Awesome GitHub RepositoriesMemory Access Tracing

MAME is a vintage hardware emulation platform designed to recreate the circuitry of arcade games, computers, and consoles to run original software on modern devices. It functions as a retro gaming preservation framework for managing, verifying, and archiving ROM sets and disk images to ensure long-term software accessibility. The project features a system debugging tool for inspecting emulated memory, CPU registers, and execution flow via breakpoints and disassembly. It also includes a Lua-based automation layer that exposes core system state and hardware controls for custom behavior and anal

Qira is a runtime analysis tool and interactive binary debugger designed for the QEMU emulator. It functions as a binary execution tracer that records a full timeline of instruction invocations and provides a system for monitoring memory operations within guest processes. The project enables the analysis of compiled binaries by tracing instruction-level execution and mapping raw memory addresses to user-defined annotations. It includes capabilities for state-snapshotting to manage execution forks, allowing the navigation of divergent logic paths and the inspection of CPU register states and s

PINCE is a dynamic debugger, instruction tracer, and memory scanner designed for the analysis and manipulation of running processes. It functions as a process memory manipulator and editor, allowing for the identification, modification, and monitoring of values within a target application's active memory. The tool distinguishes itself through memory pointer analysis, tracing addresses and offsets to locate static pointers that lead to dynamic data across different sessions. It also enables the execution of internal functions within a running process by manipulating the instruction pointer and

Memary is a memory-augmented agent framework that stores and retrieves contextual information from a knowledge graph to personalize responses and maintain long-term memory across interactions. It automatically captures all agent interactions and stores them as structured memories without requiring explicit instrumentation, then injects top-ranked user entities and themes into the active context window to tailor agent responses dynamically. The framework distinguishes itself through a multi-retriever memory search that combines COLBERT reranking with recursive graph queries across databases, e