A framework for analyzing and defending against supply chain attacks targeting Software Development Lifecycle infrastructure.
SITF (SDLC Infrastructure Threat Framework) is an open-source security framework for analyzing and defending against attacks targeting Software Development Lifecycle infrastructure. It helps security teams visualize attack stages across components like endpoints, version control, CI/CD, registries, and production, mapping each technique to enabling risks and appropriate security controls. The framework provides both interactive tools and AI automation to model supply chain attacks and improve defensive strategies.
Incident response teams, security architects, threat intelligence analysts, and security engineers focused on protecting software supply chains, particularly in organizations that produce software or open-source components.
Developers choose SITF for its structured, visual approach to supply chain threat modeling, combined with AI-powered automation that simplifies attack flow creation. Its unique value lies in bridging the gap between theoretical frameworks and practical incident analysis with real-world case studies and interactive tools.
A comprehensive framework for analyzing and defending against attacks targeting Software Development Life Cycle Infrastructure.
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The drag-and-drop flow builder allows security teams to visually map attack stages across SDLC components, making complex threats easier to understand and communicate, as demonstrated in the online visualizer demo.
Claude AI skills automate attack flow generation and technique proposals from incident reports, saving significant manual effort, as detailed in the Claude skills documentation.
Includes 75+ pre-mapped attack techniques with risks, controls, and framework mappings like OWASP SPVS, providing a solid foundation for analysis without starting from scratch.
Case studies of breaches like CircleCI and SolarWinds demonstrate practical application and enhance learning, making the framework credible and actionable for incident response.
Core automation features require access to Claude AI, which may not be available to all users and introduces vendor lock-in, limiting flexibility for teams using other AI tools.
Adding or modifying techniques involves editing JSON files and running Python scripts, which can be error-prone and less intuitive for non-developers, as noted in the contributing guide.
The framework is standalone with its own visualizer and tools, lacking built-in integrations for common security platforms or CI/CD systems, which may complicate workflow incorporation.