0xsrb

0xsrb / AASRT

Public

Imperial Security Reconnaissance System

23
4
100% credibility
Found Feb 17, 2026 at 15 stars -- GitGems finds repos before they trend. Get early access to the next one.
Sign Up Free
AI Analysis
Python
AI Summary

AASRT is an AI Agent Security Reconnaissance Tool that automates the discovery of publicly exposed AI agent implementations using the Shodan search engine API, performs vulnerability assessments, risk scoring, and provides comprehensive reporting via CLI and web dashboard.

Star Growth

See how this repo grew from 15 to 23 stars Sign Up Free
Repurpose This Repo

Repurpose is a Pro feature

Generate ready-to-use prompts for X threads, LinkedIn posts, blog posts, YouTube scripts, and more -- with full repo context baked in.

Unlock Repurpose
AI-Generated Review

What is AASRT?

AASRT is a Python tool that scans the internet via Shodan for exposed AI agents like AutoGPT, LangChain, and ClawdBot instances, flagging vulnerabilities such as API key leaks or missing auth. It delivers passive reconnaissance with risk scoring, JSON/CSV reports, and a Streamlit dashboard featuring interactive maps and scan history stored in SQLite. Developers get quick visibility into unsecured AI infrastructure before it becomes a liability.

Why is it gaining traction?

Pre-built query templates target niche AI exposures that generic scanners miss, plus Docker Compose for one-command deploys and a full CLI for automation. The imperial security Star Wars theme adds visual flair to the dashboard without sacrificing function, and it emphasizes legal passive scans only. Low barrier to entry with Shodan API integration hooks security pros scanning for imperial security bureau-style threats.

Who should use this?

Red teamers hunting exposed LLM endpoints in engagements, DevSecOps engineers auditing AI deployments across their org, or bug bounty hunters targeting imperial college github enterprise misconfigs and aster hospital-style public AI tools. Ideal for teams evaluating aastha hospital mumbai or similar exposed services without active probing.

Verdict

With 13 stars and 1.0% credibility score, it's early-stage but backed by solid docs, Docker support, and 63 passing tests at 35% coverage—try it for AI recon prototypes, but validate outputs manually before production use. Pairs well with imperial github copilot workflows for quick threat hunting.

(198 words)

Sign up to read the full AI review Sign Up Free

Similar repos coming soon.