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Foundation-Sec: LLM for Cybersecurity (long)
Foundation-Sec-8B is a cybersecurity-specialized large language model (LLM) developed by Foundation AI – Cisco Systems Inc., built on the Llama 3.1 architecture12.
Key aspects of Foundation-Sec-8B:
•
Purpose: It was created to address limitations in the adoption of LLMs within cybersecurity, such as the lack of specialized training data and the complexity of representing cybersecurity knowledge13. The goal is to accelerate the progress and adoption of AI-driven tools in both public and private cybersecurity contexts14.
•
Development Process: The model was enhanced through continued pretraining on a carefully curated cybersecurity corpus1. This involved a multi-stage data collection and processing pipeline, starting with 4 TiB of raw web content, which was then filtered, cleaned, and tokenized to produce approximately 25 GiB (about 5 billion tokens) of high-quality training data5....
•
Performance: Foundation-Sec-8B demonstrates significant performance gains over its base model, Llama 3.1-8B, across various cybersecurity benchmarks2. It matches Llama 3.1-70B and GPT-4o-mini in certain cybersecurity-specific tasks, particularly in cyber threat intelligence (CTI) knowledge, and achieves state-of-the-art performance for its size class on selected CTI tasks110. It also retains general knowledge without severe degradation, consistent with prior research on continued pretraining11.
•
Use Cases: It is being piloted or deployed for real-world applications across the security lifecycle, including:
◦
SOC Acceleration: Automating tasks like summarizing alerts, generating incident timelines, and drafting analyst reports1213.
◦
Proactive Threat Defense: Extracting Tactics, Techniques, and Procedures (TTPs), prioritizing vulnerabilities, generating attack path hypotheses, and drafting penetration test reports1314.
◦
Engineering Enablement: Helping teams interpret security policies, validate configurations, assess compliance evidence, and analyze security policies1415.
•
Availability: Foundation-Sec-8B is being released publicly to foster broader experimentation, advancement, and practical deployment of AI-driven security tools within the cybersecurity and AI research communities14.
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By CCStudiosFoundation-Sec-8B is a cybersecurity-specialized large language model (LLM) developed by Foundation AI – Cisco Systems Inc., built on the Llama 3.1 architecture12.
Key aspects of Foundation-Sec-8B:
•
Purpose: It was created to address limitations in the adoption of LLMs within cybersecurity, such as the lack of specialized training data and the complexity of representing cybersecurity knowledge13. The goal is to accelerate the progress and adoption of AI-driven tools in both public and private cybersecurity contexts14.
•
Development Process: The model was enhanced through continued pretraining on a carefully curated cybersecurity corpus1. This involved a multi-stage data collection and processing pipeline, starting with 4 TiB of raw web content, which was then filtered, cleaned, and tokenized to produce approximately 25 GiB (about 5 billion tokens) of high-quality training data5....
•
Performance: Foundation-Sec-8B demonstrates significant performance gains over its base model, Llama 3.1-8B, across various cybersecurity benchmarks2. It matches Llama 3.1-70B and GPT-4o-mini in certain cybersecurity-specific tasks, particularly in cyber threat intelligence (CTI) knowledge, and achieves state-of-the-art performance for its size class on selected CTI tasks110. It also retains general knowledge without severe degradation, consistent with prior research on continued pretraining11.
•
Use Cases: It is being piloted or deployed for real-world applications across the security lifecycle, including:
◦
SOC Acceleration: Automating tasks like summarizing alerts, generating incident timelines, and drafting analyst reports1213.
◦
Proactive Threat Defense: Extracting Tactics, Techniques, and Procedures (TTPs), prioritizing vulnerabilities, generating attack path hypotheses, and drafting penetration test reports1314.
◦
Engineering Enablement: Helping teams interpret security policies, validate configurations, assess compliance evidence, and analyze security policies1415.
•
Availability: Foundation-Sec-8B is being released publicly to foster broader experimentation, advancement, and practical deployment of AI-driven security tools within the cybersecurity and AI research communities14.