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Basic Information

Viper is an adversary simulation and red teaming platform that leverages AI to model and execute attacker behaviors. The repository is intended to provide a foundation for running simulated adversary campaigns, automating red team activities, and exercising defensive controls in realistic scenarios. It is aimed at security practitioners who need to evaluate detection and response capabilities, reproduce threat behaviors, and validate security controls under controlled conditions. The project combines orchestration of simulated attacks with AI-driven behavior generation to help teams plan, run, and iterate on assessments while reducing manual effort required to create complex scenarios.

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App Details

Features
The project centers on AI-driven adversary simulation and red teaming orchestration. It emphasizes automated generation of attack scenarios, execution of simulated campaigns, and modeling of adversarial behaviors. The platform is described as extensible so teams can integrate custom scenarios and tooling. It targets coordination of assessments and supports workflows for running repeatable simulations. Documentation and a repository structure indicate it is intended to be used as a platform rather than a single-purpose script. Overall the feature set focuses on simulation, automation, scenario management, and extensibility for security testing teams.
Use Cases
Viper helps security teams test and harden defenses by providing a reproducible environment for adversary emulation and red team exercises. It enables organizations to validate detection rules, assess incident response processes, and prioritize remediation by surfacing gaps in controls through realistic simulations. By leveraging AI to model attacker behaviors, the platform can reduce the manual effort needed to craft diverse scenarios and scale assessments across environments. This supports training of blue teams, verification of monitoring and logging, and continuous improvement of security posture through repeatable, automated evaluations.

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