639c2209f7
v3.5.1: attack-chain agents (12) + per-project .neurosploit/ persistence & resume
...
Chaining:
- agents_md/chains/ (12 multi-stage exploitation playbooks): SQLi→RCE→LPE,
SSRF→AWS-creds, SSRF→RCE, upload→RCE, upload→LFI→RCE→LPE, XSS→ATO, IDOR→ATO,
SSTI→RCE→cloud, default-creds→domain, deserialization→RCE, exposed-git→RCE,
subdomain-takeover→trusted-abuse. Each stage proven by a tool receipt before
advancing; reports chains_from edges.
- Loaded as a `chains` category (→ 329 agents). chain_round now injects the chain
recipes as a menu so the LLM applies proven multi-stage paths.
Persistence (no DB — structured state):
- Per-project `<cwd>/.neurosploit/` holding session.json (config), runs.json
(history), history.txt (readline). REPL resumes target/repo/auth/focus/models
on reopen; saves on /run and /quit.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com >
2026-06-24 22:30:22 -03:00
f8d70ce9c5
v3.5.1: infra/host engagements — IP + SSH/Windows-AD creds + Linux/Win/AD agents + REPL context bar
...
Infra:
- creds.yaml gains `ssh:` (host/port/user/password/key) and `windows:`/`ad:`
(host/user/password/domain/ntlm-hash) blocks; multi-block YAML parser.
host_instruction() tells agents how to authenticate to the host.
- 14 infra agents (agents_md/infra/): port/service scan, SMB enum, Linux privesc/
sudo/cron/SSH, Windows privesc/SMB-signing/WinRM, AD kerberoast/asreproast/ACL/
DCSync/default-creds. Loader gains `infra` category → 317 agents total.
- run_host pipeline + `neurosploit host <ip> --creds creds.yaml` (and Mode::Host
in run_mode/TUI): host recon (nmap/netexec) → infra agent selection → test →
validate → chain → report, with host tooling doctrine + supplied creds.
REPL:
- Context/status bar above the prompt: "model auth · cwd · mode▸target"
(e.g. claude-opus-4-8 sub · /opt/projeto · black-box▸app.acme.com).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com >
2026-06-24 22:17:14 -03:00
0a2cf58d9e
v3.4.1: slim Rust-only branch
...
Keep only the Rust harness (neurosploit-rs/) + the agent library (agents_md/) it
loads at runtime, plus docs. Remove the Python engine, web GUIs, legacy stack,
docker, build scripts and scratch test files from THIS branch only (other
branches keep everything). Rust-focused README with Kali/Docker + tool-install
guidance and testphp/DVWA usage examples.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com >
2026-06-24 19:36:16 -03:00
3ca3f269ee
v3.4.x: intelligent agent selection, whitebox, recon/code agents, Gemini, artifacts, RL, XBOW GUI
...
Harness intelligence:
- After recon, the model SELECTS which specialist agents match the target
(select_agents) — runs the relevant subset, not blindly top-N
- RL reward store (rl.rs): per-agent weights persist to data/rl_state_rs.json,
reward validated findings (severity-weighted), decay idle, bias next run
- Run artifacts persisted as JSON + MD (recon, exploitation transcript,
findings, html report) under runs/<target>-<ts>/ for reuse by other AIs
Whitebox mode:
- run_whitebox: walks a repo, builds bounded source context, runs code agents,
validates by adversarial vote. CLI `whitebox <path>` + web "White-box" mode
Agents: +12 recon (subdomain/tech/js/api/secrets/dns/content/param/waf/cloud/
graphql/osint) and +24 code SAST reviewers (sqli/cmdi/path/ssrf/xss/deser/
secrets/crypto/authz/idor/xxe/redirect/ssti/race/eval/csrf/random/logging/
upload/mass-assign/jwt/cors). Loader gains recon/ + code/ categories → 249 total
Models: +Google Gemini provider (API + gemini CLI subscription); installed_cli_
backends now detects gemini; chat_cli handles gemini/codex/grok + optional
Playwright MCP (.mcp.json) on the subscription path with autonomy flags
GUI: full XBOW-style redesign — sidebar (Operate/Library), topbar status, mode
segment (black-box/white-box), model panel, live console, severity cards,
agent browser with category filters, models view; responsive + aligned
Verified: cargo build --release clean; CLI agents/whitebox; LIVE subscription
run shows model selecting 23→4 agents, RL update, artifacts written; GUI +
white-box toggle in Playwright.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com >
2026-06-23 11:39:56 -03:00
3de357bf18
Merge NeuroSploit v3.3.0 — Autonomous MD-Agent Engine into main
...
# Conflicts:
# prompts/task_library.json
2026-06-14 21:41:26 -03:00
55af0d4634
NeuroSploit v3.3.0 — Autonomous MD-Agent Engine
...
Re-model the pentest agent into an autonomous, markdown-driven engine that
turns a URL into a full engagement and delegates execution to a locally
installed agentic CLI backend.
Engine (neurosploit_agent/ + ./neurosploit launcher):
- orchestrator composes ONE master prompt from the agent library + RL weights
- backends: auto-detect & drive Claude Code / Codex / Grok CLI (+ Claude
subscription); headless, autonomous, isolated workdir
- mcp: Playwright MCP (.mcp.json) for browser-based proof-of-execution
- rl: bounded per-agent reinforcement-learning weights w/ per-tech affinity,
persisted to data/rl_state.json
- models: latest registry incl. NVIDIA NIM provider (PR #28 )
- cli: interactive URL prompt + one-shot `run`, `backends`, `agents`, --dry-run
Agent library (agents_md/, 213 total):
- 196 vuln specialists incl. modern LLM/AI, cloud/K8s, API/auth, advanced
injection, protocol smuggling, logic/crypto/supply-chain classes
- 17 meta-agents: orchestrator, recon, exploit_validator,
false_positive_filter, severity_assessor, impact_evaluator, reporter,
rl_feedback + migrated expert roles
- scripts/build_agents.py data-driven builder; REGISTRY.md index
Docs: rewritten README.md, v3.3.0 RELEASE.md, .env.example (NVIDIA NIM, xAI,
engine vars).
Retire legacy Python orchestration (neurosploit.py + agent classes) to legacy/.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com >
2026-06-14 20:57:38 -03:00
806d1bcbe1
feat: 2026 UI overhaul, stability fixes, and NVIDIA NIM support
...
- Overhauled frontend with 2026 hacking HUD aesthetic (neon colors, glassmorphism)
- Added native support for NVIDIA NIM as a Tier 2 provider
- Fixed critical backend crashes in autonomous_agent.py and knowledge_processor.py
- Updated Kali sandbox build to Go 1.26 and fixed health check reliability
- Integrated Space Grotesk and JetBrains Mono fonts
2026-04-29 00:57:04 +05:30
e0935793c5
NeuroSploit v3.2 - Autonomous AI Penetration Testing Platform
...
116 modules | 100 vuln types | 18 API routes | 18 frontend pages
Major features:
- VulnEngine: 100 vuln types, 526+ payloads, 12 testers, anti-hallucination prompts
- Autonomous Agent: 3-stream auto pentest, multi-session (5 concurrent), pause/resume/stop
- CLI Agent: Claude Code / Gemini CLI / Codex CLI inside Kali containers
- Validation Pipeline: negative controls, proof of execution, confidence scoring, judge
- AI Reasoning: ReACT engine, token budget, endpoint classifier, CVE hunter, deep recon
- Multi-Agent: 5 specialists + orchestrator + researcher AI + vuln type agents
- RAG System: BM25/TF-IDF/ChromaDB vectorstore, few-shot, reasoning templates
- Smart Router: 20 providers (8 CLI OAuth + 12 API), tier failover, token refresh
- Kali Sandbox: container-per-scan, 56 tools, VPN support, on-demand install
- Full IA Testing: methodology-driven comprehensive pentest sessions
- Notifications: Discord, Telegram, WhatsApp/Twilio multi-channel alerts
- Frontend: React/TypeScript with 18 pages, real-time WebSocket updates
2026-02-22 17:59:28 -03:00
CyberSecurityUP