implementing-cloud-workload-protection
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.
- License 许可
- Apache-2.0
- 最近更新
- 2026-06-10
- Stars
- ★ 0
- Forks
- 0
01 前言 Front Matter
- name
- implementing-cloud-workload-protection
- tags
- [ "cloud-security", "cwpp", "workload-protection", "boto3", "runtime-security", "process-anomaly-detection" ]
- author
- mahipal
- domain
- cybersecurity
- license
- Apache-2.0
- version
- 1.0
- nist_csf
- [ "PR.IR-01", "ID.AM-08", "GV.SC-06", "DE.CM-01" ]
- subdomain
- cloud-security
- description
- 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.
- mitre_attack
- [ "T1078.004", "T1530", "T1537", "T1580", "T1071" ]
02 资源文件 3
- 许可证LICENSE11.0 KB
- 参考文档references/api-reference.md1.7 KB
- 脚本scripts/agent.py6.8 KB
03 SKILL.md 正文
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"]},
)
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