Autopentest-drl -

| Feature | Traditional Scanner (e.g., Nessus) | Attack Graph (e.g., MulVAL) | AutoPentest-DRL | | :--- | :--- | :--- | :--- | | | High | Medium (depends on data quality) | Low (learns from action outcomes) | | Sequence awareness | None (independent checks) | Yes (paths) | Yes (optimal sequences) | | Adaptability to network changes | None (re-run required) | None (new graph required) | High (re-plans online) | | Handles unknown vulnerabilities | No (signature-based) | No | Partially (transfer learning) | | Exploration vs exploitation | Only exploitation (fixed rules) | Only exploitation (static path) | Dynamic balance | | Resource efficiency | Poor (scans everything) | Good | Excellent (learns to probe likely targets first) |

In the long term (5+ years), we may see —where multiple agents share attack strategies without sharing sensitive network data, enabling a collective intelligence for autonomous security assessment. autopentest-drl

Deploy two DRL agents simultaneously: one for (scans) and one for exploitation (attacks) to speed up penetration testing on large-scale networks. Potential Next Steps | Feature | Traditional Scanner (e