Jul 17, 2025
Building Hallucination-Free AI Agents for Security
Geng Sng, Co-founder & CTO
Why Trust Matters in Security
Large Language Models (LLMs) have transformed automation and reasoning but also bring about novel risks. Chief among these is hallucination, where an AI confidently provides convincing yet false information. In cybersecurity, these errors aren't just costly, they can be catastrophic.
Imagine AI mistakenly flagging nonexistent vulnerabilities or overlooking genuine threats. Security leaders must ask themselves: Can we truly trust AI to safeguard our critical systems?
At Cogent Security, trust is at the heart of our AI Agent design. Here’s how we’ve set a new standard for reliability and precision in enterprise security.
Grounded, Contextual, Controlled
1. Grounded in Your Data
Cogent’s Security AI Agents don’t guess. They operate on retrieval-augmented generation (RAG), drawing answers from your live data sources: vulnerability scanners, CMDBs, policies, and more.
By operating within the walls of your data as opposed to relying on generic internet training, our agents avoid fabricating facts. They give precise, tailored responses grounded in the systems you actually run, the policies you’ve actually written, and the vulnerabilities you’re actually exposed to.
Using Cogent’s unified evaluation framework, we continuously score and validate the outputs of all AI-native tools through a combination of automated checks and expert human feedback. This feedback loop enables us to provide precision guarantees for key tasks, ensuring the outputs are not only relevant to your environment but also practically useful. Over time, the system learns from new signals, which improves accuracy, enables adaptation to your data, and ensures continuous refinement of recommendations.
2. Context-Aware by Design
Every environment is unique, and what matters in one organization may be irrelevant in another. Cogent’s AI Agents use organization-specific inputs to contextualize their reasoning, such as your tagging schema, remediation SLAs, and system ownership mappings.
When there's no context, the AI Agents apply data science techniques to understand the distribution of your data and generate baselines, which enables making confidence-weighted inferences that you can inspect directly in Cogent's portal.
This means recommendations aren’t just correct, they’re correct for your organization. You’ll never get vague generalities or misaligned advice. Instead, the AI behaves like a highly-trained analyst in your organization with complete environmental awareness and business context.
3. Guardrails That Stop Hallucinations Cold
In any AI system, it is critical to "Trust, but verify". We take that to the next level through AI Agent controls with multiple layers of guardrails:
Input sanitization removes noise and malicious prompts before they reach models
Relevance filters ensure only essential, validated data makes it into prompts
Source validation confirms all facts against your internal systems and trusted vendor feeds
Output review enforces policy compliance and factual accuracy before responses go live
If Cogent's AI can’t explain and verify a recommendation, it won’t provide it.
Examples of Robust AI in Practice
A Trusted Co-Pilot for Security Teams
When you ask Cogent Assistant, “Which critical vulnerabilities should we focus on this week?” it carefully analyzes your scan data, asset ownership information, and planned patch schedules. You’ll receive a prioritized list with clear references, giving you reliable insights suitable for board presentations and operational workflows alike.
Tailored Remediation Guidance
Every remediation plan that Cogent provides is accurate and actionable. Actions are intelligently grouped and routed based on your organization's ownership mapping and security controls, and your team can stay focused on addressing real threats.
Compliance and Risk Reporting That Writes Itself
When auditors or executives need reports, just ask the Cogent AI Compliance Analyst. It quickly generates clear, traceable summaries of compliance statuses, SLA adherence, and control effectiveness, reducing effort from weeks to minutes. It generates accurate, defensible reports that are designed to meet your specific use cases.
Building AI That Earns Your Trust
At Cogent, we don’t ask you to trust the AI. We show you why you can.
Every decision our AI Agents make is grounded in real, verifiable data, from asset configs to runtime signals, and backed by reasoning you can inspect. You’ll see not just what the agent concludes, but how it got there.
That’s the foundation of trust: not just speed or accuracy, but transparency. We built Cogent so security teams can move fast and feel confident that the AI is doing the right thing for the right reasons.
No hallucinations. No guessing. Just accurate, explainable, and context-aware decisions at machine scale.