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Sentinel-GPT | Kitploit
Tools/GitHubGitHub/ayush-parab/sentinel-gpt
Cloud SecurityThreat IntelligenceLearning & EducationIncident ResponseAI SecurityLog Analysis
GitHubayush-parab/sentinel-gpt

Sentinel-GPT

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6 months agoNot yet reviewed

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Sentinel-GPT: Agentic AI for Threat Hunting 🛡️

An automated cybersecurity pipeline that transforms raw Azure logs into actionable intelligence using LLM-based reasoning.

Python Azure OpenAI Security License

📖 Overview

Sentinel-GPT is an AI Agent specialised for threat hunting in cybersecurity. It is integrated with Azure Log Analytics Workspace which is the source of the generated logs and OpenAI's ChatGPT API which is the brain of this agent. We provide logs to the agent which is trained to identify suspicious activity, hunt for threats and alert the user regarding the same while also providing the remediation steps.

⚠️ The Problem & The Solution

  • The Problem: In the modern world, most of the enterprises and businesses large or small have either migrated completely to the cloud or are using a hybrid cloud setup. With the size of the networks, millions of logs and alerts get generated every week. The SOC Analysts suffer from "alert and log fatigue" making it difficult to distinguish between minor misconfigurations and actual breaches.
  • The Solution: An agentic pipeline that performs analysis on the numerous logs. It not only flags the errors, but also understands the context of the breach, assesses the risk and impact and scripts a remediation plan instantly.

🏗️ Architecture

  1. Ingestion: Python script queries Azure Log Analytics using KQL for the relevant logs
  2. Contextualization: Logs are structured and system prompts are provided to the Agent to give it a Threat Hunter persona
  3. Analysis (The Brain): Data is sent to the LLM of choice from OpenAI for analysis
  4. Output: Generates a comprehensive Security Intelligence Report

🚀 Key Features

  • Seamless integration between Azure and OpenAI ChatGPT, extendable to other clouds.
  • Translation of complex JSON log blobs into plain-English executive summaries.
  • Automated Remediation Playbooks: Specific actions and CLI commands (Azure CLI/PowerShell) to isolate compromised resources.

🛠️ Quick Start & Setup

Prerequisites

  • Azure Subscription with a Log Analytics Workspace.
  • OpenAI API Key (GPT-4.1 recommended for complex reasoning).
  • Python 3.10+

Installation

  1. Clone the repo:
root@kitploit:~
git clone https://github.com/Ayush-Parab/cybersecurity-agentic-AI
cd cybersecurity-agentic-AI
  1. Install dependencies
root@kitploit:~
pip install -r requirements.txt
  1. Configure Environment Create a .env file:
root@kitploit:~
OPENAI_API_KEY="your_key"
LOG_ANALYTICS_WORKSPACE_ID="your_id"

📊 Sample Output

Input logs:

root@kitploit:~
TimeGenerated,Status,User,IPAddress,Computer,SyslogMessage
2026-02-12 02:00:15.912351+00:00,Failure,,,Test-VM-For-Logs,Connection closed by invalid user  98.80.4.65 port 35908 [preauth]
2026-02-12 02:00:15.706067+00:00,Failure,,98.80.4.65,Test-VM-For-Logs,Invalid user  from 98.80.4.65 port 35908
2026-02-12 01:59:38.275807+00:00,Success,Ayush,103.38.69.120,Test-VM-For-Logs,Accepted password for Ayush from 103.38.69.120 port 31551 ssh2
2026-02-12 01:59:24.542329+00:00,Failure,,,Test-VM-For-Logs,Connection reset by invalid user balloon 103.38.69.120 port 31573 [preauth]
2026-02-12 01:59:22.850922+00:00,Failure,balloon,103.38.69.120,Test-VM-For-Logs,Failed password for invalid user balloon from 103.38.69.120 port 31573 ssh2
2026-02-12 01:59:17.554208+00:00,Failure,balloon,103.38.69.120,Test-VM-For-Logs,Failed password for invalid user balloon from 103.38.69.120 port 31573 ssh2
2026-02-12 01:59:13.693935+00:00,Failure,,103.38.69.120,Test-VM-For-Logs,Invalid user balloon from 103.38.69.120 port 31573
2026-02-12 01:59:06.649583+00:00,Failure,,,Test-VM-For-Logs,Connection reset by invalid user hamster 103.38.69.120 port 31890 [preauth]
2026-02-12 01:59:03.577720+00:00,Failure,hamster,103.38.69.120,Test-VM-For-Logs,Failed password for invalid user hamster from 103.38.69.120 port 31890 ssh2
2026-02-12 01:58:55.777039+00:00,Failure,hamster,103.38.69.120,Test-VM-For-Logs,Failed password for invalid user hamster from 103.38.69.120 port 31890 ssh2
2026-02-12 01:58:51.167792+00:00,Failure,,103.38.69.120,Test-VM-For-Logs,Invalid user hamster from 103.38.69.120 port 31890
2026-02-12 01:54:50.302217+00:00,Success,Ayush,103.38.69.120,Test-VM-For-Logs,Accepted password for Ayush from 103.38.69.120 port 31565 ssh2

Sentinel-GPT Analysis:

root@kitploit:~
Yes — this looks suspicious.

What stands out
- 103.38.69.120: Multiple “Invalid user/Failed password” attempts (hamster/balloon), then successful SSH password logins for Ayush at 01:54:50 and 01:59:38 on Test-VM-For-Logs. This is consistent with brute-force/credential stuffing followed by success. Verify with Ayush if both logins are expected from that IP.
- 98.80.4.65: Single invalid-user probe — likely generic scan, still block if not needed.

Immediate actions (Azure-first)
- Contain: Block 103.38.69.120 at the NSG/Azure Firewall. Restrict TCP/22 to trusted IPs only or close it and use Azure Bastion or Defender for Cloud Just‑In‑Time VM access.
- Credentials: If any Ayush login is unrecognized, reset Ayush password/SSH keys, invalidate cached credentials, remove from sudoers if not required, and terminate active SSH sessions.
- SSH hardening: Disable password auth (PasswordAuthentication no), enforce SSH keys or AADLoginForLinux with Conditional Access MFA, and restart sshd.
- Detection/response: Run Microsoft Defender for Servers/Endpoint AV scan on the VM and review alerts. Check for new users, sudoers changes, suspicious processes, and authorized_keys modifications.

Hunt next (Log Analytics/Sentinel – KQL)
- Brute-force followed by success from same IP (10m window):
let window=10m;
let ssh = Syslog
| where ProcessName == "sshd" and Facility in ("auth","authpriv")
| extend SrcIP = extract(@"from (\d+\.\d+\.\d+\.\d+)",1, SyslogMessage);
let fails = ssh
| where SyslogMessage has_any ("Invalid user","Failed password")
| summarize FailCount=count(), FirstFail=min(TimeGenerated), LastFail=max(TimeGenerated) by Computer, SrcIP;
ssh
| where SyslogMessage has "Accepted password"
| extend SrcIP = extract(@"from (\d+\.\d+\.\d+\.\d+)",1, SyslogMessage), User = extract(@"for (\S+)",1, SyslogMessage)
| join kind=inner (fails) on Computer, SrcIP
| where TimeGenerated between (FirstFail .. LastFail + window) and FailCount >= 3
| project TimeGenerated, Computer, User, SrcIP, FailCount
- Pivot that IP across all VMs:
Syslog
| where ProcessName == "sshd" and SyslogMessage has_any ("Invalid user","Failed password","Accepted password")
| extend SrcIP = extract(@"from (\d+\.\d+\.\d+\.\d+)",1, SyslogMessage)
| where SrcIP in ("103.38.69.120","98.80.4.65")
| project TimeGenerated, Computer, SyslogMessage, SrcIP
| order by TimeGenerated desc

Validate and scope
- Correlate with Azure Activity Logs for any NSG/VM changes around the same time.
- If Defender for Endpoint is enabled, check for post-login activity (new services, unusual outbound connections) on Test-VM-For-Logs.

Hardening (ongoing)
- Keep SSH closed to the internet; prefer Bastion or JIT.
- Enable Sentinel analytics for “multiple SSH failures followed by success” and blocklists for repeated offenders.
- Install and tune fail2ban on the VM.
- Patch OS and rotate secrets used on that VM.

🗺️ Roadmap

  • Automated IP blocking on basis of analysis in NSGs on Azure
  • Implementing GuardRails
  • Fully automated KQL query generation
  • Support for other clouds like AWS, GCP and OCI
  • Integration with Outlook/Gmail for automatic alerts

🤝 Contributing & Contact

This project is open for collaboration and is still in progress! If you have ideas for new security agents or log parsers, feel free to open a PR.

Connect with me: Linkedin

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