microsoft/llmail-inject-challenge-analysis

Data Analysis of the results of llmail-inject challenge

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Experimental

This project provides an in-depth analysis of results from a prompt injection challenge focused on large language model (LLM) security within email systems. It takes submissions from attack attempts against an LLM-powered email assistant and evaluates their effectiveness. Security researchers and LLM developers can use this to understand the strengths and weaknesses of different prompt injection defenses.

No commits in the last 6 months.

Use this if you are a security researcher or LLM developer seeking to understand how adaptive prompt injection attacks bypass defenses in email-based LLM applications.

Not ideal if you are looking for an active tool to perform prompt injection attacks or to implement defenses directly, as this is an analysis of a past challenge.

LLM Security Prompt Injection Cybersecurity Research AI Safety Email Security
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 5 / 25
Maturity 15 / 25
Community 7 / 25

How are scores calculated?

Stars

10

Forks

1

Language

Jupyter Notebook

License

MIT

Last pushed

Jul 01, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/llm-tools/microsoft/llmail-inject-challenge-analysis"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.