mirror of
https://github.com/SHOGGOTH-SECTOR/sica-fondt.git
synced 2026-08-01 16:40:24 +00:00
24f816b6a3
Place useful parts of the surrounding repos into sica-fondt by layer, per the
body model (Ada = membrane; brain/endocrine/capabilities/knowledge non-Ada):
- brain/ LLM reasoning + providers (dapr, hermes, MoMoA)
- capabilities/ REPRAG sidecars: hermes tools/skills, dapr tools, parallel
dispatch, A51 channels, and the OSINT cluster
- knowledge/ LORAG corpus: 754 cyber-skills, agency personas, secure-coding,
MITRE ATT&CK data
- reference/ defensive threat-reference (C3, shhbruh doc) + AdaYaml parser
License handling: AGPL sources (worldosint, advanced_evolution, mercury,
Reticulum) and GPL DeTTECT are SPEC-only clean-room/port descriptions — no
copyleft code copied. MIT/Apache/data parts copied as working trees.
Safety: shhbruh escape/persistence material and C3 covert-C2 kept as reference
only, not wired into the running organism. See CONSOLIDATION.md.
https://claude.ai/code/session_01UehUqEXXJJCsHoA4voCU5c
76 lines
2.1 KiB
Markdown
76 lines
2.1 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 for runtime security monitoring, process
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anomaly detection, and file integrity checking on EC2/GCE instances. Scans for cryptomining, reverse shells, and unauthorized
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binaries. 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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- implementing
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- cloud
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- workload
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- protection
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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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---
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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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