🔍 MM PS5 API Mapper v0.8 — Resource Chain Correlation Graph

🔍 MM PS5 API Mapper v0.8

Map the observable PS5 surface once. Reuse the evidence everywhere.

v0.8 — Resource Chain Correlation Graph turns MM PS5 API Mapper into a broader evidence-driven mapping framework for PS5 research and homebrew development.

It collects, normalizes and correlates what a payload can safely observe at runtime, then exports that information into structured datasets for offline analysis and reuse.

---

🧠 What this release maps

Surface	What it can capture / correlate
📁 Filesystem & ELF/SELF	Observable paths, executables, program metadata, dynamic tables, symbols, imports/exports, relocations and provider relationships
⚙️ Processes & runtime	Processes, PIDs, threads, loaded modules, runtime library structures and process-to-module relationships
🧩 Virtual memory	VM spaces, VM regions and module ↔ VM relationships
🔌 File descriptors	FD tables, occupied descriptors and descriptor → resource anchors
🧱 Resource objects	Bounded raw observations, aligned pointer candidates, repeated resource fingerprints and graph relationships
🎮 /dev & hardware surface	Observable device nodes, bus devices, drivers, driver methods and softc/resource anchors
🔗 Correlation graph	Exact pointer joins, candidate relationships, process → FD → resource paths and bus → device → driver paths
🧬 APIs / NIDs	Static/runtime symbol evidence enriched offline with PS5 Payload SDK, headers, stubs and NID metadata

---

🚀 Built for developers

MM PS5 API Mapper is not just a one-shot dump payload. It is intended as a reusable research layer for PS5 tools, payloads, diagnostics, compatibility systems, visualizers and other homebrew projects.

Mapper output can help developers:

• discover visible libraries, modules and APIs;
• resolve NIDs against available SDK/header metadata;
• understand process, thread and VM topology;
• inspect descriptor/resource relationships without inventing undocumented structure layouts;
• correlate /dev, bus, device and driver surfaces;
• compare captures and identify stable vs changing relationships;
• build firmware-by-firmware datasets separately from the clean source tree;
• reuse one structured evidence database instead of repeating the same discovery work project after project.

---

🧭 Evidence-first design

The mapper intentionally separates:

• ✅ Observed — directly captured evidence
• 🔗 Exactly correlated — independently captured values that match exactly
• 🟡 Candidate — useful relationships that still require confirmation
• 🧱 Unknown / raw — preserved without invented semantic labels
• ⚠️ Coverage gap / observable limit — explicitly reported instead of hidden

Unknown fields stay unknown. Candidate pointers are not automatically dereferenced. Discovered APIs are not automatically executed. Presence does not imply permission.

---

📦 Official public v0.8 ELF

The official prebuilt is publicly available directly from this GitHub Release.

Payload: mm_ps5_api_mapper_v0.8_resource_chain_correlation_graph.elf

Size: 184,584 bytes

SHA-256

2adb6cd3967ec25b5bb93021506cd0360ae254b709d43e66a6b496315fd15a18

A matching .sha256 file is attached beside the ELF.

Firmware-specific captures, local addresses and hardware test datasets are simply kept separate from the clean source repository. The official ELF itself is public.

---

🛠️ Project stack

• PS5 Payload SDK build target
• C mapper/runtime implementation
• JSONL primary evidence capture
• Python offline resolver and comparison tools
• SDK/header/NID enrichment pipeline
• Host-side regression validation
• GPL-3.0-or-later

---

MM PS5 API Mapper

Research the surface. Preserve the evidence. Build on the map.