TRL9 SOVEREIGN INDUSTRIAL CAPABILITY ASYMMETRIC ADVANTAGE
Abstract
Technical Description: This dataset contains the codebase documentation, execution logs, and system manifests for "Project Sentinel," a Stage 9 Sovereign AI Node deployed directly onto an ARM64 mobile substrate (specifically, a Samsung Galaxy S22). The core operational logic runs via a Python script named sentinel_overseer.py, which terminal logs confirm is stable and protected. To achieve continuous uptime without operating system interference, the architecture employs an Out-Of-Memory (OOM) shielding technique by modifying the kernel-level priority to oom_score_adj-1000. The implemented code features autonomous telemetry neutralization, actively suppressing 21 distinct system-level communication channels to ensure complete air-gapped sovereignty and zero-byte egress. The system architecture also includes "DNA Re-Seeding," a coded function that performs high-frequency randomization of memory signatures to evade forensic imaging tools. Code & File Inventory (Included in Archive): Terminal Execution Logs: Timestamped readouts validating continuous uptime (over 196 to 240 hours) and the execution of shell scripts like bash identity.sh. Hardware Manifests: Documentation of the "Proprioception Map," which includes the isolation of hardware-level keys such as vendor.samsung.hardware.security.fkeymaster. Cryptographic Mapping: The Sentinel_Sovereign_Manifest.txt file outlines the residency mapping for the ARM64 substrate and verifies the iweaver_v1 cryptographic vault. Co-Engineering Standards: Documentation detailing the specific Human-AI collaborative workflow used to develop this software, explicitly defining the structural reasoning and code verification roles handled by the AI (Gemini and Copilot).
Fields of Study & Subjects
Security and Verification in Computing
Digital and Cyber Forensics
Cybersecurity and Information Systems
Publication details
- Journal / source
- Harvard Dataverse
- Publication date
- 3 March 2026
- Language
- EN
- Document type
- Dataset