CamTRON - Camera Scanner

An automated tool for detecting surveillance devices(cameras) on networks.

Features

• Multi-brand detection: Supports 30+ camera brands including Hikvision, Dahua, Axis, CCTV, and more
• High-performance scanning: Concurrent scanning with configurable thread count
• Flexible input: Scan single IPs, URLs, CIDR ranges, or files with target lists
• Smart detection: Uses multiple detection methods (titles, headers, favicon MD5 hashes, body content)
• CSV export: Option to save results to CSV file
• Real-time progress: Live progress display with color-coded output
• Resilient: Handles network timeouts and malformed responses gracefully

Installation

Prerequisites

• Go 1.16 or higher

From Source

git clone https://github.com/K3ysTr0K3R/camtron.git
cd camtron
go build -o camtron main.go

Quick Install

go install github.com/K3ysTr0K3R/camtron@latest

Usage

Basic Scanning Tutorials

Scan a Single URL

./camtron -u http://192.168.1.1

Scan a Single IP

./camtron -ip 192.168.1.100

Scan a CIDR Range

./camtron -ip 192.168.1.0/24

Scan Targets From a File

./camtron -f targets.txt

Increase Thread Count (Default: 50)

./camtron -f targets.txt -t 100

Save Results to CSV

./camtron -f targets.txt -o results.csv

Append Results to Existing CSV

./camtron -f targets.txt -o results.csv -append

Command Line Options

-u string      Scan a single URL
-ip string     Scan a single IP/CIDR
-f string      File with targets (one per line)
-t int         Threads (default: 50)
-o string      Output CSV file (optional)
-append        Append to output CSV instead of overwrite

Input File Format

Create a text file with one target per line:

192.168.1.1
192.168.1.100
10.0.0.0/24
http://example.com

Supported Brands

• Avtech — Login pages and favicon detection
• Axis — Favicon MD5 detection
• CCTV — Multiple detection methods
• Dahua — Multiple patterns and favicon detection
• D-Link DCS — Header-based detection
• DVR — Login page detection
• Geovision — Title-based detection
• Hikvision — Comprehensive detection (headers, titles, body content)
• Instar — Title-based detection
• IP Camera — Header-based detection
• Netwave — Header-based detection
• Nuuo — Title-based detection
• Reecam — Header-based detection
• Tenda — Multiple login page variants
• Uniview — Favicon and logo detection
• Xiongmai — Title-based detection

Detection Methods

CamTRON uses multiple detection techniques:

• Title Matching: Checks HTML <title> for brand signatures
• Header Analysis: Examines HTTP response headers for identifiers
• Body Content: Searches HTML body for known strings
• Favicon Hashing: MD5 hashing of favicon.ico
• Status Codes: Detects specific HTTP response patterns

Performance

• Default threads: 50 concurrent scans
• Timeouts: 2-second timeout per request
• Connection pooling: Reuses HTTP connections
• DNS caching: Reduces repeated DNS lookups
• Progress tracking: Real-time scan statistics

Output

Console Output

[15:04:05.123] [+] 192.168.1.100 : hikvision, dahua
[15:04:05.456] [+] 192.168.1.101 : axis

CSV Output

Target,Brands
192.168.1.100,"hikvision, dahua"
192.168.1.101,"axis"

Building from Source

git clone https://github.com/yourusername/camtron.git
cd camtron
go build -o camtron .
go build -ldflags="-s -w" -o camtron .

Dependencies

• Go standard library
• golang.org/x/net/html

go mod download

Development

Adding New Rules

Add rules to the rules slice in main.go:

{"brandname", "/path", "condition=value", "", false}

Supported Conditions

• title= — HTML title matching
• body= — HTML body matching
• headers= — HTTP headers matching
• md5= — Favicon MD5 matching
• status_code= — HTTP status code matching

Multiple Conditions

{"brand", "/", "title=Login&&body=Camera System", "", false}

Legal Disclaimer

This tool is intended for:

• Security professionals testing their own networks
• Authorized penetration testing engagements
• Educational purposes

WARNING: Unauthorized scanning of networks you do not own or have permission to test is illegal. Always obtain proper authorization. The developers assume no responsibility for misuse or damage.

Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push the branch
5. Open a Pull Request

Support

• Check the Issues page
• Open a new issue with detailed information

Note: This tool is for legitimate security assessment purposes only.