feat(4.0.0): web console — lead board + live findings + real CLI REPL

New web/ app (zero npm deps, Node http built-ins only):
- server.js reads agents_md/ to build a categorized lead board (435 agents
  auto-classified into Business Logic / Broken Access Control / Injection /
  LLM Application / Auth & Session / SSRF / API / Cloud & Infra / etc.),
  reads runs/ for history, and spawns the compiled neurosploit CLI binary
  for every exploitation job — structured findings/phase/progress are parsed
  from its stdout (finding_json:/phase lines), same signal the TUI uses.
- REPL drawer spawns `neurosploit` with no subcommand (real interactive
  session, Reader::Plain over the piped stdin) and streams stdin/stdout —
  every /command works exactly as in a terminal, nothing reimplemented.
- SSE endpoints for both job and REPL streams; run/finding/report assets
  served under /api/runs/:id/asset/*.
- public/{index,app.js,style.css}: lead board with category toggles + custom
  leads + Start Exploitation, live run view (progress/findings/log), run
  detail view, REPL drawer — screenshot-inspired layout.
- web/API.md: full endpoint reference. web/README.md: quick start.

Bump version 3.6.9 -> 4.0.0 (Cargo.toml, CLI banners, README/TUTORIAL).

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0129WdYHccPsH27k5GGuwijd

neurosploit-rs/app/src/main.rs

@@ -1,4 +1,4 @@
-//! NeuroSploit v3.6.9 — interactive harness + CLI (`run` / `whitebox` / `agents` / `models`).
+//! NeuroSploit v4.0.0 — interactive harness + CLI (`run` / `whitebox` / `agents` / `models`).
 
 mod repl;
 mod tui;
@@ -11,8 +11,8 @@ use std::path::{Path, PathBuf};
 #[command(
     name = "neurosploit",
     version,
-    about = "NeuroSploit v3.6.9 — multi-model autonomous pentest harness",
-    long_about = "NeuroSploit v3.6.9 — a Rust multi-model harness that drives a pool of LLMs \
+    about = "NeuroSploit v4.0.0 — multi-model autonomous pentest harness",
+    long_about = "NeuroSploit v4.0.0 — a Rust multi-model harness that drives a pool of LLMs \
 (API key or local subscription: Claude/Codex/Gemini/Grok/OpenCode/Hermes) to autonomously test a target. \
 After recon it INTELLIGENTLY selects only the agents matching the discovered surface, runs \
 them in parallel, then validates every finding by cross-model voting before reporting.\n\n\
@@ -765,7 +765,7 @@ pub(crate) fn spawn_engagement(base: &Path, mut cfg: RunConfig, mcp: bool, mode:
     println!("  │  ua     : {ua}");
     write_status(&workdir, "running", &format!("\"target\":{:?}", cfg.target));
 
-    println!("  ┌─ NeuroSploit v3.6.9  ·  by Joas A Santos & Red Team Leaders");
+    println!("  ┌─ NeuroSploit v4.0.0  ·  by Joas A Santos & Red Team Leaders");
     println!("  │  run id : {run_id}");
     println!("  │  target : {}", cfg.target);
     println!("  │  models : {}", cfg.models.join(", "));