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

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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

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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

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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

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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

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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

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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

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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

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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"

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Building from Source

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

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Dependencies

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

go mod download

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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}

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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.

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Contributing

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

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Support

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

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