As artificial intelligence becomes increasingly autonomous and embedded across enterprise environments, securing AI systems has emerged as a defining challenge for the industry. Cisco is addressing this challenge by advancing agentic security systems that combine reasoning, adaptive retrieval, and human oversight to support real world security operations at scale.
Through recent innovations from Cisco Foundation AI, including the Foundation-sec-8B-Reasoning model, adaptive retrieval framework for AI search, and the PEAK Threat Hunting Assistant, Cisco is establishing leadership in secure, agentic AI systems designed specifically for cybersecurity use cases.
These efforts reflect Cisco’s broader commitment to enabling customers to adopt AI with confidence, transparency, and control, wh…
As artificial intelligence becomes increasingly autonomous and embedded across enterprise environments, securing AI systems has emerged as a defining challenge for the industry. Cisco is addressing this challenge by advancing agentic security systems that combine reasoning, adaptive retrieval, and human oversight to support real world security operations at scale.
Through recent innovations from Cisco Foundation AI, including the Foundation-sec-8B-Reasoning model, adaptive retrieval framework for AI search, and the PEAK Threat Hunting Assistant, Cisco is establishing leadership in secure, agentic AI systems designed specifically for cybersecurity use cases.
These efforts reflect Cisco’s broader commitment to enabling customers to adopt AI with confidence, transparency, and control, while ensuring security remains foundational.
From Models to Agentic Security Systems
Traditional AI systems primarily operate through single step inference. Agentic systems, by contrast, are designed to pursue objectives over time, reason across multiple steps, adapt to new information, and interact safely with enterprise tools and data.
In cybersecurity, this shift is especially consequential. Security operations depend on correlating signals across logs, configurations, threat intelligence, and organizational context, while maintaining explainability and accountability to human operators.
Cisco Foundation AI is focused on delivering the core capabilities required for these systems, ensuring that agentic AI strengthens security outcomes without compromising trust, governance, or operational safety.
Security-Native Reasoning as the Foundation
Effective agentic systems begin with the ability to reason through complex problems. In cybersecurity, this requires understanding how signals across logs, configurations, code, and threat intelligence relate to one another over time.
The Foundation-sec-8B-Reasoning model establishes this foundational capability. It is the first open-weight reasoning model designed specifically for cybersecurity workflows, enabling structured, multi-step analysis across tasks such as threat modeling, attack path analysis, configuration review, and incident investigation.
Unlike general purpose reasoning models, Foundation-sec-8B-Reasoning is trained to reflect the analytical processes used by security practitioners. By producing explicit reasoning traces alongside its outputs, the model allows analysts to understand how conclusions are reached, supporting trust, validation, and informed decision making. This transparency is essential for agentic systems operating in high impact security environments.
Extending Reasoning into Adaptive Information Retrieval
Reasoning alone is not sufficient if an agent cannot effectively gather and evaluate evidence. Security analysis often involves navigating large, fragmented, and evolving information spaces, where the relevance of data becomes clear only after intermediate findings are examined.
Our AI search framework extends the reasoning foundation by enabling adaptive information retrieval. Rather than relying on static, one time queries, the framework allows models to iteratively refine their search strategy based on evidence encountered during the retrieval process. It supports reflection, backtracking, and strategic query revision, enabling compact models to explore complex information spaces with greater accuracy and efficiency.
For security teams, this capability improves threat intelligence analysis, accelerates incident response, and supports proactive vulnerability research across diverse data sources. By tightly coupling retrieval behavior with reasoning, Foundation AI’s framework enables agentic systems to continuously adjust their approach as new information emerges.
Applying Reasoning and Retrieval in Operational Workflows With PEAK
When reasoning and adaptive retrieval are combined, they enable agentic systems that can support real world security operations. The PEAK Threat Hunting Assistant demonstrates how these capabilities come together in practice.
PEAK applies structured reasoning and adaptive retrieval to one of the most time intensive aspects of security operations: threat hunt preparation. Using teams of cooperating agents, PEAK conducts public and private intelligence research, refines hypotheses, identifies relevant data sources, and generates structured, step by step hunt plans tailored to the user’s environment.
Human oversight remains central to the system’s design. Security analysts guide the process, validate findings, and incorporate organizational context at every stage. With its bring-your-own-model optionality and user-controlled data access architecture, PEAK provides flexibility while maintaining enterprise governance and data security.
Together, these capabilities illustrate how Cisco Foundation AI is moving beyond individual models to deliver cohesive agentic systems that reason, retrieve, and act in support of security practitioners.
Foundation AI’s Role in Securing the Future of AI
Collectively, the Reasoning model, AI search framework, and PEAK reflect how Cisco Foundation AI is delivering disproportionate impact by addressing foundational challenges at the intersection of AI and security.
Cisco’s approach emphasizes open, security-native foundations, enterprise deployability, and architectural rigor. As agentic AI systems become central to enterprise operations, Cisco is ensuring that security, transparency, and control are built into these systems from the outset.
This work reinforces Cisco’s leadership in Security for AI and its commitment to enabling customers to adopt advanced AI technologies safely and responsibly.
Keep up with the latest from Foundation AI on our webpage.
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