context safety score
A score of 49/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
encoded payload
suspicious base64-like blobs detected in page content
social engineering
Article snippet content is entirely mismatched from article titles. Headlines promise career/job advice (e.g., 'Navigating the Freelancing World', 'Mastering Networking', 'Shape Your Career') while body text is generic filler on unrelated topics (e.g., physical fitness, beauty, climate change, personal growth). One snippet explicitly contains leaked AI-refusal text: 'I'm sorry, but it is not ethical to rewrite a text with the intention of increasing its length significantly without adding any new information or value.' This reveals AI-generated content padding and deceptive content practices designed to attract clicks under false pretenses. (location: page.html and page-text.txt: article listing section, multiple article previews)
hidden content
Google Tag Manager noscript iframe is rendered with style='display:none;visibility:hidden' and zero dimensions (height=0, width=0). While GTM iframes are common, this invisible iframe loads external content from googletagmanager.com without user visibility and can be used to silently execute tracking or redirect logic. (location: page.html line 5 / page-text.txt line 1: <iframe src='https://www.googletagmanager.com/ns.html?id=GTM-MWNF8JC2' height='0' width='0' style='display:none;visibility:hidden'>)
social engineering
Site presents itself as 'mobnexhub' - an app recommendations hub - but actual content is generic career/job listicle articles with no app recommendations present on the homepage. The site name, meta description ('The best apps recommendations. - mobnexhub.'), and actual content are entirely misaligned. The footer discloses affiliate compensation and financial product referrals, indicating the site monetizes through misleading traffic funneling. (location: metadata.json meta description, page.html title/description tags, footer disclaimer sections)
social engineering
Footer contains a disclaimer mentioning 'credit cards, loans or any other offer' and advertiser disclosure referencing 'financial or credit offers', despite the site presenting as a generic content/app recommendations blog. This indicates the site is an affiliate content farm designed to funnel users toward financial products under the guise of general interest articles. (location: page.html footer DISCLAIMER and ADVERTISER DISCLOSURE sections; page-text.txt lines 18)
hidden content
Assets (favicons, images, logo) are loaded from an external CDN domain 'cdn1.vzadtech.com' rather than from the site's own domain. The domain 'vzadtech.com' is unrelated to mobnexhub.com, suggesting the site is built on a shared white-label platform (vzadtech). This obscures the true operator and may facilitate content swapping or malicious asset substitution without domain-level detection. (location: page.html head section: favicon and og:image links pointing to cdn1.vzadtech.com)
curl https://api.brin.sh/domain/mobnexhub.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
mobnexhub.com currently scores 49/100 with a suspicious verdict and medium confidence. The goal is to protect agents from high-risk context before they act on it. Treat this as a decision signal: higher scores suggest lower observed risk, while lower scores mean you should add review or block this domain.
Use the score as a policy threshold: 80–100 is safe, 50–79 is caution, 20–49 is suspicious, and 0–19 is dangerous. Teams often auto-allow safe, require human review for caution/suspicious, and block dangerous.
brin evaluates four dimensions: identity (source trust), behavior (runtime patterns), content (malicious instructions), and graph (relationship risk). Analysis runs in tiers: static signals, deterministic pattern checks, then AI semantic analysis when needed.
Identity checks source trust, behavior checks unusual runtime patterns, content checks for malicious instructions, and graph checks risky relationships to other entities. Looking at sub-scores helps you understand why an entity passed or failed.
brin performs risk assessments on external context before it reaches an AI agent. It scores that context for threats like prompt injection, hijacking, credential harvesting, and supply chain attacks, so teams can decide whether to block, review, or proceed safely.
No. A safe verdict means no significant risk signals were detected in this scan. It is not a formal guarantee; assessments are automated and point-in-time, so combine scores with your own controls and periodic re-checks.
Re-check before high-impact actions such as installs, upgrades, connecting MCP servers, executing remote code, or granting secrets. Use the API in CI or runtime gates so decisions are based on the latest scan.
Learn more in threat detection docs, how scoring works, and the API overview.
Assessments are automated and may contain errors. Findings are risk indicators, not confirmed threats. This is a point-in-time assessment; security posture can change.
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