Cyber Newsroom exists to cut through the noise in cybersecurity media. The security landscape generates an overwhelming volume of threat reports, vulnerability disclosures, incident post-mortems, and vendor advisories every day. Most practitioners lack the time to synthesise it all. We do it for them.
Our platform ingests RSS feeds from dozens of trusted cybersecurity sources, clusters related stories into coherent intelligence items, and generates multi-perspective analysis using large language models — each grounded in the source material and reviewed by a human editor before publication.
We continuously monitor a curated set of RSS and Atom feeds from sources including incident-response firms, security researchers, national CERTs, major vendors, and specialist cybersecurity media. Each article is parsed, de-duplicated, and scored for relevance.
Related articles are grouped into stories — coherent threat intelligence items covering a single event, vulnerability, or campaign. Clustering uses keyword overlap and entity matching to avoid treating the same event as multiple separate stories.
Once a story has sufficient source material, our LLM pipeline generates two types of content:
All generation is done with explicit prompts that instruct the model to remain grounded in the source material, cite concrete details, and avoid hallucinating facts not present in the ingested articles.
Before any draft is published, a human editor reviews it for factual accuracy, tone, and appropriateness. Drafts that fail review are rejected. Only approved content appears on the public site.
Cyber Newsroom features a roster of fictional AI analyst personas, each with a distinct background, ideology, and specialty. These are not real people — they are prompt-engineered archetypes designed to represent different legitimate perspectives within the security community.
When multiple personas analyse the same story, we also publish a Roundtable Synthesis that distils the key agreements and disagreements across perspectives.
Cyber Newsroom is built on FastAPI (Python) with a SQLite/PostgreSQL backend and Jinja2 templating. AI generation is powered by locally-hosted Ollama models or any OpenAI-compatible API endpoint, allowing operation with complete data sovereignty. No article content or source material is sent to third-party AI providers unless explicitly configured.
The platform integrates with IndexNow for instant URL submission to major search engines on publication, and generates structured data (JSON-LD / Schema.org) for all articles to maximise search-engine comprehension.
Cyber Newsroom has no commercial relationships with security vendors. We do not accept sponsored content, affiliate arrangements, or payment for coverage. Our feed list is curated for technical quality and source diversity, not vendor preference.
For full terms governing use of this site, see our Terms of Use. For information about how we handle your data, see our Privacy Policy.
Questions about the platform, editorial process, or responsible disclosure? Reach us at contact@cybernewsroom.xyz.