DVR Scanner & Fingerprinter (Brand Specific)

Fast, multi-threaded scanner that fingerprints surveillance web interfaces (DVR/NVR) and security-related IoT devices.

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    ║                         DVR Scanner & Fingerprinter                           ║
    ║                         v2.0 - dev@sinners.cty                                ║
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                     🔍 Scanning for DVR Devices

                     💡 Press Ctrl+C to save and exit gracefully

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Starting DVR Scanner on ips.txt with 10 threads...
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✓ [1/1000] 192.168.1.1 - Status: 200 (not DVR)
✗ [2/1000] 192.168.1.2 - Connection refused
🎯 [3/1000] DVR FOUND: 192.168.1.100 | Status: 200 | Type: Hikvision
🎯 [4/1000] DVR FOUND: 10.0.0.55 | Status: 200 | Type: Generic Login (Context: Login page with 'stream')
...
💾 Auto-saved 10 DVR results
...

Features

• 🚀 Concurrent scanning using ThreadPoolExecutor with configurable thread count.
• 🛡️ Graceful shutdown on SIGINT/SIGTERM (Ctrl+C): saves progress, stops workers cleanly.
• 🎯 Brand-specific detection via strict signatures (Hikvision, Dahua, Uniview, Axis, Hanwha/Wisenet, Avigilon, Mobotix, XMEye, TVT, Amcrest, Foscam, Reolink, DrayTek, MikroTik, Ubiquiti, Synology, etc.).
• 🏷️ Evidence-rich results: detection method, signatures matched, headers, titles, server info.
• 🧠 Robust content decoding: tries multiple encodings with safe fallback.
• 📝 Auto-saving JSON + IP list every N detections; empty files created if none found.
• 🚫 Noise reduction: skips processing 400/404 responses; tracks HTTP error count.
• 📊 Scan summary: totals for scanned, skipped errors, failures, DVRs found.
• ⚙️ Configurable input file, threads, verbosity flag, save interval, output paths.

Getting Started

Prerequisites

• Python 3
• requests, urllib3

Installation

pip install requests urllib3

Prepare targets

Create an ips.txt file (default) with one IP per line:

192.0.2.10
198.51.100.23
203.0.113.42

Usage

python scanner.py \
  --input ips.txt \
  --threads 10 \
  --save-interval 10 \
  --output dvr_scan_results.json

Flags:

• -i, --input — path to IP list file (default: ips.txt)
• -t, --threads — max worker threads (default: 10)
• -v, --verbose — verbose logging (flag)
• --save-interval — auto-save every N DVR detections (default: 10)
• -o, --output — JSON output path (default: dvr_scan_results.json)
  • The IP list is also saved as <output>_ips.txt.

What it does

1. Reads IPs from the input file.
2. Sends HTTP GET to http://<ip>:80 with common browser headers.
3. Skips 400/404 responses (counts them separately).
4. Decodes content robustly; extracts key headers.
5. Applies strict brand signatures (headers + body + <title> fallback for DVR terms).
6. Saves detections (JSON + IP list), with auto-save every N hits.
7. On Ctrl+C, saves progress and exits cleanly.

Outputs

• JSON (default: dvr_scan_results.json): rich per-hit metadata
  • ip, status_code, important_headers, page_title, page_content (truncated), dvr_type, detection_method, detection_signatures, scan_timestamp, url, optional server_info
• TXT (default: dvr_scan_results_ips.txt): list of detected DVR IPs

Detection logic (strict)

• Brand patterns for major DVR/NVR/IoT vendors (headers + body).
• Title-based fallback only for explicit DVR/NVR/camera phrases (e.g., “network video recorder”, “embedded net dvr”).
• Generic password/login heuristics are intentionally removed to reduce false positives.

Operational tips

• Start with a modest thread count to avoid overloading networks.
• Ensure you’re authorized to scan the target IP ranges.
• Increase --save-interval for fewer writes; decrease for safer incremental checkpoints.

Safety & legal

Only scan hosts and networks you are authorized to test. Unauthorized scanning may violate law or terms of service.

Quick example

python scanner.py -i ips.txt -t 20 --save-interval 5 -o results.json

Project structure (suggested)

scanner.py        # contains FingerPrinter and CLI
ips.txt           # input IP list (one per line)
dvr_scan_results.json      # JSON detections (output)
dvr_scan_results_ips.txt   # IPs only (output)

👤 Author

@Syn2Much

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