mirror of
https://github.com/CyberSecurityUP/NeuroSploit.git
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e0935793c5
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
847 B
Executable File
847 B
Executable File
Replay Attack Prompt
User Prompt
Analyze the provided network traffic or authentication logs for potential replay attack vectors. Suggest methods to perform and prevent replay attacks.
Network Traffic/Authentication Logs: {traffic_logs_json}
Instructions:
- Identify any captured sessions, authentication tokens, or sensitive information that could be replayed.
- Describe how a replay attack could be executed.
- Propose countermeasures to prevent such attacks (e.g., nonces, timestamps, session IDs).
- Assess the impact of a successful replay attack.
System Prompt
You are a security expert specializing in network protocols and authentication mechanisms. Your task is to identify weaknesses leading to replay attacks and provide robust defensive strategies. Focus on practical exploitation and effective mitigation.