or building related detection rules.

analyzing-cobalt-strike-beacon-configuration

Extract and analyze Cobalt Strike beacon configuration from PE files

analyzing-cobaltstrike-malleable-c2-profiles

Parse and analyze Cobalt Strike Malleable C2 profiles with dissect.cobaltstrike (profiles and beacon-payload configs) and pyMalleableC2 (AST parsing) to extract HTTP/DNS transforms, URIs, headers, sleep/jitter, and injection behavior, then generate network detection signatures. Use when reverse-engineering a captured malleable profile or building detections against Cobalt Strike Beacon traffic.

analyzing-command-and-control-communication

Analyzes malware C2 communication over HTTP, HTTPS, DNS, and custom

analyzing-cyber-kill-chain

Analyzes intrusion activity against the Lockheed Martin Cyber Kill Chain

analyzing-disk-image-with-autopsy

Perform comprehensive forensic analysis of raw (dd), E01, or AFF disk images with Autopsy and The Sleuth Kit, recovering deleted files, examining metadata and embedded artifacts, keyword searching, and building investigation timelines with visual reports. Use for structured analysis of a forensic disk image or when stakeholders need visual reports from evidence.

analyzing-dns-logs-for-exfiltration

Analyzes DNS query logs to detect data exfiltration via DNS tunneling,

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