mirror of
https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git
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mukul975
cb8d79e068
- Add validated mitre_attack frontmatter to all 754 skills (286 distinct techniques), verified against MITRE ATT&CK v19.1 via the official mitreattack-python library: 0 revoked, deprecated, or invalid IDs - Curate precise per-skill technique IDs for forensics, malware-analysis, threat-intel, and red-team skills (e.g. DCSync -> T1003.006, Kerberoasting -> T1558.003, Pass-the-Ticket -> T1550.003) - Reconcile v19.1 tactic restructuring: Defense Evasion split into Stealth (TA0005) and Defense Impairment (TA0112); revoked T1562.* family and T1070.001/.002 remapped to active equivalents (T1685.*) - Normalize word-split tags across 35 skills (remove filename-derived stopword tags, add semantic cybersecurity tags) - Add api-reference.md for 3 skills that were missing it - Update README ATT&CK section with accurate v19.1 tactic distribution
85 lines
2.3 KiB
Markdown
85 lines
2.3 KiB
Markdown
---
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name: implementing-cloud-workload-protection
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description: 'Implements cloud workload protection using boto3 and google-cloud APIs
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for runtime security monitoring, process anomaly detection, and file integrity checking
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on EC2/GCE instances. Scans for cryptomining, reverse shells, and unauthorized binaries.
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Use when building runtime security controls for cloud compute workloads.
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'
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domain: cybersecurity
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subdomain: cloud-security
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tags:
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- cloud-security
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- cwpp
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- workload-protection
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- boto3
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- runtime-security
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- process-anomaly-detection
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version: '1.0'
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author: mahipal
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license: Apache-2.0
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nist_csf:
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- PR.IR-01
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- ID.AM-08
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- GV.SC-06
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- DE.CM-01
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mitre_attack:
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- T1078.004
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- T1530
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- T1537
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- T1580
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- T1071
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---
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# Implementing Cloud Workload Protection
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## When to Use
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- When deploying or configuring implementing cloud workload protection capabilities in your environment
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- When establishing security controls aligned to compliance requirements
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- When building or improving security architecture for this domain
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- When conducting security assessments that require this implementation
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## Prerequisites
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- Familiarity with cloud security concepts and tools
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- Access to a test or lab environment for safe execution
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- Python 3.8+ with required dependencies installed
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- Appropriate authorization for any testing activities
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## Instructions
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Monitor cloud workloads for runtime threats by checking process lists, network
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connections, file integrity, and resource utilization anomalies.
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```python
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import boto3
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ssm = boto3.client("ssm")
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# Run command on EC2 instances to check for suspicious processes
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response = ssm.send_command(
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InstanceIds=["i-1234567890abcdef0"],
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DocumentName="AWS-RunShellScript",
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Parameters={"commands": ["ps aux | grep -E 'xmrig|minerd|cryptonight'"]},
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)
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```
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Key protection areas:
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1. Process monitoring for cryptominers and reverse shells
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2. File integrity monitoring on critical system files
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3. Network connection auditing for C2 callbacks
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4. Resource utilization anomaly detection (CPU spikes)
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5. Unauthorized binary detection via hash comparison
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## Examples
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```python
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# Check for unauthorized outbound connections
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ssm.send_command(
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InstanceIds=instances,
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DocumentName="AWS-RunShellScript",
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Parameters={"commands": ["ss -tlnp | grep ESTABLISHED"]},
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)
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```
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