asset-discovery

Attack surface mapping identifies external and internal shadow assets through subdomain enumeration and exposure analysis. This skill automates asset discovery across your domains to reduce blind spots and guide defenses using structured reports.

Subdomain enumeration and CVE-aware risk assessment are handled by integrating the PD toolchain with cloud services. This approach discovers assets, evaluates exposures, and outputs results into assets.db and summary.json for traceability.

Yes, asset discovery relies on PD toolchain outputs from subfinder, dnsx, naabu, httpx, and tlsx. It processes these tool outputs to map exposure and store results in a local assets.db database with automated reporting.

EASM workflows are automated to map exposure and detect shadow assets, generating ready-to-review structured reports. Results are safely stored in assets.db and summary.json, ensuring traceability across internal and external surfaces.

Yes, dnspython and requests are required dependencies for executing subdomain enumeration and asset discovery tasks. These libraries handle DNS resolution and HTTP requests during the automated mapping of your attack surface.

Shadow asset detection focuses on data handled safely by the PD toolchain and MCP cloud integrations. Limitations arise if local toolchain outputs are incomplete, affecting the accuracy of exposure analysis and CVE-based risk assessment.