mcpField
A
analyzing-browser-forensics-with-hindsight

analyzing-browser-forensics-with-hindsight

github.com/mukul975安全35.2k595 次安装8 周前更新
代码仓库

关于 analyzing-browser-forensics-with-hindsight

面向数字取证和事件响应人员的浏览器取证技能,介绍如何使用 Hindsight 分析 Chrome 及其他 Chromium 浏览器配置文件。它整合多类浏览器痕迹并生成时间线,支持重建网页活动。

主要功能

  1. 01解析 URL、下载记录和缓存
  2. 02提取书签、自动填充及登录数据
  3. 03检查 Cookie、本地存储和会话
  4. 04关联浏览器数据并生成时间线
  5. 05导出 XLSX、JSON 或 SQLite

适用场景

  1. 01重建事件期间的网页活动
  2. 02调查内部威胁相关浏览器痕迹
  3. 03分析取证镜像中的浏览器配置文件
  4. 04整理浏览器记录以支持事件响应

安装

复制下面的命令,在终端中运行。

$npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill analyzing-browser-forensics-with-hindsight

安装后在 Claude Code 中输入/analyzing-browser-forensics-with-hindsight确认已加载。

包含的文件

除 SKILL.md 外,安装时一起下载的参考资料和脚本。

LICENSE
assets/
template.md
references/
api-reference.md
standards.md
workflows.md
scripts/
agent.py
process.py

详细介绍

使用 Hindsight 分析浏览器取证

概述

Hindsight 是一款开源的浏览器取证工具,旨在解析 Google Chrome 及其他基于 Chromium 的浏览器(Microsoft Edge、Brave、Opera、Vivaldi)中的痕迹数据。它从多个浏览器数据库文件中提取并关联数据,创建统一的网络活动时间线。Hindsight 可以解析 URL、下载历史、缓存记录、书签、自动填充记录、已保存的密码、首选项、浏览器扩展、HTTP Cookie、本地存储(HTML5 Cookie)、登录数据以及会话/标签页信息。该工具可生成多种输出格式(XLSX、JSON、SQLite)的时间顺序时间线,使调查人员能够重建用户的网络活动,用于事件响应、内部威胁调查和刑事案件。

何时使用

  • 在调查需要借助 Hindsight 分析浏览器取证的安全事件时
  • 在为该领域构建检测规则或威胁狩猎查询时
  • 当 SOC 分析师需要针对此类分析的结构化流程时
  • 在验证相关攻击技术的安全监控覆盖范围时

前置条件

  • 已安装 Hindsight 的 Python 3.8+(pip install pyhindsight)
  • 可访问取证镜像中的浏览器配置文件目录
  • 浏览器配置文件数据(未使用操作系统级加密)
  • Timeline Explorer 或电子表格应用程序用于分析

浏览器配置文件位置

浏览器Windows 配置文件路径
Chrome%LOCALAPPDATA%\Google\Chrome\User Data\Default\
Edge%LOCALAPPDATA%\Microsoft\Edge\User Data\Default\
Brave%LOCALAPPDATA%\BraveSoftware\Brave-Browser\User Data\Default\
Opera%APPDATA%\Opera Software\Opera Stable\
Vivaldi%LOCALAPPDATA%\Vivaldi\User Data\Default\
Chrome(macOS)~/Library/Application Support/Google/Chrome/Default/
Chrome(Linux)~/.config/google-chrome/Default/

关键痕迹文件

文件内容
HistoryURL 访问、下载、关键词搜索
Cookies包含域名、过期时间、值的 HTTP Cookie
Web Data自动填充条目、已保存的信用卡
Login Data已保存的用户名/密码(加密)
BookmarksJSON 书签树
Preferences浏览器配置和扩展
Local Storage/按域名划分的 HTML5 本地存储
Session Storage/按域名划分的会话专属存储
Network Action Predictor之前输入的 URL
Shortcuts地址栏快捷方式和预测
Top Sites经常访问的网站

运行 Hindsight

命令行
# Basic analysis of a Chrome profile
hindsight.exe -i "C:\Evidence\Users\suspect\AppData\Local\Google\Chrome\User Data\Default" -o C:\Output\chrome_analysis

# Specify browser type
hindsight.exe -i "/path/to/profile" -o /output/analysis -b Chrome

# JSON output format
hindsight.exe -i "C:\Evidence\Chrome\Default" -o C:\Output\chrome --format jsonl

# With cache parsing (slower but more complete)
hindsight.exe -i "C:\Evidence\Chrome\Default" -o C:\Output\chrome --cache
Web UI
# Start Hindsight web interface
hindsight_gui.exe
# Navigate to http://localhost:8080
# Upload or point to browser profile directory
# Configure output format and analysis options
# Generate and download report

痕迹分析详情

URL 历史和访问
-- Chrome History database schema (key tables)
-- urls table: id, url, title, visit_count, typed_count, last_visit_time
-- visits table: id, url, visit_time, from_visit, transition, segment_id

-- Timestamps are Chrome/WebKit format: microseconds since 1601-01-01
-- Convert: datetime((visit_time/1000000)-11644473600, 'unixepoch')
下载历史
-- downloads table: id, current_path, target_path, start_time, end_time,
--   received_bytes, total_bytes, state, danger_type, interrupt_reason,
--   url, referrer, tab_url, mime_type, original_mime_type
Cookie 分析
-- cookies table: creation_utc, host_key, name, value, encrypted_value,
--   path, expires_utc, is_secure, is_httponly, last_access_utc,
--   has_expires, is_persistent, priority, samesite

Python 分析脚本

import sqlite3
import os
import json
import sys
from datetime import datetime, timedelta


CHROME_EPOCH = datetime(1601, 1, 1)


def chrome_time_to_datetime(chrome_ts: int):
    """Convert Chrome timestamp to datetime."""
    if chrome_ts == 0:
        return None
    try:
        return CHROME_EPOCH + timedelta(microseconds=chrome_ts)
    except (OverflowError, OSError):
        return None


def analyze_chrome_history(profile_path: str, output_dir: str) -> dict:
    """Analyze Chrome History database for forensic evidence."""
    history_db = os.path.join(profile_path, "History")
    if not os.path.exists(history_db):
        return {"error": "History database not found"}

    os.makedirs(output_dir, exist_ok=True)
    conn = sqlite3.connect(f"file:{history_db}?mode=ro", uri=True)

    # URL visits with timestamps
    cursor = conn.cursor()
    cursor.execute("""
        SELECT u.url, u.title, v.visit_time, u.visit_count,
               v.transition & 0xFF as transition_type
        FROM visits v JOIN urls u ON v.url = u.id
        ORDER BY v.visit_time DESC LIMIT 5000
    """)
    visits = [{
        "url": r[0], "title": r[1],
        "visit_time": str(chrome_time_to_datetime(r[2])),
        "total_visits": r[3], "transition": r[4]
    } for r in cursor.fetchall()]

    # Downloads
    cursor.execute("""
        SELECT target_path, tab_url, start_time, end_time,
               received_bytes, total_bytes, mime_type, state
        FROM downloads ORDER BY start_time DESC LIMIT 1000
    """)
    downloads = [{
        "path": r[0], "source_url": r[1],
        "start_time": str(chrome_time_to_datetime(r[2])),
        "end_time": str(chrome_time_to_datetime(r[3])),
        "received_bytes": r[4], "total_bytes": r[5],
        "mime_type": r[6], "state": r[7]
    } for r in cursor.fetchall()]

    # Keyword searches
    cursor.execute("""
        SELECT k.term, u.url, k.url_id
        FROM keyword_search_terms k JOIN urls u ON k.url_id = u.id
        ORDER BY u.last_visit_time DESC LIMIT 1000
    """)
    searches = [{"term": r[0], "url": r[1]} for r in cursor.fetchall()]

    conn.close()

    report = {
        "analysis_timestamp": datetime.now().isoformat(),
        "profile_path": profile_path,
        "total_visits": len(visits),
        "total_downloads": len(downloads),
        "total_searches": len(searches),
        "visits": visits,
        "downloads": downloads,
        "searches": searches
    }

    report_path = os.path.join(output_dir, "browser_forensics.json")
    with open(report_path, "w") as f:
        json.dump(report, f, indent=2)

    return report


def main():
    if len(sys.argv) < 3:
        print("Usage: python process.py <chrome_profile_path> <output_dir>")
        sys.exit(1)
    analyze_chrome_history(sys.argv[1], sys.argv[2])


if __name__ == "__main__":
    main()

参考资料

示例输出

$ python hindsight.py -i /evidence/chrome-profile -o /analysis/hindsight_output

Hindsight v2024.01 - Chrome/Chromium Browser Forensic Analysis
================================================================

Profile: /evidence/chrome-profile (Chrome 120.0.6099.130)
OS: Windows 10

[+] Parsing History database...
    URL records:          12,456
    Download records:     234
    Search terms:         567

[+] Parsing Cookies database...
    Cookie records:       8,923
    Encrypted cookies:    6,712

[+] Parsing Web Data (Autofill)...
    Autofill entries:     1,234
    Credit card entries:  2 (encrypted)

[+] Parsing Login Data...
    Saved credentials:    45 (encrypted)

[+] Parsing Bookmarks...
    Bookmark entries:     189

--- Browsing History (Last 10 Entries) ---
Timestamp (UTC)          | URL                                          | Title                        | Visit Count
2024-01-15 14:32:05.123  | https://mail.corporate.com/inbox             | Corporate Mail                | 45
2024-01-15 14:33:12.456  | https://drive.google.com/file/d/1aBcDe...    | Q4_Financial_Report.xlsx     | 1
2024-01-15 14:35:44.789  | https://mega.nz/folder/xYz123               | MEGA - Secure Cloud          | 3
2024-01-15 14:36:01.234  | https://mega.nz/folder/xYz123#upload        | MEGA - Upload                | 8
2024-01-15 14:42:15.567  | https://pastebin.com/raw/kL9mN2pQ           | Pastebin (raw)               | 1
2024-01-15 15:01:33.890  | https://192.168.1.50:8443/admin              | Admin Panel                  | 12
2024-01-15 15:15:22.111  | https://transfer.sh/upload                  | transfer.sh                  | 2
2024-01-15 15:30:45.222  | https://vpn-gateway.corporate.com            | VPN Login                    | 5
2024-01-15 16:00:00.333  | https://whatismyipaddress.com                 | What Is My IP                | 1
2024-01-15 16:05:12.444  | https://protonmail.com/inbox                 | ProtonMail                   | 3

--- Downloads (Suspicious) ---
Timestamp (UTC)          | Filename                    | URL Source                               | Size
2024-01-15 14:33:15.000  | Q4_Financial_Report.xlsm   | https://phish-domain.com/docs/report     | 245 KB
2024-01-15 14:34:02.000  | update_client.exe          | https://cdn.evil-updates.com/client.exe  | 1.2 MB

--- Cookies (Session Tokens) ---
Domain                   | Name              | Expires            | Secure | HttpOnly
.corporate.com           | SESSION_ID        | 2024-01-16 14:32   | Yes    | Yes
.mega.nz                 | session           | Session            | Yes    | Yes
.protonmail.com          | AUTH-TOKEN        | 2024-02-15 00:00   | Yes    | Yes

Report saved to: /analysis/hindsight_output/Hindsight_Report.xlsx

评论

支持 Markdown