Autopentest-drl New! 【TRUSTED × 2027】

: The environment contains virtual hosts with specific CVEs (Common Vulnerabilities and Exposures).

: The DRL agent explores potential vulnerabilities (states) and receives rewards for successful compromises, eventually optimizing its route. autopentest-drl

You cannot train a DRL agent on a live production network. Instead, researchers use high-fidelity emulators like or CybORG (from DARPA’s CASTLE challenge). These emulators provide: : The environment contains virtual hosts with specific

Multiple agents (red, green, blue) learning simultaneously in the same environment. Blue agents learn to patch, red agents learn to evade. This mirrors real cyber warfare and yields more robust defenses. This mirrors real cyber warfare and yields more

Users can run a "logical attack" using a sample network topology. In this mode, no actual exploits are launched. Instead, the DRL agent determines the optimal attack path based on the network's configuration, allowing researchers to study attack mechanisms without risk.

0.95 to balance short-term efficiency with long-term strategic goals.