mirror of
https://github.com/CyberSecurityUP/NeuroSploit.git
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v3.5.4 — Robust attack chaining & false-positive reduction
Bundles the multi-round post-exploitation attack-chaining engine (attack_chain: per-foothold decisions, loot carried forward, validate-before-pivot, loop-until- dry, --chain-depth) and the false-positive controls (robust verdict parsing, severity-aware quorum, adversarial refute pass, stronger validator prompt). Version bumped 3.5.3 -> 3.5.4; README/RELEASE updated.
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@@ -871,7 +871,7 @@ dependencies = [
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[[package]]
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name = "neurosploit"
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version = "3.5.3"
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version = "3.5.4"
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dependencies = [
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"anyhow",
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"clap",
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@@ -888,7 +888,7 @@ dependencies = [
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[[package]]
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name = "neurosploit-harness"
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version = "3.5.3"
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version = "3.5.4"
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dependencies = [
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"anyhow",
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"futures",
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@@ -3,7 +3,7 @@ members = ["crates/harness", "app"]
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resolver = "2"
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[workspace.package]
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version = "3.5.3"
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version = "3.5.4"
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edition = "2021"
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license = "MIT"
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repository = "https://github.com/JoasASantos/NeuroSploit"
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@@ -1,4 +1,4 @@
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//! NeuroSploit v3.5.3 — interactive harness + CLI (`run` / `whitebox` / `agents` / `models`).
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//! NeuroSploit v3.5.4 — interactive harness + CLI (`run` / `whitebox` / `agents` / `models`).
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mod repl;
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mod tui;
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@@ -11,8 +11,8 @@ use std::path::{Path, PathBuf};
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#[command(
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name = "neurosploit",
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version,
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about = "NeuroSploit v3.5.3 — multi-model autonomous pentest harness",
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long_about = "NeuroSploit v3.5.3 — a Rust multi-model harness that drives a pool of LLMs \
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about = "NeuroSploit v3.5.4 — multi-model autonomous pentest harness",
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long_about = "NeuroSploit v3.5.4 — a Rust multi-model harness that drives a pool of LLMs \
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(API key or local subscription: Claude/Codex/Gemini/Grok) to autonomously test a target. \
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After recon it INTELLIGENTLY selects only the agents matching the discovered surface, runs \
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them in parallel, then validates every finding by cross-model voting before reporting.\n\n\
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@@ -534,7 +534,7 @@ pub(crate) fn spawn_engagement(base: &Path, mut cfg: RunConfig, mcp: bool, mode:
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cfg.rl_path = Some(base.join("data").join("rl_state_rs.json").display().to_string());
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write_status(&workdir, "running", &format!("\"target\":{:?}", cfg.target));
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println!(" ┌─ NeuroSploit v3.5.3 · by Joas A Santos & Red Team Leaders");
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println!(" ┌─ NeuroSploit v3.5.4 · by Joas A Santos & Red Team Leaders");
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println!(" │ run id : {run_id}");
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println!(" │ target : {}", cfg.target);
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println!(" │ models : {}", cfg.models.join(", "));
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@@ -1,4 +1,4 @@
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//! NeuroSploit v3.5.3 — interactive session (Claude-Code / Codex / Cursor-CLI style).
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//! NeuroSploit v3.5.4 — interactive session (Claude-Code / Codex / Cursor-CLI style).
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//!
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//! Launched when `neurosploit` runs with no subcommand. A persistent REPL with
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//! real line editing (arrow-key history recall, Ctrl-A/E/K, paste), model
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@@ -299,7 +299,7 @@ pub async fn repl(base: &Path) -> anyhow::Result<()> {
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let backends = harness::installed_cli_backends();
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println!("\x1b[1m");
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println!(" ███╗ ██╗███████╗██╗ ██╗██████╗ ██████╗");
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println!(" ████╗ ██║██╔════╝██║ ██║██╔══██╗██╔═══██╗ NeuroSploit v3.5.3");
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println!(" ████╗ ██║██╔════╝██║ ██║██╔══██╗██╔═══██╗ NeuroSploit v3.5.4");
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println!(" ██╔██╗ ██║█████╗ ██║ ██║██████╔╝██║ ██║ interactive harness");
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println!(" ██║╚██╗██║██╔══╝ ██║ ██║██╔══██╗██║ ██║ by Joas A Santos");
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println!(" ██║ ╚████║███████╗╚██████╔╝██║ ██║╚██████╔╝ & Red Team Leaders");
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@@ -1,4 +1,4 @@
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//! NeuroSploit v3.5.3 — TUI "Mission Control" mode.
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//! NeuroSploit v3.5.4 — TUI "Mission Control" mode.
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//!
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//! Concurrent panels that update live while the engagement runs in the
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//! background, with a composer input that stays active during execution:
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@@ -1,4 +1,4 @@
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//! POMDP belief-state world model (v3.5.3).
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//! POMDP belief-state world model (v3.5.4).
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//!
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//! The target is only partially observable, so we don't track booleans — we
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//! track a **belief**: a property graph whose nodes (host / service / vuln /
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@@ -1,4 +1,4 @@
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//! Verification / grounding engine (v3.5.3).
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//! Verification / grounding engine (v3.5.4).
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//!
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//! Hard rule: **no claim enters the world model without a tool receipt** — raw
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//! tool output, not the LLM's paraphrase. This is the empirical anti-hallucination
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@@ -1,4 +1,4 @@
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//! NeuroSploit v3.5.3 harness — a robust multi-model runtime for the
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//! NeuroSploit v3.5.4 harness — a robust multi-model runtime for the
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//! markdown-driven autonomous pentest engine.
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//!
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//! The harness loads the `agents_md/` library, drives a *pool* of LLM models
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@@ -1,4 +1,4 @@
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//! POMDP decision layer (v3.5.3): value-of-information planning + the
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//! POMDP decision layer (v3.5.4): value-of-information planning + the
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//! anti-hallucination gate.
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//!
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//! The choice "scan more vs exploit now" is **not** a heuristic here — it falls
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@@ -97,9 +97,9 @@ pub fn html(target: &str, findings: &[Finding]) -> String {
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h4{{margin:12px 0 3px;font-size:12px;text-transform:uppercase;letter-spacing:.5px;color:#8b5cf6}}\
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.b{{color:#8b5cf6;font-weight:800}}</style></head><body>\
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<h1><span class=b>NeuroSploit</span> Penetration Test Report</h1>\
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<div class=meta>Target: <b>{t}</b> · v3.5.3 Rust harness · multi-model validated</div>\
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<div class=meta>Target: <b>{t}</b> · v3.5.4 Rust harness · multi-model validated</div>\
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<div>{chips}</div>{graph_block}<h2>Findings ({n})</h2>{body}\
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<p class=meta>Authorized testing only. Findings confirmed by multi-model adversarial voting.<br>NeuroSploit v3.5.3 · by <b>Joas A Santos</b> & <b>Red Team Leaders</b></p></body></html>",
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<p class=meta>Authorized testing only. Findings confirmed by multi-model adversarial voting.<br>NeuroSploit v3.5.4 · by <b>Joas A Santos</b> & <b>Red Team Leaders</b></p></body></html>",
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t = esc(target), chips = chips, n = sorted.len(), body = body, graph_block = graph_block,
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)
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}
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@@ -135,7 +135,7 @@ pub fn typst_report(target: &str, findings: &[Finding], dir: &Path) -> std::io::
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let mut data = String::new();
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data.push_str(&format!(
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"#let meta = (target: {}, run_id: {}, generated: {}, model: {})\n",
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tq(target), tq(&run_id), tq("NeuroSploit v3.5.3"), tq("multi-model")
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tq(target), tq(&run_id), tq("NeuroSploit v3.5.4"), tq("multi-model")
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));
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data.push_str("#let findings = (\n");
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for f in sorted_findings(findings) {
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