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CyberMira is a developer-focused cybersecurity assistant designed to retrieve structured security material before Gemini generates an explanation. Its architecture separates the knowledge source from the answer-writing model: a Sanity knowledge base stores security content, application logic selects relevant material, and retrieval supplies that material to Gemini. That approach can help ground an answer, but the project description does not establish that its answers are accurate or free of unsupported claims.
What CyberMira is
CyberMira is a cybersecurity assistant for developers, described by its creator, Alphonse Kazadi, in a DEV Community post published September 30, 2026. The post reports a knowledge base of 36 structured entries covering OWASP Top 10:2025 categories, vulnerabilities, attack patterns, detection techniques, mitigations, technologies, and security references. That count is the author’s report, not an independently audited inventory.
The project description identifies Sanity as the structured content store, Sanity Context MCP as the retrieval interface, FastAPI as the application and retrieval-logic layer, Gemini as the answer-generation model, and React with Vite as the developer-facing frontend. Kazadi says the content is separated into schemas for vulnerabilities, technologies, attack patterns, detection techniques, mitigations, and OWASP categories, rather than held in one large text block. The project submission describes the implementation; it is not an independent product evaluation.
How a question moves through the system
In the author’s described flow, a developer submits a question through the React/Vite interface. The FastAPI backend determines which knowledge paths are relevant, Sanity Context MCP retrieves corresponding content from the CyberMira Knowledge Base, and that retrieved material is provided to Gemini to generate a readable answer.
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- Ask: A developer enters a security question in the frontend.
- Select: Backend logic maps the question to relevant knowledge paths.
- Retrieve: Sanity Context MCP fetches matching structured material from the knowledge base.
- Explain: Gemini uses the retrieved evidence to generate an answer.
For the example question, “How can I prevent broken object-level authorization in a REST API?”, the author says relevant paths can include access_control, attack_patterns, and mitigation. This illustrates the intended division of work: retrieve material organized around security concepts, then use a model to explain it.
What grounding means—and what it does not prove
Sanity’s glossary defines grounding as tying model output to specific, retrievable source material so claims rest on evidence the system can point to. It distinguishes grounding, a desired quality of an answer, from retrieval-augmented generation (RAG), an architecture that retrieves material and then generates an answer. Sanity’s grounding glossary explains that distinction.
CyberMira’s retrieval-first design is an attempt to ground answers in its knowledge base. Retrieval by itself, however, does not show that every generated claim is supported by the retrieved material. The project submission reports no benchmark, security audit, or independent evaluation of answer quality, retrieval performance, or accuracy. It therefore supports describing the design, not claiming that it prevents hallucinations or guarantees correct security advice.
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Kazadi’s post identifies the Sanity project as zf6ckuvp, the dataset as production, and the knowledge base as “CyberMira Knowledge Base,” with ID kbDqGgqkpnBN. These are configuration details reported in the post, not independently checked live settings.
The post also says the demo is publicly accessible without an account. That is a time-sensitive statement from September 30, 2026, not a guarantee of present availability. The submission does not include a separate agent-session transcript, and it does not establish the current repository or demo state.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to interpret the architecture
The useful design idea is the separation of responsibilities. Structured security content is meant to provide inspectable source material; application logic chooses what to retrieve; the model turns that material into prose. That differs from asking a model to answer from its trained-in knowledge alone, and from putting all security material into one unstructured block. These are architectural distinctions, not demonstrated performance advantages.
For a security answer to be dependable, a reader or operator would still need to assess whether the retrieved sources are relevant and current, whether the generated explanation accurately reflects them, and how the system handles missing or conflicting material. The published description does not report results for those questions. CyberMira is best understood from the available account as an implementation of a retrieval-first assistant, rather than as a validated security authority.
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