How to Build a Bug Bounty Automation Lab at Home for Under $100 (2026)

This article provides a practical guide to building a 24/7 automated reconnaissance system for bug bounty hunting using hardware costing under $100 and entirely open-source tools. The core problem it addresses is that successful bug bounty hunters gain competitive advantage by detecting new target scope additions—new subdomains, services, vulnerabilities—automatically while competitors sleep, allowing them to find and report issues hours or days before manual researchers. The article matters because it demonstrates that this advantage is achievable with minimal investment, showing exact hardware specifications, tool configurations, API key setup, and bash pipeline scripts that chain together subdomain discovery, HTTP probing, vulnerability scanning, and mobile notifications.

• Cost-advantage through continuous monitoringThe article establishes that successful hunters don't scan faster manually; instead, they run automated pipelines continuously. The example provided shows a new subdomain appearing at 2am, being discovered by 2:05am, scanned with Nuclei templates, and notified to the hunter's phone, enabling them to begin exploitation by 9am—hours before competitors who start manual reconnaissance at 9am. This continuous advantage compounds because every programme addition is caught within hours rather than days.
• Hardware choice determines cost structureTwo viable options are presented: a Raspberry Pi 5 (4GB model at ~$60 plus ~$24 in accessories for total ~$85-100) drawing less than 10W and costing ~$0.50/month in electricity, versus a VPS at $4-6/month ($50-70/year ongoing). The article specifies that the Raspberry Pi 5 runs all Go-based security tools natively on 64-bit ARM. For 2+ years of operation, the Pi breaks even; for convenience and remote access, the VPS wins. The hardware choice directly impacts whether the setup costs $85 once or $50-70 annually.
• ProjectDiscovery tool stack as backboneThe article identifies four core tools—Subfinder, Httpx, Nuclei, and Notify—as the complete pipeline, chosen because they are designed to work together with stdin/stdout chaining. Subfinder performs passive subdomain enumeration across 50+ sources without active scanning. Httpx filters discovered subdomains to identify live HTTP services with status codes and technology detection. Nuclei scans live hosts using community-maintained templates updated daily. Notify delivers findings to Slack or Telegram. The article includes exact installation commands via Go and demonstrates this stack processin
• API keys double discovery without costThe article specifies that Subfinder without API keys discovers ~24 subdomains using public sources only, but adding free-tier keys from Shodan, SecurityTrails, VirusTotal, Censys, and FullHunt increases this to ~51 subdomains—a 2× improvement. Critically, the article notes that none of these providers require a credit card for free tier access. However, it emphasizes that API rate limits are the constraint: SecurityTrails free tier allows limited queries per month, so hitting the limit is possible within a week if running daily scans against 20 targets. The recommendation is to automate 5-10
• Pipeline script chains tools via pipesThe article provides a complete bash script (run_pipeline.sh) demonstrating the exact data flow: Subfinder output pipes directly to Httpx, Httpx results pipe to Nuclei (extracting the URL field), Nuclei findings pipe to Notify. The script includes directory creation, date-stamped output files, and silent modes for clean output. Each stage filters data before passing to the next: Subfinder outputs subdomains, Httpx filters to live hosts with HTTP status codes and technology detection, Nuclei filters to medium/high/critical severity findings only, Notify sends only non-empty result sets. This de
• Continuous monitoring via cron and diffThe article describes using cron to run the pipeline daily (example: 0 2 * * * executes at 2am) and detecting attack surface changes using the `comm -23` command to compare today's subdomain list against yesterday's, identifying only new additions. This approach requires running the full pipeline on a schedule and maintaining timestamped output files. The article explicitly states this is the highest-value capability—not running scans faster, but catching new subdomains added to target scope within 24 hours of them going live, before other hunters discover them manually.
• Setup requires 2-3 hours end-to-endThe article specifies a 25-minute read time with 2-3 hours estimated for end-to-end build, including OS installation on the Raspberry Pi (using Raspberry Pi Imager, flashing 64-bit Lite OS, enabling SSH), installing Go 1.22 for ARM64, installing all four ProjectDiscovery tools via Go installation commands, creating the Subfinder API key config file, writing and testing the pipeline script, and configuring cron jobs. The article provides specific download URLs, installation paths, and verification commands (e.g., `go version`, `subfinder -version`) to confirm each stage is functional.
• Free-tier API constraints require strategic targetingThe article emphasizes in the exercise section that API rate limit checking is the most important step before building automation, as free-tier limits determine how many targets can be covered sustainably. SecurityTrails free tier is explicitly called out as having a monthly query limit that would be exceeded within the first week if running daily scans against 20 targets. The practical conclusion stated is to automate the 5-10 highest-value targets on free API tiers and only upgrade specific API keys when a target's complexity justifies the cost, rather than attempting to cover all targets wi

Bottom line: By combining a sub-$100 Raspberry Pi with free open-source ProjectDiscovery tools and strategically configured free-tier APIs, bug bounty hunters can deploy 24/7 automated reconnaissance that discovers new target scope—new subdomains, live services, and vulnerabilities—within hours of appearance, giving them a competitive first-mover advantage before manual researchers even start their workday. The key is not faster scanning, but continuous monitoring running while competitors sleep, paired with