A security toolkit for attacking dynamic routing and first-hop redundancy protocols using weaponized virtual routers.
Routopsy is a security toolkit built specifically for attacking dynamic routing protocols and first-hop redundancy protocols in network infrastructure. It enables security professionals to test the resilience of critical networking components by simulating realistic attacks using weaponized virtual router instances rather than protocol reimplementations.
Network security researchers, penetration testers, red team members, and infrastructure security professionals who need to assess the security of routing and redundancy protocols in enterprise networks.
Routopsy provides a unique approach by containerizing actual router implementations for attack simulations, offering more realistic testing scenarios than protocol-specific tools while maintaining extensibility for custom attack development.
Routopsy - Hacking Routers with Routers
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Uses weaponized virtual router instances via containers, providing more authentic testing scenarios than protocol reimplementations, as highlighted in the README's focus on practical network security.
Supports attacks against both Dynamic Routing Protocols (DRP) and First-Hop Redundancy Protocols (FHRP) including OSPF, BGP, HSRP, and VRRP in a single toolkit, as stated in the key features.
Allows for additional attacks to be implemented in Python3 or by adding custom containers, enabling flexibility for security researchers, as mentioned in the README's extensibility note.
Relies on Docker and network configuration for virtual routers, which can be barrier for users without container or advanced networking skills, adding overhead to deployment.
The main README lacks detailed usage instructions, directing users to a separate wiki that may be sparse or not regularly maintained, as indicated by the referral to the wiki for further information.
Specialized solely for routing and redundancy protocol attacks, making it ineffective for general security assessments or other network layers, which restricts its audience to experts.