data-scraper-agent

Automate CVE data collection by running an API-first extraction pipeline that fetches from NVD, Exploit-DB, MITRE, and GitHub advisories. The pipeline uses pluggable source adapters to collect, normalize, and deduplicate unstructured web data into structured records.

Aggregate threat intelligence feeds into structured JSON or CSV using an extraction pipeline with Extractor, Parser, Transformer, and Loader stages. It normalizes disparate sources, deduplicates entries, and outputs files for easy integration into existing security pipelines.

Yes, you can monitor vendor advisories with configurable rate limiting and caching. The scraper enforces ethical scraping guidelines while incrementally syncing security advisories to prevent duplicate records and avoid overwhelming source APIs.

Yes, the threat intel scraper supports incremental syncing with built-in caching for vulnerability research. This allows security teams to track newly published CVEs affecting assets, correlate findings with internal inventory, and generate actionable reports without rescanning entire databases.

Normalize unstructured security advisory data by applying the pipeline's Transformer stage to unify records from NVD, MITRE, and Exploit-DB. The system automatically handles data normalization and deduplication to consolidate disparate threat intel feeds into cohesive knowledge units.

Automated web scraping for threat intelligence is limited by enforced ethical scraping guidelines and configurable rate limits. Users must respect source API constraints and rely on pluggable adapters for supported sources like NVD, Exploit-DB, MITRE, and GitHub advisories rather than arbitrary web pages.