Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add adriannoes/awesome-agentic-ai --skill extracting-browser-history-artifactsgit clone --depth 1 https://github.com/adriannoes/awesome-agentic-aiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/extracting-browser-history-artifacts)<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/extracting-browser-history-artifacts"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/extracting-browser-history-artifacts/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/extracting-browser-history-artifacts"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/extracting-browser-history-artifacts.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 5 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high YARA Match · line 71 YARA rule matched a known malware signature (reverse shell, backdoor, ransomware, C2 framework, or info stealer).Fix: Remove the malware payload or compromised file entirely. Investigate how it entered the skill and audit all other artifacts for additional indicators of compromise.
- high Privilege Escalation · line 197 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 217 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 235 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 237 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00036 | $0.02928 |
| Opus 5.5 | $0.00014 | $0.01171 |
| Sonnet 5.5 | $0.00007 | $0.00586 |
| Haiku 4.5 | $0.00004 | $0.00293 |
Grade A, and why
extracting-browser-history-artifacts scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 353 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Extracting Browser History Artifacts
When to Use
- When investigating user web activity as part of a forensic examination
- During insider threat investigations to establish patterns of data exfiltration
- When tracing user visits to malicious or policy-violating websites
- For correlating browser activity with other forensic artifacts and timelines
- When investigating phishing attacks to identify which links were clicked
Prerequisites
- Forensic image or access to user profile directories
- SQLite3 for querying browser databases
- Hindsight, BrowsingHistoryView, or DB Browser for SQLite
- Knowledge of browser artifact file locations per OS
- Python 3 with sqlite3 module for automated extraction
- Understanding of Chrome, Firefox, and Edge storage formats
Workflow
Step 1: Locate Browser Artifact Files
# Mount forensic image
mount -o ro,loop,offset=$((2048*512)) /cases/case-2024-001/images/evidence.dd /mnt/evidence
# Chrome artifact locations (Windows)
CHROME_WIN="/mnt/evidence/Users/suspect/AppData/Local/Google/Chrome/User Data/Default"
# Key files: History, Cookies, Login Data, Web Data, Bookmarks, Preferences,
# Cache/, GPUCache/, Local Storage/, Session Storage/, IndexedDB/
# Firefox artifact locations (Windows)
FIREFOX_WIN="/mnt/evidence/Users/suspect/AppData/Roaming/Mozilla/Firefox/Profiles/*.default-release"
# Key files: places.sqlite, cookies.sqlite, formhistory.sqlite, logins.json,
# key4.db, sessionstore.jsonlz4, webappsstore.sqlite
# Edge (Chromium) artifact locations (Windows)
EDGE_WIN="/mnt/evidence/Users/suspect/AppData/Local/Microsoft/Edge/User Data/Default"
# Copy artifacts to working directory
mkdir -p /cases/case-2024-001/browser/{chrome,firefox,edge}
cp -r "$CHROME_WIN"/{History,Cookies,Downloads,"Login Data","Web Data",Bookmarks} \
/cases/case-2024-001/browser/chrome/ 2>/dev/null
cp -r $FIREFOX_WIN/{places.sqlite,cookies.sqlite,formhistory.sqlite,logins.json} \
/cases/case-2024-001/browser/firefox/ 2>/dev/null
cp -r "$EDGE_WIN"/{History,Cookies,Downloads} \
/cases/case-2024-001/browser/edge/ 2>/dev/null
# Hash artifacts for integrity
find /cases/case-2024-001/browser/ -type f -exec sha256sum {} \; \
> /cases/case-2024-001/browser/artifact_hashes.txt
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 353 lines · 36 tokens per session scan A cffc9b82939c
extracting-browser-history-artifacts is a skill published in the GitHub repository adriannoes/awesome-agentic-ai (96 stars, last pushed 5d ago), licensed MIT. It adds 36 tokens to every session and 2,928 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
extracting-browser-history-artifacts compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| extracting-browser-history-artifactsadriannoes/awesome-agentic-ai | Skill | 96 | 5d ago | MIT | A | 36 | Claude Code, Codex |
| extracting-browser-history-artifactsxalgorix/xalgorix | Skill | 1.3k | yesterday | Apache-2.0 | A | 36 | Claude Code, Codex |
| Browser Extension TestingPramodDutta/qaskills | Skill | 245 | 5d ago | MIT | A | 29 | Claude Code, Codex |
| Cross-Browser Compatibility TestingPramodDutta/qaskills | Skill | 245 | 5d ago | MIT | A | 32 | Claude Code, Codex |
| analyzing-browser-forensics-with-hindsightmukul975/Anthropic-Cybersecurity-Skills | Skill | 36k | 2mo ago | Apache-2.0 | A | 95 | Claude Code |
| analyzing-browser-forensics-with-hindsightxalgorix/xalgorix | Skill | 1.3k | yesterday | Apache-2.0 | A | 53 | Claude Code, Codex |
| Laravel Dusk TestingPramodDutta/qaskills | Skill | 245 | 5d ago | MIT | A | 44 | Claude Code, Codex |