cybersentry

ไฝœ่€… prutxviโœ“ ๅทฒ้ชŒ่ฏ

๐Ÿค– Autonomous AI-powered ethical hacking agent powered by Llama 3.1 70B on NVIDIA NIM

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2026/8/24
ๆทปๅŠ ๆ—ถ้—ด

โš ๏ธ ็ฌฌไธ‰ๆ–น่ฝฏไปถๅฃฐๆ˜Ž

ๆœฌ Skill ไธบ็ฌฌไธ‰ๆ–นๅผ€ๆบ่ฝฏไปถ๏ผŒ็‹ฌ็ซ‹ๆ‰˜็ฎกไบŽ GitHubใ€‚SkillTip ไป…ไธบไฟกๆฏ็›ฎๅฝ•๏ผŒไธๆŽงๅˆถๆˆ–็ปดๆŠคๅบ•ๅฑ‚ไป“ๅบ“ใ€‚ๆ‰€ๆ˜พ็คบ็š„ๅฎ‰ๅ…จๆฃ€ๆŸฅไธบ่‡ชๅŠจๅŒ–ไธ”่Œƒๅ›ดๆœ‰้™๏ผŒๅฎ‰่ฃ…ๅ‰่ฏท่‡ช่กŒๅฎกๆŸฅๆบ็ ใ€‚

้˜…่ฏปๆœๅŠกๆกๆฌพ

ๅฎ‰่ฃ…

ๆทปๅŠ ๅˆฐไฝ ็š„ Claude Code skills ็›ฎๅฝ•๏ผš

# Add to your Claude Code skills
git clone https://github.com/prutxvi/cybersentry

ๅฟซ้€Ÿๅ…ฅ้—จ

ไฝฟ็”จ cybersentry ็ญ‰ Skills ็š„ๆŒ‡ๅ—ใ€‚

ๅฎ‰ๅ…จๆŠฅๅ‘Š

ๅทฒ้ชŒ่ฏ

ไธŠๆฌกๆ‰ซๆ๏ผšโ€”

{
  "status": "PASSED",
  "issues": []
}

README.md

  โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•—   โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•— โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•—โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•— โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•—โ–ˆโ–ˆโ–ˆโ•—   โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•—โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•— โ–ˆโ–ˆโ•—   โ–ˆโ–ˆโ•—
 โ–ˆโ–ˆโ•”โ•โ•โ•โ•โ•โ•šโ–ˆโ–ˆโ•— โ–ˆโ–ˆโ•”โ•โ–ˆโ–ˆโ•”โ•โ•โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•”โ•โ•โ•โ•โ•โ–ˆโ–ˆโ•”โ•โ•โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•”โ•โ•โ•โ•โ•โ–ˆโ–ˆโ–ˆโ–ˆโ•—  โ–ˆโ–ˆโ•‘โ•šโ•โ•โ–ˆโ–ˆโ•”โ•โ•โ•โ–ˆโ–ˆโ•”โ•โ•โ–ˆโ–ˆโ•—โ•šโ–ˆโ–ˆโ•— โ–ˆโ–ˆโ•”โ•
 โ–ˆโ–ˆโ•‘      โ•šโ–ˆโ–ˆโ–ˆโ–ˆโ•”โ• โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•”โ•โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•—  โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•”โ•โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•”โ–ˆโ–ˆโ•— โ–ˆโ–ˆโ•‘   โ–ˆโ–ˆโ•‘   โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•”โ• โ•šโ–ˆโ–ˆโ–ˆโ–ˆโ•”โ• 
 โ–ˆโ–ˆโ•‘       โ•šโ–ˆโ–ˆโ•”โ•  โ–ˆโ–ˆโ•”โ•โ•โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•”โ•โ•โ•  โ–ˆโ–ˆโ•”โ•โ•โ–ˆโ–ˆโ•—โ•šโ•โ•โ•โ•โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•‘โ•šโ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•‘   โ–ˆโ–ˆโ•‘   โ–ˆโ–ˆโ•”โ•โ•โ–ˆโ–ˆโ•—  โ•šโ–ˆโ–ˆโ•”โ•  
 โ•šโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•—  โ–ˆโ–ˆโ•‘   โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•”โ•โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•‘  โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•‘ โ•šโ–ˆโ–ˆโ–ˆโ–ˆโ•‘   โ–ˆโ–ˆโ•‘   โ–ˆโ–ˆโ•‘  โ–ˆโ–ˆโ•‘   โ–ˆโ–ˆโ•‘   
  โ•šโ•โ•โ•โ•โ•โ•  โ•šโ•โ•   โ•šโ•โ•โ•โ•โ•โ• โ•šโ•โ•โ•โ•โ•โ•โ•โ•šโ•โ•  โ•šโ•โ•โ•šโ•โ•โ•โ•โ•โ•โ•โ•šโ•โ•  โ•šโ•โ•โ•โ•   โ•šโ•โ•   โ•šโ•โ•  โ•šโ•โ•   โ•šโ•โ•   
                                                                                        
          ๐Ÿ” AI-Powered Autonomous Ethical Hacking Agent ๐Ÿ”

CyberSentry: Autonomous Ethical Website Security Auditor

Python 3.13 NVIDIA NIM Llama 3.1 70B License: MIT ReAct Architecture Ethical Hacking


๐Ÿ“‹ Table of Contents


Overview

CyberSentry is an autonomous AI-powered security auditing agent designed for ethical website penetration testing and vulnerability assessment. Powered by NVIDIA NIM running Llama 3.1 70B, it implements a ReAct loop architecture (Think โ†’ Act โ†’ Observe โ†’ Repeat) to intelligently coordinate 8 advanced security scanning tools.

Unlike traditional security scanners, CyberSentry reasons about findings, adapts its approach based on results, and generates professional bug-bounty style security reports with actionable recommendations.

Key Innovation

  • Autonomous Decision-Making: Uses Llama 3.1 70B to reason about security findings and adjust scanning strategy
  • Real-time Terminal Visualization: Live xterm windows with hacker-themed green-on-black UI
  • 8 Integrated Security Tools: Robots/Sitemap, Tech Detection, HTTP Headers, SSL Analysis, Cookie Audit, Directory Fuzzing, CORS Testing, Nmap Scanning
  • Professional Reporting: Generates industry-standard security audit reports with CVSS-style severity ratings

โœจ Features

FeatureDescription
๐Ÿค– AI-Powered ReasoningLlama 3.1 70B makes autonomous decisions about which tools to run and how to interpret results
๐Ÿ”„ ReAct LoopImplements Think โ†’ Act โ†’ Observe โ†’ Reason cycle for intelligent tool orchestration
๐ŸŽฏ 8 Security ToolsRobots/Sitemap Recon, Tech Stack Detection, HTTP Header Analysis, SSL Certificate Checking, Cookie Auditing, Directory Fuzzing, CORS Analysis, Nmap Port Scanning
๐Ÿ“Š Real-time UIRich terminal interface with color-coded severity indicators and live progress
๐Ÿ“ˆ Professional ReportsGenerates markdown security reports with findings, severity levels, and remediation steps
๐Ÿ›ก๏ธ Ethical FocusBuilt with explicit ethical guidelines and requires authorized target specification
โšก Efficient ScanningIntelligent tool coordination reduces scanning time vs. running all tools sequentially
๐Ÿ”’ Secure Credential ManagementUses environment variables for API key management

๐ŸŽฏ Architecture

โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚                    User Input (Target URL)                   โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
                     โ”‚
                     โ–ผ
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚           ReAct Agent Loop (Autonomous)                      โ”‚
โ”‚  โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”   โ”‚
โ”‚  โ”‚ 1๏ธโƒฃ  THINK: LLM analyzes target & plans tools        โ”‚   โ”‚
โ”‚  โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค   โ”‚
โ”‚  โ”‚ 2๏ธโƒฃ  ACT: Execute planned security tools             โ”‚   โ”‚
โ”‚  โ”‚    โ”œโ”€ Robots/Sitemap Parser                          โ”‚   โ”‚
โ”‚  โ”‚    โ”œโ”€ Tech Stack Detector (Wappalyzer)              โ”‚   โ”‚
โ”‚  โ”‚    โ”œโ”€ HTTP Header Analyzer                           โ”‚   โ”‚
โ”‚  โ”‚    โ”œโ”€ SSL Certificate Checker                        โ”‚   โ”‚
โ”‚  โ”‚    โ”œโ”€ Cookie Auditor                                 โ”‚   โ”‚
โ”‚  โ”‚    โ”œโ”€ Directory Fuzzer                               โ”‚   โ”‚
โ”‚  โ”‚    โ”œโ”€ CORS Policy Tester                             โ”‚   โ”‚
โ”‚  โ”‚    โ””โ”€ Nmap Port Scanner                              โ”‚   โ”‚
โ”‚  โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค   โ”‚
โ”‚  โ”‚ 3๏ธโƒฃ  OBSERVE: Collect tool outputs & results         โ”‚   โ”‚
โ”‚  โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค   โ”‚
โ”‚  โ”‚ 4๏ธโƒฃ  REASON: LLM interprets findings & decides next  โ”‚   โ”‚
โ”‚  โ”‚    โ”œโ”€ Run more focused scans?                        โ”‚   โ”‚
โ”‚  โ”‚    โ”œโ”€ Deep dive on vulnerabilities?                 โ”‚   โ”‚
โ”‚  โ”‚    โ””โ”€ Generate final report?                         โ”‚   โ”‚
โ”‚  โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜   โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
                     โ”‚
                     โ–ผ
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚        Professional Security Audit Report (Markdown)         โ”‚
โ”‚  โ”œโ”€ Findings by Severity (Critical/High/Medium/Low)         โ”‚
โ”‚  โ”œโ”€ CVSS Scores & Risk Assessment                           โ”‚
โ”‚  โ”œโ”€ Remediation Recommendations                             โ”‚
โ”‚  โ””โ”€ Executive Summary                                        โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜

For detailed architecture documentation, see docs/ARCHITECTURE.md


๐Ÿ› ๏ธ Tech Stack

ComponentTechnology
LanguagePython 3.13
LLM EngineNVIDIA NIM (Llama 3.1 70B)
Agent PatternReAct (Reasoning + Acting)
Terminal UIRich Python library
Network ToolsNmap, requests, ssl, socket, subprocess
Security ToolsRobots parser, sslyze, requests_toolbelt
EnvironmentKali Linux / WSL2 Ubuntu
API IntegrationOpenAI-compatible NVIDIA NIM API

๐Ÿ“ฆ Installation

Prerequisites

  • Python 3.13+
  • pip (Python package manager)
  • NVIDIA NIM API Key (Get free access)
  • Nmap (for port scanning)
  • Kali Linux or WSL2 Ubuntu (recommended for full tool support)

Step 1: Clone Repository

git clone https://github.com/prutxvi/cybersentry.git
cd cybersentry

Step 2: Create Virtual Environment

# On Kali Linux / Ubuntu
python3 -m venv venv
source venv/bin/activate

# On Windows (WSL2)
python -m venv venv
source venv/Scripts/activate

Step 3: Install Dependencies

pip install -r requirements.txt

Required packages:

  • openai - NVIDIA NIM API client
  • python-dotenv - Environment variable management
  • rich - Beautiful terminal UI
  • requests - HTTP requests
  • scapy - Network packet manipulation

Step 4: Configure Environment Variables

# Copy example configuration
cp .env.example .env

# Edit .env with your NVIDIA API key
nano .env

Add your NVIDIA NIM API key:

NVIDIA_API_KEY=nvapi-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
TARGET_URL=https://your-own-website.com

Step 5: Install System Dependencies

On Kali Linux:

sudo apt update
sudo apt install nmap xterm -y

On WSL2 Ubuntu:

sudo apt update
sudo apt install nmap xterm -y

๐Ÿš€ Usage

Basic Usage

# Activate virtual environment
source venv/bin/activate

# Run security audit on configured target
python agent.py

# Expected output:
#   โœ“ Tool 1/8: Robots.txt & Sitemap Analysis
#   โœ“ Tool 2/8: Tech Stack Detection
#   โœ“ Tool 3/8: HTTP Header Analysis
#   โœ“ Tool 4/8: SSL Certificate Check
#   โœ“ Tool 5/8: Cookie Audit
#   โœ“ Tool 6/8: Directory Fuzzing
#   โœ“ Tool 7/8: CORS Testing
#   โœ“ Tool 8/8: Nmap Port Scan
#
#   ๐Ÿ“„ Report saved to: report_20260503_021648.md

Interactive Mode

The agent will:

  1. Display its reasoning in the terminal as it decides which tools to run
  2. Show real-time tool execution in xterm windows with live output
  3. Ask follow-up questions about findings that need deeper investigation
  4. Summarize results after all tools complete
  5. Generate professional report with findings and recommendations

Output Files

report_YYYYMMDD_HHMMSS.md  โ† Professional security audit report

The report includes:

  • Executive summary
  • Findings grouped by severity
  • Technical details of each vulnerability
  • CVSS scores (where applicable)
  • Remediation recommendations
  • Scan metadata (tool versions, timestamp, scope)

๐Ÿ” Real Findings

Scan Target: example.com (May 2, 2026)

This is a real security audit performed on the developer's portfolio website. Note: Scan was authorized by the domain owner.

FindingSeverityCVSSStatus
Missing Content-Security-Policy HeaderMedium5.3โš ๏ธ Unpatched
Server Header Reveals Vercel PlatformLow2.7โ„น๏ธ Info
SSL Certificate Expires June 2, 2026Medium5.9โš ๏ธ 30 Days
WordPress Paths Detected (403 Errors)Low3.1โ„น๏ธ Hardened
Missing X-Content-Type-Options HeaderLow2.7โš ๏ธ Unpatched

Detailed Findings

[1] Missing Content-Security-Policy (CSP) Header (Medium Severity)

  • Risk: Without CSP, the site is vulnerable to XSS (Cross-Site Scripting) attacks
  • Finding: Response headers lack Content-Security-Policy directive
  • CVSS v3.1: 5.3 (Medium)
  • Recommendation: Implement CSP header with strict directives
    Content-Security-Policy: default-src 'self'; script-src 'self' 'unsafe-inline'; style-src 'self' 'unsafe-inline'
    

[2] Server Header Reveals Technology Stack (Low Severity)

  • Risk: Attackers learn site runs on Vercel, enabling targeted attacks
  • Finding: Server: Vercel header exposed in HTTP response
  • CVSS v3.1: 2.7 (Low)
  • Recommendation: Remove or obfuscate server header
    # In Vercel vercel.json
    "headers": [
      {
        "source": "/(.*)",
        "headers": [
          {
            "key": "Server",
            "value": "Web Server"
          }
        ]
      }
    ]
    

[3] SSL Certificate Expires Soon (Medium Severity)

  • Risk: Service interruption, potential MITM attacks during renewal
  • Finding: Certificate valid until June 2, 2026 (30 days remaining)
  • CVSS v3.1: 5.9 (Medium)
  • Recommendation: Renew certificate immediately (auto-renewal via Vercel)

[4] WordPress Paths Detected (Low Severity)

  • Risk: Potential information disclosure; 403 responses leak existence of WP paths
  • Finding: Paths detected: /wp-admin, /wp-includes, /wp-content (all return 403)
  • CVSS v3.1: 3.1 (Low)
  • Recommendation: These are hardened and return 403, which is good. No action needed.

[5] Missing X-Content-Type-Options Header (Low Severity)

  • Risk: MIME-type sniffing attacks
  • Finding: X-Content-Type-Options: nosniff header not present
  • Recommendation: Add header to prevent MIME-sniffing
    X-Content-Type-Options: nosniff
    

Scan Statistics

  • Scan Date: May 2, 2026
  • Total Tools Run: 8/8 โœ…
  • Findings Discovered: 5
  • Critical Issues: 0
  • High Issues: 0
  • Medium Issues: 2
  • Low Issues: 3
  • Scan Duration: ~45 seconds

For complete findings details, see docs/FINDINGS.md


๐Ÿ—บ๏ธ Roadmap

โœ… Completed (v1.0)

  • Core ReAct agent implementation
  • 8 security tools integrated
  • Real-time terminal UI with Rich library
  • Professional report generation
  • NVIDIA NIM API integration
  • Environment configuration system
  • Ethical guidelines framework

๐Ÿ”„ In Development (v1.1)

  • Multi-target batch scanning
  • Persistent finding database
  • Trend analysis and historical comparisons
  • Slack/Discord notifications
  • CI/CD integration support
  • Extended tool set (15+ tools)

๐Ÿš€ Planned (v2.0)

  • Web dashboard for report visualization
  • SQLite database for finding history
  • Machine learning-based vulnerability prioritization
  • Integration with bug bounty platforms (HackerOne API)
  • Docker containerization
  • Multi-LLM support (Claude, GPT-4, etc.)
  • Advanced exploitation module (with proper safeguards)

๐Ÿ‘จโ€๐Ÿ’ป About the Developer

Pruthvi Raj

  • ๐Ÿ“ Location: NIAT Aurora, Bhuvanagiri, Telangana, India
  • ๐ŸŽ“ Education: B.Tech 1st Year (2025-2029)
  • ๐Ÿ” Focus: Cybersecurity, AI, Ethical Hacking
  • ๐Ÿ™ GitHub: github.com/prutxvi
  • ๐Ÿ“ง Email: pruthviraj73962@gmail.com

Motivation

CyberSentry was created as part of a mission to democratize security auditing tools and demonstrate the power of combining AI reasoning with traditional security scanning. This project showcases how autonomous agents can make intelligent decisions about security testing strategies.

Vision

To develop tools that empower ethical hackers, security professionals, and organizations to assess and improve their security posture, while maintaining the highest standards of responsible disclosure and ethical conduct.


โš–๏ธ Legal & Ethical Disclaimer

IMPORTANT: READ BEFORE USE

Authorization Requirements

CyberSentry is designed ONLY for authorized security testing. You MUST have explicit written permission from the website owner before running any scans.

Unauthorized access to computer systems is illegal. Violations of the Computer Fraud and Abuse Act (CFAA) and similar laws worldwide can result in criminal charges.

Acceptable Use

โœ… DO:

  • Test only systems you own or have explicit written authorization to test
  • Use for educational purposes on authorized test environments
  • Participate in legitimate bug bounty programs
  • Help organizations identify and fix security issues
  • Responsibly disclose all findings to affected parties

โŒ DON'T:

  • Scan systems without authorization
  • Attempt to cause harm or disruption
  • Exploit vulnerabilities maliciously
  • Violate privacy laws (GDPR, CCPA, etc.)
  • Share or sell findings without consent

Disclaimer

The creators of CyberSentry assume no liability for misuse or damage caused by this tool. Users are solely responsible for complying with applicable laws and regulations. By using this tool, you agree to use it ethically and legally.

For complete ethical guidelines, see DISCLAIMER.md


๐Ÿ“„ License

This project is licensed under the MIT License - see the LICENSE file for details.

Copyright ยฉ 2026 Pruthvi Raj

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions...


๐Ÿค Contributing

Contributions are welcome! Please note that this project is designed for ethical security testing. Any contributions should maintain the ethical standards outlined in DISCLAIMER.md.

If you find a bug or have a feature suggestion, please open an issue on GitHub.


๐Ÿ“š Additional Resources


๐Ÿ“ž Support

For issues, questions, or suggestions:

  1. Check docs/ARCHITECTURE.md for technical details
  2. Review docs/FINDINGS.md for example output
  3. Open an issue on GitHub
  4. Contact the developer at your.email@example.com

Built for cybersecurity education and ethical hacking

Last Updated: May 3, 2026

ๅธธ่ง้—ฎ้ข˜

What is cybersentry?โŒ„

cybersentry is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by prutxvi. ๐Ÿค– Autonomous AI-powered ethical hacking agent powered by Llama 3.1 70B on NVIDIA NIM. It has 106 GitHub stars.

Is cybersentry safe to use?โŒ„

Yes. cybersentry passed SkillsLLM's automated security scan โ€” a dependency vulnerability audit plus prompt-injection heuristics โ€” with no high-severity issues. You can read the full report in the Security Report section on this page.

How do I install cybersentry?โŒ„

Clone the repository with "git clone https://github.com/prutxvi/cybersentry" and add it to your Claude Code skills directory (see the Installation section above).

What programming language is cybersentry written in?โŒ„

cybersentry is primarily written in Python. It is open-source under prutxvi on GitHub, so you can review or fork the full source.

Are there alternatives to cybersentry?โŒ„

Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh cybersentry against similar tools.

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