跳到主要内容

analyzing-browser-forensics-with-hindsight 精选

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's web activity from a browser profile.

在 GitHub 打开

安装方式

cp -r skills/analyzing-browser-forensics-with-hindsight ~/.claude/skills/analyzing-browser-forensics-with-hindsight

把该 skill 目录放进客户端 skills 目录。不同客户端的目录可能不同,Claude Code 默认是 ~/.claude/skills/

整仓一次性获取:git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git

依赖与权限

  • 无需 API Key
  • 需要联网访问外部服务
  • 依赖外部命令:python pip sqlite3 convert
  • 以上为按正文与 frontmatter 自动推断的信号,仅供参考;安装前建议先阅读原文。

SKILL.md 正文

来源 mukul975/Anthropic-Cybersecurity-Skills@54a7988 · 许可 Apache-2.0 · 内容未修改

Analyzing Browser Forensics with Hindsight

Overview

Hindsight is an open-source browser forensics tool designed to parse artifacts from Google Chrome and other Chromium-based browsers (Microsoft Edge, Brave, Opera, Vivaldi). It extracts and correlates data from multiple browser database files to create a unified timeline of web activity. Hindsight can parse URLs, download history, cache records, bookmarks, autofill records, saved passwords, preferences, browser extensions, HTTP cookies, Local Storage (HTML5 cookies), login data, and session/tab information. The tool produces chronological timelines in multiple output formats (XLSX, JSON, SQLite) that enable investigators to reconstruct user web activity for incident response, insider threat investigations, and criminal cases.

When to Use

  • When investigating security incidents that require analyzing browser forensics with hindsight
  • When building detection rules or threat hunting queries for this domain
  • When SOC analysts need structured procedures for this analysis type
  • When validating security monitoring coverage for related attack techniques

Prerequisites

  • Python 3.8+ with Hindsight installed (pip install pyhindsight)
  • Access to browser profile directories from forensic image
  • Browser profile data (not encrypted with OS-level encryption)
  • Timeline Explorer or spreadsheet application for analysis

Browser Profile Locations

BrowserWindows Profile Path
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/

Key Artifact Files

FileContents
HistoryURL visits, downloads, keyword searches
CookiesHTTP cookies with domain, expiry, values
Web DataAutofill entries, saved credit cards
Login DataSaved usernames/passwords (encrypted)
BookmarksJSON bookmark tree
PreferencesBrowser configuration and extensions
Local Storage/HTML5 Local Storage per domain
Session Storage/Session-specific storage per domain
Network Action PredictorPreviously typed URLs
ShortcutsOmnibox shortcuts and predictions
Top SitesFrequently visited sites

Running Hindsight

Command Line

# 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

Artifact Analysis Details

URL History and Visits

-- 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')

Download History

-- 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 Analysis

-- 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 Analysis Script

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()

References

  • Hindsight GitHub: https://github.com/obsidianforensics/hindsight
  • Chrome Forensics Guide: https://allenace.medium.com/hindsight-chrome-forensics-made-simple-425db99fa5ed
  • Browser Forensics Tools: https://www.cyberforensicacademy.com/blog/browser-forensics-tools-how-to-extract-user-activity
  • Chromium Source (History): https://source.chromium.org/chromium/chromium/src/+/main:components/history/

Example Output

$ 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

质量与来源

所属仓库
mukul975/Anthropic-Cybersecurity-Skills
仓库星标
3.4 万
最近更新
1 个月前
采集时间
今天
commit
54a798831d22
内容指纹
sha256:2a1b299850c0692
文件路径
skills/analyzing-browser-forensics-with-hindsight/SKILL.md

同仓库其它 Skill

查看全部 50 个
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's dpapi.py, including domain-wide decryption via the DPAPI backup key. Use during authorized red-team credential-access engagements after gaining a foothold or when triaging DPAPI blobs pulled from a host.
精选 mukul975/Anthropic-Cybersecurity-Skills 3.4 万 原文
Claude CodeCodex CLICursor
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's NT hash without a password reset. Use when BloodHound shows GenericWrite/GenericAll/AddKeyCredentialLink over a target, as a stealthier alternative to ForceChangePassword, during authorized red-team engagements.
精选 mukul975/Anthropic-Cybersecurity-Skills 3.4 万 原文
Claude CodeCodex CLICursor
achieving-cmmc-level-2-compliance
Prepare a defense-contractor environment for CMMC Level 2 certification: scope CUI and FCI, implement the 110 NIST SP 800-171 Rev 2 security requirements across 14 families, compute the SPRS score with the DoD Assessment Methodology, manage a compliant POA&M, and ready the organization for a C3PAO assessment. Use when an organization handles Controlled Unclassified Information (CUI) under a DoD contract, when a contract carries DFARS clause 252.204-7012/7019/7020/7021, when preparing for or responding to a CMMC assessment, when computing or improving an SPRS score, when building a System Security Plan or POA&M for 800-171, or when scoping which systems are in the CUI boundary. Keywords: CMMC, CMMC Level 2, NIST 800-171, SP 800-171 Rev 2, CUI, FCI, SPRS, DFARS 7012, C3PAO, POA&M, System Security Plan, DoD Assessment Methodology, 110 controls, defense industrial base, DIB, FedRAMP equivalency.
精选 mukul975/Anthropic-Cybersecurity-Skills 3.4 万 原文
Claude CodeCodex CLICursor
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.
精选 mukul975/Anthropic-Cybersecurity-Skills 3.4 万 原文
Claude CodeCodex CLICursor
analyzing-active-directory-acl-abuse
Detect dangerous ACL misconfigurations in Active Directory using ldap3
精选 mukul975/Anthropic-Cybersecurity-Skills 3.4 万 原文
Claude CodeCodex CLICursor
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.
精选 mukul975/Anthropic-Cybersecurity-Skills 3.4 万 原文
Claude CodeCodex CLICursor
agent-browser
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
精选 shanraisshan/claude-code-best-practice 6.7 万 原文
Claude CodeCodex CLIGemini CLI
presentation-structure
Knowledge about the presentation slide format, weight system, navigation, and section structure
精选 shanraisshan/claude-code-best-practice 6.7 万 原文
Claude CodeCodex CLIGemini CLI
presentation-styling
Knowledge about CSS classes, component patterns, and syntax highlighting in the presentation
精选 shanraisshan/claude-code-best-practice 6.7 万 原文
Claude CodeCodex CLIGemini CLI
vibe-to-agentic-framework
The conceptual framework behind the presentation — what "Vibe Coding to Agentic Engineering" means, why the journey is structured the way it is, and how every slide fits the narrative arc
精选 shanraisshan/claude-code-best-practice 6.7 万 原文
Claude CodeCodex CLIGemini CLI
time-skill
Display the current time in Pakistan Standard Time (PKT, UTC+5). Use when the user asks for the current time, Pakistan time, or PKT.
精选 shanraisshan/claude-code-best-practice 6.7 万 原文
Claude CodeCodex CLIGemini CLI
weather-fetcher
Instructions for fetching current weather temperature data for Dubai, UAE from Open-Meteo API
精选 shanraisshan/claude-code-best-practice 6.7 万 原文
Claude CodeCodex CLIGemini CLI