implementing-cloud-workload-protection
Teaches your AI agent to ship projects and manage infrastructure and protect apps against attacks.
What it does
This tool helps protect your cloud computers (like those from Amazon or Google) against real-time threats. It checks for suspicious activities such as cryptocurrency mining, unauthorized programs, or intrusion attempts.
When to use it
- ✓When setting up security for your cloud computers.
- ✓When creating security rules to meet compliance standards.
- ✓When improving the protection of your cloud systems.
Example of what to ask your AI
“Check my servers for cryptocurrency mining.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
The tool runs commands on your cloud computers to analyze running processes, check important files, and monitor resource usage. It looks for signs of malicious activity.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-cloud-workload-protectionOr download just the file:
curl -L https://raw.githubusercontent.com/mukul975/Anthropic-Cybersecurity-Skills/main/skills/implementing-cloud-workload-protection/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Implementing Cloud Workload Protection
When to Use
- When deploying or configuring implementing cloud workload protection capabilities in your environment
- When establishing security controls aligned to compliance requirements
- When building or improving security architecture for this domain
- When conducting security assessments that require this implementation
Prerequisites
- Familiarity with cloud security concepts and tools
- Access to a test or lab environment for safe execution
- Python 3.8+ with required dependencies installed
- Appropriate authorization for any testing activities
Instructions
Monitor cloud workloads for runtime threats by checking process lists, network connections, file integrity, and resource utilization anomalies.
import boto3
ssm = boto3.client("ssm")
# Run command on EC2 instances to check for suspicious processes
response = ssm.send_command(
InstanceIds=["i-1234567890abcdef0"],
DocumentName="AWS-RunShellScript",
Parameters={"commands": ["ps aux | grep -E 'xmrig|minerd|cryptonight'"]},
)
Key protection areas:
- Process monitoring for cryptominers and reverse shells
- File integrity monitoring on critical system files
- Network connection auditing for C2 callbacks
- Resource utilization anomaly detection (CPU spikes)
- Unauthorized binary detection via hash comparison
Examples
# Check for unauthorized outbound connections
ssm.send_command(
InstanceIds=instances,
DocumentName="AWS-RunShellScript",
Parameters={"commands": ["ss -tlnp | grep ESTABLISHED"]},
)
FAQ
What are 'cloud workloads'?
These are the programs and services that run on computers from companies like Amazon (AWS) or Google (GCP).
What are 'APIs'?
They are like 'messengers' that allow different computer programs to communicate with each other.
What is 'boto3'?
It is a tool that helps Python programs communicate with Amazon (AWS) services.
Details
Original description by the author
Implements cloud workload protection using boto3 and google-cloud APIs for runtime security monitoring, process anomaly detection, and file integrity checking on EC2/GCE instances. Scans for cryptomining, reverse shells, and unauthorized binaries. Use when building runtime security controls for cloud compute workloads. '
Popularity
- GitHub stars
- 35k
- Ranking position
- #5852
- License
- Apache-2.0
- Updated
- 8/31/2026
Comments
- …
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