Communitygithub.com

分析惡意軟體沙箱規避技術

透過分析行為報告,檢測惡意軟體樣本中的沙箱和虛擬機器規避技術。

分析惡意軟體沙箱規避技術 是什麼?

此技能專注於分析惡意軟體中使用的沙箱規避技術(對應 MITRE ATT&CK T1497),這些技術使惡意軟體能夠偵測分析環境並改變行為以避免被發現。它能夠解析來自 Cuckoo Sandbox 和 AnyRun 的行為報告,並識別多種規避指標,包括基於計時的檢查(例如使用 GetTickCount、QueryPerformanceCounter、睡眠膨脹)、VM 工件檢測(例如註冊表鍵值、MAC 地址前綴、vmtoolsd.exe 等進程名稱)、用戶互動檢查(例如滑鼠移動、鍵盤輸入)以及環境指紋識別(例如磁碟大小、CPU 數量、RAM)。該技能會生成一份 JSON 格式的報告,其中列出檢測到的規避技術,並附帶 MITRE ATT&CK 映射、API 呼叫證據以及規避複雜度評分。它適用於安全事件調查、威脅獵捕、SOC 分析流程以及驗證安全監控覆蓋範圍,支援 Cuckoo Sandbox 2.0+ 和 AnyRun 平台,並需要 Python 3.8+ 環境來解析行為報告 JSON 檔案。

相容平台~Claude Code~Codex CLI✓Cursor
npx skills add https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-malware-sandbox-evasion-techniques

在你喜歡的 AI 中提問

開啟一個已預先載入此 Agent Skill 的新對話。

說明文件

分析惡意軟體沙箱規避技術 是做什麼的?

概述

沙箱規避(MITRE ATT&CK T1497)使惡意軟體能夠偵測分析環境並改變行為以逃避偵測。本技能會分析來自 Cuckoo Sandbox 和 AnyRun 的行為報告,尋找規避指標,包括基於計時的檢查(GetTickCount、QueryPerformanceCounter、睡眠膨脹)、VM 工件檢測(註冊表鍵值、MAC 地址前綴、vmtoolsd.exe 等進程名稱)、用戶互動檢查(滑鼠移動、鍵盤輸入)以及環境指紋識別(磁碟大小、CPU 數量、RAM)。偵測規則會標記表現出這些行為的樣本,以便進行更深層的手動分析。

使用時機

  • 在調查需要分析惡意軟體沙箱規避技術的安全事件時
  • 在為此領域建立偵測規則或威脅獵捕查詢時
  • 當 SOC 分析師需要此分析類型的結構化程序時
  • 在驗證相關攻擊技術的安全監控覆蓋範圍時

先決條件

  • Cuckoo Sandbox 2.0+ 或 AnyRun 帳戶,用於取得行為分析報告
  • Python 3.8+ 及 json 函式庫,用於解析報告
  • JSON 格式的行為報告匯出檔案

步驟

  1. 解析 Cuckoo/AnyRun 行為報告 JSON 檔案
  2. 提取與計時相關的 API 呼叫序列
  3. 透過註冊表查詢和 WMI 呼叫識別 VM 工件檢測
  4. 比較請求的睡眠時間與實際睡眠時間,以偵測睡眠膨脹
  5. 標記用戶互動檢查(GetCursorPos、GetAsyncKeyState 模式)
  6. 根據技術數量和多樣性對規避複雜度進行評分
  7. 將檢測到的技術映射到 MITRE ATT&CK T1497 子技術

預期輸出

一份 JSON 格式的報告,列出檢測到的規避技術,包含 MITRE ATT&CK 映射、API 呼叫證據、規避複雜度評分,以及規避類別分類(計時、VM 檢測、用戶互動、環境指紋識別)。

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,

相關技能