analyzing-browser-forensics-with-hindsight SKILL.md skillF

This file is byte-identical to the first copy the registry indexed, one of 3 indexed copies. Same content hash, so the same checks give both the same grade.

analyzing-browser-forensics-with-hindsight from andycungkrinx91/konoha is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add andycungkrinx91/konoha/analyzing-browser-forensics-with-hindsight@v1.0

Pins v1.0 in mdr.lock. Pin the fingerprint instead.

Audit grade
F, 15 of 17 checks passed
Kind
SKILL.md skill
Repository
andycungkrinx91/konoha
Path
src/templates/skills/akatsuki-skill/references/anthropic-cybersecurity-skills-assets/skills/analyzing-browser-forensics-with-hindsight/SKILL.md
Versions recorded
1
Latest version
v1.0, committed Oct 25, 2026
Size
10,925 bytes
Repository stars
15
License
MIT

Analyze Chromium-based browser artifacts using Hindsight to extract browsing.

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

# 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
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add andycungkrinx91/konoha/analyzing-browser-forensics-with-hindsight@sha256:b1c909b3f3449b4b

The line at the top of this page pins the label v1.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_m5u4ukq4hvw3sbrf.svg)](https://markdownregistry.com/a/art_m5u4ukq4hvw3sbrf)

1 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 1 version of this file, committed on Oct 25, 2026.

versioncommittedcommitsizeaudit
v1.0 latest2026-10-25 fd02612 10,925 BF view

Audit of the latest version

F  15 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • FAIL, critical: No link to an exfiltration or paste host (matched: https://pastebin.com)
  • fail: No link to a raw IP address (matched: https://192.168.1.50:8443)
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (10925 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No script tag

Starting a new one? Use a template for SKILL.md on mdpantry, which passes every one of these checks and says what to change in it.

Source

GitHub

andycungkrinx91/konoha · 15 stars · license MIT · pushed 2026-11-01 · branch master

API

GET https://markdownregistry.com/api/v1/artifacts/art_m5u4ukq4hvw3sbrf
GET https://markdownregistry.com/api/v1/resolve?ref=andycungkrinx91/konoha/analyzing-browser-forensics-with-hindsight
GET https://markdownregistry.com/api/v1/blob/b1c909b3f3449b4bed0d35c9c8d425d068b0c487d5abc79bcd4c515062eb9ff8

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.

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