clouditera/SecGPT-14B

SecGPT-14B: A Specialized Cybersecurity LLM

SecGPT-14B, developed by Clouditera, is a 14.8 billion parameter open-source large language model engineered for network security. It integrates natural language understanding, code generation, and security knowledge inference, building upon the robust architectures of Qwen2.5-Instruct and DeepSeek-R1 models.

Key Capabilities

• Vulnerability Analysis: Identifies causes, assesses impact, and suggests fixes.
• Log & Traffic Forensics: Reconstructs attack paths and analyzes attack chains.
• Anomaly Detection: Pinpoints potential threats to improve security posture.
• Offensive/Defensive Reasoning: Supports red team exercises and blue team analysis.
• Command Parsing: Analyzes attack scripts to identify intent and high-risk operations.
• Security Knowledge Q&A: Acts as an intelligent knowledge engine for security teams.
• Penetration Testing: Simulates attack flows, constructs payloads, and generates exploitation chains.
• Code Auditing: Assists in identifying vulnerabilities within codebases.
• Reverse Engineering: Aids in static analysis, feature extraction, and malware family classification.

Performance and Training

SecGPT-14B was trained on an extensive 5TB cybersecurity corpus, with over 40% of the data being manually curated and structured. This includes legal regulations, academic papers, industry reports, vulnerability details, CTF challenges, and security community blogs. Benchmarks against SecGPT-mini and Qwen2.5-Instruct show significant improvements, particularly in security-specific datasets like CISSP and CS-EVAL, where it consistently outperforms its base models. The training involved large-scale pre-training, instruction fine-tuning, and reinforcement learning on 8 A100 GPUs.

Deployment

SecGPT supports high-performance deployment via the vLLM framework, suitable for low-latency, high-concurrency, and high-throughput security model services.