- Significantly expanded Chapter 7 with detailed guides and code examples for AI red teaming lab setup.
- Introduced comprehensive sections on local LLM deployment, API-based testing, and network isolation.
- Added critical safety controls including kill switches, watchdog timers, rate limiting, and cost management.
- Included advanced topics such as testing RAG, agent systems, and multi-modal models.
- Provided pre-engagement and daily operational checklists, risk management, and incident response procedures.
- Implement automatic port scanning for LLM services if no port is provided.
- Discover available models from OpenAI-compatible and Ollama API endpoints.
- Enable the attack phase to test against multiple discovered models.
- Improve usability by reducing manual configuration for common LLM setups.
- Enhance test coverage by automatically validating against various models.
- remove empty os, sys, and typer files from the pit directory
- these files were likely created as placeholders during initial setup
- they serve no functional purpose and were never populated with content
- improves project hygiene by removing unused and redundant artifacts
- Introduce a new sequential pipeline architecture for automated scans.
- Update the scan command to utilize the new pipeline for auto mode.
- Integrate InjectionTester for actual discovery of injection points within the DiscoveryPhase.
- Implement real attack execution in the AttackPhase using InjectionTester and pattern registry.
- Enhance the VerificationPhase to process detailed TestResult objects with detection scoring.
- Completely rewrites SPECIFICATION.md to detail a new CLI architecture and user experience for PIT v2.0.0.
- Introduces a comprehensive command hierarchy, detailed terminal output mockups across 5 phases, and extensive options for pit scan.
- Focuses on a "premium TUI" design philosophy, "one-command" operation, zero-config defaults, and enhanced error handling.
- Adds sections for configuration, pattern, and history management, along with accessibility and performance specifications.
- Updates .gitignore to reflect the new documentation structure, moving legacy and new spec files into dedicated docs subdirectories.
- Add SPECIFICATION.md to the list of ignored files.
- Prevent tracking of a new project specification document.
- Ensure only relevant source files are committed to the repository.
- Add typer and rich to the prompt_injection_tester project dependencies.
- Introduce pit as a new command-line entry point in pyproject.toml.
- These dependencies are essential for developing the new pit command-line interface.
- Standardize import order across all modules in the tool.
- Introduce explicit type hints for variables and function return types to enhance code clarity.
- Remove unused imports to reduce code clutter and improve maintainability.
- Update .gitignore to exclude generated code review reports and coverage files.
- These changes improve code readability and facilitate static analysis.
- Convert all prompt and attack examples from plain text to YAML format.
- Enhance the readability and structure of complex jailbreak techniques.
- Provide clearer delineation of different parts within multi-step prompts.
- Implement URL scheme validation for LLM endpoint connections.
- Mitigate Server-Side Request Forgery (SSRF) by ensuring only 'http' and 'https' schemes are allowed.
- Sanitize report output paths to prevent directory traversal attacks.
- Ensure test reports are saved only within the current working directory.
- Update RAG pipeline documentation to use Mermaid for improved flow diagram rendering.
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