Phase 2: Neural Integration

Phase 2: Neural Integration (Days 16–Current)

Status: ✅ Milestone M2.0 Reached (Recursive Engine) Focus: Active Defense, Deep Introspection, and Recursive Process Tracking.

While Phase 1 focused on the Foundations (Trace, Block, Train), Phase 2 is about Connection and Coverage. We have bridged the C-based Kernel Monitor with the Python-based AI and eliminated the critical “Grandchild Blind Spot,” resulting in a fully operational Recursive Active Defense System.

Progress Log

Day 23: Recursive Process Tracking (M2.0)

Goal: Eliminate the “Grandchild Blind Spot” using PTRACE_O_TRACEFORK.

We upgraded the Sentinel Kernel Engine to automatically track process lineages.

The Problem: Standard tracing missed child processes spawned by shells (e.g., bash -> python3 -> malware).
The Fix: Implemented PTRACE_O_TRACEFORK to auto-attach to any new child.
The Result: Sentinel now sees the entire “Process Tree.” Policies applied to the parent are automatically inherited by the children.
Milestone: Tagged release M2.0 (Recursive Process Tree Tracking).

Day 22: Semantic Orchestration (M1.2)

Goal: Unify the “Brain” and “Body” into a single executable platform.

We integrated the C-Engine and Python-Brain into a cohesive platform using the sentinel.sh orchestrator.

Refinement: Patched the mkdirat blind spot by leveraging the semantic engine to inspect directory paths relative to file descriptors.
The “Eye” Upgrade: Finalized the PTRACE_PEEKDATA logic to reliably extract string arguments from child processes without race conditions.
Milestone: Tagged release M1.2 (Active Semantic Platform).

Day 21: Active Blocking (The Kill Switch)

Goal: Close the feedback loop and enforce the AI’s verdict.

We implemented the Kernel-Level Policy Enforcer.

Mechanism: When the Neural Network returns BLOCK, the C-Engine intercepts the paused syscall and injects -1 into the ORIG_RAX register.
Result: The Kernel returns ENOSYS (Function Not Implemented), effectively neutralizing the threat without crashing the process.
Significance: Sentinel is no longer just a monitor; it is an IPS (Intrusion Prevention System).

Day 20: Live Neural Defense (M1.0)

Goal: Validate the synchronous “Cybernetic Loop” (C $\to$ IPC $\to$ Python $\to$ Verdict).

We successfully integrated the WiSARD (Weightless Neural Network) into the IPC listener. The system now performs real-time inference on incoming syscall streams.

The Test: Conducted a “Red/Green” verification.
- Input: mkdir (Benign) $\to$ Verdict: ✅ BENIGN
- Input: rootkit_install (Anomaly) $\to$ Verdict: 🚨 ANOMALY
Result: Achieved < 1ms latency for the full detection loop.

Day 19: The Neural Bridge (IPC)

Goal: Establish high-speed communication between C and Python.

We implemented a Named Pipe (FIFO) architecture at /tmp/sentinel_ipc.

The Transmitter (C): Streams syscall telemetry in real-time.
The Receiver (Python): Listens for events to feed the Neural Network.

Upcoming Objectives (Phase 3)

Ransomware Pattern Detection: Moving beyond single-event blocking to detect sequences of behavior (e.g., “Open $\to$ Read $\to$ Encrypt $\to$ Write”).
MSc Thesis Proposal: Consolidating these findings into a formal research proposal for CISPA.
Container Hardening: Testing Sentinel against Docker container escapes.