I build web scrapers and data extractors the way I audit systems: assuming requirements are stricter than they look — and making correctness structural, not aspirational.

🚫 Privacy by design No personal data. Actors use fixed output allowlists, preventing unexpected personal fields from reaching your dataset even when a source changes. Where appropriate, this is covered by automated tests.

🤖 robots.txt enforced in code Disallowed paths are refused before requests are made — including paths supplied through Actor input.

🔓 Logged-out sources only No account-gated scraping, private credentials, or borrowed sessions.

💸 Pay for useful results Pages that produce no usable data are skipped, keeping runs focused on actual results.

🪶 Cheap by design When structured data can be retrieved directly, I use HTTP instead of a browser. Browser automation is reserved for sites that actually require it.

Cybersecurity engineer and researcher with experience in vulnerability management, security auditing, incident response, web application security, and automated security testing.

Qualys-certified across vulnerability detection & response, patch management, cybersecurity asset management, and web application scanning. Also Google Cybersecurity Professional Certificate certified.

My research focuses on machine learning for automated security testing and anomaly detection — which is why reliability and schema drift matter in my data tools too.

Python · JavaScript · TypeScript · Node.js · Crawlee · Playwright · Qualys · Burp Suite · OWASP ZAP · Nmap · Wazuh · Splunk · Linux

Looking for a source that isn't here, a custom schema, or a scraper optimized for cost and reliability?

Open an issue and tell me what you need. I'll give you an honest assessment of whether it's worth building.