Install
$ agentstack add skill-pinkpixel-dev-skills-collection-2-implementing-cloud-workload-protection ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
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"]},
)
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: pinkpixel-dev
- Source: pinkpixel-dev/skills-collection-2
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.