Local LLM (Local Large Language Model)
Data ProtectionA local LLM is a large language model that runs on your own machine (laptop, server, or on-premises GPU) rather than through a cloud API. Tools like Ollama make it possible to run models like Phi-4, Llama 3.2, Mistral, and DeepSeek locally with GPU acceleration.
Why Local LLMs Matter for Security
- Data stays on your machine: prompts containing IAM policies, CloudTrail logs, Terraform templates, or customer data never leave your RAM
- No third-party processor: eliminates GDPR, HIPAA, and SOC 2 concerns about sending sensitive data to external APIs
- Offline capable: works in air-gapped environments and during incident response when network access may be restricted
- No per-token cost: run unlimited queries against your own hardware
Trade-offs
- Local models are smaller than cloud frontier models (8B-14B parameters vs 100B+)
- Quality is lower for complex reasoning tasks, but sufficient for policy review, code scanning, and log analysis
- Requires hardware with enough RAM (16-24GB minimum for useful models)
AWS Security Use Cases
- IAM policy analysis for privilege escalation risks
- CloudTrail log analysis for suspicious activity
- Terraform/CloudFormation security review
- Incident response assistance with NIST framework guidance
- Security code review for Lambda functions and application code
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Related Terms
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