cloud-threat-detection - This project demonstrates the implementation of an

项目说明

🛡️Cloud-Threat-Detection

This project shows how to build an automatic security system on Amazon Web Services (AWS) that constantly watches for cyber threats, takes action to stop them, and immediately alerts your security team. The system uses smart detection tools to spot unusual activity, like someone trying to steal data or hack into a server, and then automatically responds—for example, by isolating the affected server and creating a backup for in. This all happens in minutes or e, which means your team can find and fix security problems much faster than if they had to do e manually.

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📋 Table of Contents

<a href="#key-features">Key Features</a>

<a href="#architecture-diagram">Architecture Diagram</a>

<a href="#tech-stack">Tech Stack</a>

<a href="#project-phase">Project Phase</a>

<a href="#result">Result</a>

<a href="#security-best-practices">Security Best Practices</a>

<a href="#resources">Resources</a>

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<h2><a class="anchor" id="key-features"></a> 🎯 Key Features</h2>

🔍 Real-time Threat Detection: Utilizes Amazon GuardDuty and CloudWatch Alarms to monitor for malicious acti.

⚡ Automated Response: AWS Lambda functions execute pre-defined response playbooks (EC2 isolation, forensic snapshot creation).

📨 Instant Notifications: Amazon SNS sends real-time alerts to security teams.

🔄 End-to-End Testing: Kali Linux penetration testing the entire pipeline.

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<h2><a class="anchor" id="architecture-diagram"></a> 🏗️ Architecture Diagram</h2>

!image alt

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<h2><a class="anchor" id="tech-stack"></a> 🚀 Tech Stack</h2>

🔍 Detection Layer

| Service | Purpose |
| :--- | :--- |
| Amazon GuardDuty | Intelligent threat detection (port scans, anomalous API calls) |
| Amazon CloudWatch | Custom metrics and alarms (S3 data exfiltration) |
| AWS CloudTrail | Detailed API logging for S3 object-le |

⚡ Orchestration & Response Layer

| Service | Purpose |
| :--- | :--- |
| Amazon E | Event routing and triggering Lambda functions |
| AWS Lambda | Executes automated response playbooks |
| AWS Step Functions | Coordinates multi-step remediation workflows |

📨 Notification

| Service | Purpose |
| :--- | :--- |
| Amazon SNS | Real-time alerts (email/SMS) |

🧪 Testing Layer

| Service | Purpose |
| :--- | :--- |
| Kali Linux / Pacu | Penetration testing and attack simulation |

🏗️ Infrastructure Layer

| Service | Purpose |
| :--- | :--- |
| Amazon VPC | Isolated network en |
| Amazon EC2 | Target instances for attack simulation |
| Amazon S3 | Sensitive data storage for exfiltration testing |
| Amazon RDS | High-value target for lateral mo testing |

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<h2><a class="anchor" id="project-phase"></a> 📝 Project-Phase</h2>

### Phase 1 : Lab En Setup

Create isolated VPC with public and private subnets.

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Deploy "Compromised" EC2 instance with IAM role(S3ReadOnly).

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Create sensitive S3 bucket with dummy data.

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Deploy RDS database in private subnet.

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Enable the SNS.

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### Phase 2 : Detection Services Configuration

Enable Amazon GuardDuty.

Configure AWS CloudTrail, first create a trail for S3 object-le and enable the CloudWatch logs option.

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Create CloudWatch Metric Filter, first create log group then create metric filter in it for GetObject events.

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Create Alarm for S3 exfiltration, In alram select the custom metric filter with threshold > 2.

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### Phase 3 : Automated Response Implementation

Develop AWS Lambda function for automated response.

Lambda Function TD_Catcher

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Create E rule for high-se GuardDuty findings.

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### Phase 4 : Attack Simulation &

Set up Kali Linux attack machine.

Configure Pacu for automated AWS pentesting. Execute attacks: S3 exfiltration, port scanning, lateral mo.

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<h2><a class="anchor" id="result"></a> 📄 Result</h2>

Amazon SNS Notification for S3 exfiltration.

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Check CloudWatch.

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Check GuardDuty findings.

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Check GuardDuty Summary.

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<h2><a class="anchor" id="security-best-practices"></a> ✅ Security Best Practices</h2>

- Principle of Least Pri for IAM roles

- Isolated lab en for testing

- MFA enforcement on all users

- Regular security reviews

- Encryption at rest and in transit

- Secure storage of sensitive data

- Regular penetration testing

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<h2><a class="anchor" id="resources"></a> 📚 Resources</h2>

Amazon VPC

Amazon EC2

Amazon S3

Amazon RDS

AWS CloudTrail

Amazon CloudWatch

Amazon GuardDuty

Amazon E

AWS Lambda

Pacu

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项目信息

开发语言：Python

Star 数：2

技术要点

该项目属于防护思路方向的开源资源，代码结构清晰，适合安全研究人员学习参考。项目围绕This project demonstrates the implementation of an automated security operations (SecOps) system on Amazon Web Services (AWS). 展开，提供了可运行的实现，对理解相关安全机制、工具原理与攻防技术具有较高的研究价值。

从技术实现角度看，此类项目的核心在于对底层原理的深入理解与工程化落地。开发者在研究过程中可以结合官方文档与社区讨论，梳理项目的初始化流程、核心模块职责与数据流转，逐步掌握其中的技术细节与设计思路。

使用与学习建议

1. 下载源码压缩包，解压到本地环境。

2. 根据项目类型准备对应的运行环境与依赖。

3. 按照 README 中的步骤完成配置与部署。

4. 在隔离的测试环境中运行验证，避免影响生产系统。

免责声明

本资源来源于开源社区，仅供安全研究、技术学习与合法授权范围内的攻防演练使用，请勿用于任何非法或侵害他人权益的用途。使用本项目产生的一切后果由使用者自行承担。