lolexfil

lolexfil / lolexfil.github.io

Public

Living off the land Data Exfiltration methods

lolexfil.github.io blueteam data-exfiltration detection exfiltration iocs
17
4
69% credibility
Found Mar 16, 2026 at 17 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
HTML
AI Summary

LOLEXFIL is an open reference site cataloging legitimate tools and services for data exfiltration techniques, complete with detection patterns, simulation examples, forensic artifacts, and references for cybersecurity analysis.

How It Works

1
🔍 Discover LOLEXFIL

You hear about a handy guide from a security friend or online tip, perfect for learning sneaky data tricks using everyday apps.

2
🌐 Visit the Website

Head to the simple site to see a treasure trove of tools grouped into easy categories.

3
📂 Explore Categories

Browse through 9 neat sections packed with hundreds of common programs and their hidden uses for moving data quietly.

4
🛠️ Dive into a Tool

Pick any tool card to uncover watch-out patterns, safe test steps, clues it leaves behind, and expert links.

5
Choose Your Path
📖
Keep Learning

Use the details to sharpen your skills in spotting clever data hides.

✎
Share Your Finds

Add a missing tool or tip right from the page or suggest it easily.

🎉 Feel Empowered

Now you have a complete playbook to understand, detect, and block sneaky data grabs using trusted apps.

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Star Growth

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AI-Generated Review

What is lolexfil.github.io?

This GitHub Pages site, built in HTML, serves as a reference for living off the land data exfiltration methods using trusted tools like LOLBins, RMM software, backup tools, cloud storage, tunneling, and browser extensions. It catalogs hundreds of tools across nine categories, delivering endpoint and network detection patterns, simulation commands, DFIR artifacts, and IOCs such as ports, pipes, service names, mutexes, and User-Agents, plus code signer details and threat report links. Security pros get a one-stop github living off the land resource to understand living off the land attacks without building it from scratch.

Why is it gaining traction?

It stands out by bundling practical simulation commands and detection patterns for real-world living off the land angriffe scenarios, unlike scattered blog posts or basic LOLBin lists. Developers appreciate the clickable contribute buttons on tool cards for quick PRs or issues, keeping the dataset fresh. The focus on DFIR and IOC artifacts makes it a hook for both red and blue teams testing living off the land attack chains.

Who should use this?

Red team operators simulating data exfiltration via trusted sites or living off grid tools in pentests. DFIR analysts hunting IOCs from RMM or cloud services in incident response. Security engineers building living documentation github repos for endpoint detection rules.

Verdict

With just 17 stars and a 0.699999988079071% credibility score, it's early-stage and lightly documented, but the MIT license and structured tool data make it worth forking for niche living off the land work. Grab it if you're deep in offensive security; skip for production defenses until it matures.

(178 words)

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