bishopfox/sliver

Adversary Emulation Framework

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Summary Information

Updated 59 minutes ago
Added to GitGenius on September 5th, 2026
Created on January 17th, 2019
Open Issues & Pull Requests: 226 (+0)
GitHub issues: Enabled
Number of forks: 1,583
Total Stargazers: 11,791 (+0)
Total Subscribers: 162 (+0)

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Detailed Description

Sliver is an open source adversary emulation framework that enables red team engagements and security testing through dynamically compiled implants with command-and-control capabilities.

The tool addresses the need for realistic security testing by providing implants that communicate with a central server over multiple transport protocols including mutual TLS, WireGuard, HTTP(S), and DNS. Each implant is compiled with unique asymmetric encryption keys and includes compile-time obfuscation. The framework supports both staged and stageless payload delivery, procedurally generated HTTPS C2 channels, and DNS canaries for blue team detection testing. Implants can perform Windows-specific operations such as process migration, process injection, and user token manipulation, as well as execute .NET assemblies and COFF/BOF loaders in memory.

Organizations conducting authorized security assessments should consider Sliver if they need cross-platform implant deployment across Windows, macOS, and Linux targets. The framework suits teams that require multiplayer collaboration during engagements and benefit from Python scripting capabilities for automation. The tool's support for multiple C2 transport methods and its integration with Let's Encrypt for certificate management make it suitable for realistic adversary simulation across varied network conditions. The README does not compare Sliver to alternative frameworks.

The project maintains active engagement with users through GitHub discussions and comprehensive documentation. Development activity shows consistent attention to feature expansion, with recent additions spanning multiple capability areas from transport encryption options to in-memory code execution techniques. The codebase demonstrates ongoing refinement of core functionality rather than focusing narrowly on a single capability area.