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Foundation Sec 8B Q8 0 GGUF

Developed by fdtn-ai
Foundation-Sec-8B-Q8_0-GGUF is a large language model specialized in network security that has undergone 8-bit quantization. It is based on the LLaMA 3.1 architecture and focuses on network security text processing tasks.
Downloads 143
Release Time : 5/31/2025

Model Overview

This model is an 8-bit quantized version of Foundation-Sec-8B. It retains the professional capabilities of the original 8-billion parameter model in the field of network security while significantly reducing the memory usage during inference. It is suitable for network security-related tasks such as threat intelligence analysis and vulnerability classification.

Model Features

Efficient quantization
Using 8-bit quantization technology, the inference memory usage is reduced from approximately 16GB to approximately 8.54GB while maintaining model performance.
Professional network security capabilities
It has undergone continuous pre-training on a carefully curated corpus of network security-specific text and has professional network security text processing capabilities.
Wide compatibility
Supports multiple inference engines, including llama.cpp and the LlamaCpp Python wrapper.

Model Capabilities

Threat intelligence summarization
Vulnerability classification
Event classification assistance
Red team simulation prompts
Security workflow generation

Use Cases

Network security analysis
CVE summarization
Automatically summarize detailed CVE information and extract key security information.
Quickly understand the nature and impact scope of vulnerabilities
Vulnerability classification
Map CVE/CWE to the MITRE ATT&CK framework.
Standardize vulnerability classification for easy evaluation by security teams
Security operations
Log analysis
Extract key indicators and events from security log data.
Accelerate the event response process
Red team simulation
Generate red team test scenarios and attack simulation prompts.
Enhance the effectiveness of defense drills
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