Automation on Ankit Maurya

MCP Monitoring Tool

Sat, 15 Jun 2024 00:00:00 +0000

This project is a proxy-based monitoring system for inspecting LLM context during conversations. It provides visibility into what’s being sent to and from AI models.

Features

Context Inspection: Monitor all prompts and responses going to LLM APIs
Security Logging: Capture and store interaction data for security analysis
Real-time Monitoring: Live view of active conversations
Data Export: Export conversation logs for analysis

Architecture

The tool sits as a proxy between your application and the LLM API, intercepting all traffic for inspection.

Building a CSPM Pipeline: Lessons Learned

Wed, 15 May 2024 00:00:00 +0000

Cloud Security Posture Management (CSPM) pipelines help organizations continuously monitor and improve their security posture. Here’s what I learned building CSPM solutions.

Why CSPM Matters

Manual security reviews don’t scale. As cloud infrastructure grows, you need automated checks that run continuously.

Core Components

1. Data Collection

import boto3

def collect_iam_policies():
    iam = boto3.client('iam')
    policies = iam.list_policies(Scope='Local')['Policies']
    return [
        {
            'arn': p['Arn'],
            'name': p['PolicyName'],
            'version': iam.get_policy_version(
                PolicyArn=p['Arn'],
                VersionId=iam.get_default_version_id(p['Arn'])['DefaultVersionId']
            )['PolicyVersion']['Document']
        }
        for p in policies
    ]

2. Policy Evaluation

Each control should map to a security benchmark (CIS, NIST, SOC2). Example check:

n8n AI Automation System

Wed, 10 Apr 2024 00:00:00 +0000

Building an AI-powered automation system using n8n for security operations and workflow management.

Overview

This system automates security tasks using n8n workflows, AI integrations, and various notification channels.

Key Components

n8n Engine: Core workflow automation
Telegram Bot: Alert notifications and commands
Webhook Triggers: Integration with external services
AI Processing: GPT-based analysis and responses

Workflow Examples

Security Alert Pipeline

Receive webhook from security tool
Parse alert data
Send to AI for classification
Route based on severity (Telegram/Email)
Log to database

Telegram Integration

// n8n Telegram node configuration
{
  chatId: process.env.TELEGRAM_CHAT_ID,
  text: "Security Alert: {{ $json.alert_type }}",
  parse_mode: "HTML"
}

Benefits

Automated incident response
Reduced manual monitoring
Faster alert routing
Integration with existing tools