context safety score
A score of 39/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
malicious redirect
Meta refresh redirect after 2 seconds to https://case.metaforbusiness-partners.com/ — a domain impersonating Meta (Facebook) for Business. The redirect is silent with no visible page content, designed to funnel users to a spoofed Meta business portal without their awareness. (location: page.html:4 — <meta http-equiv="refresh" content="2; url = https://case.metaforbusiness-partners.com/">)
brand impersonation
Redirect destination domain 'metaforbusiness-partners.com' closely mimics Meta's legitimate 'business.facebook.com' or 'meta.com' brand. The subdomain 'case.' and path structure suggest impersonation of a Meta for Business case/support portal, likely to harvest credentials or business account data. (location: page.html:4 — redirect URL: https://case.metaforbusiness-partners.com/)
phishing
The page serves as a transparent redirect stage in a phishing chain: an empty, content-free Firebase-hosted page auto-redirects to a brand-impersonating domain. This two-stage architecture is a classic phishing lure pattern used to evade URL scanners that only check the initial landing URL. (location: page.html — entire page functions as phishing redirect stage)
hidden content
The page body is completely empty (no visible text, no UI elements), yet performs an automatic redirect. All functional behavior is hidden from the user. page-text.txt confirms zero visible content, meaning the redirect is fully concealed from casual inspection. (location: page.html:6-7 — empty <body> with redirect occurring via <head> meta tag)
curl https://api.brin.sh/domain/load-page-genius-1000542978.web.appCommon questions teams ask before deciding whether to use this domain in agent workflows.
load-page-genius-1000542978.web.app currently scores 39/100 with a suspicious verdict and low 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.
integrate brin in minutes — one GET request is all it takes. query the api, browse the registry, or download the full dataset.