context safety score
A score of 40/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
malicious redirect
script/meta redirect patterns detected in page source
cloaking
Page checks user-agent for bot/crawler strings to serve different content
cloaking
Page conditionally redirects based on referrer or user-agent
js obfuscation
JavaScript uses Function constructor for runtime code generation
brand impersonation
The page title and OG metadata explicitly identify this as 'Copy of Умный дом Ujin' (Copy of Ujin Smart Home). The og:title tag reads 'Copy of Ujin' — a strong indicator this is an unauthorized clone/copy of the legitimate Ujin (ujin.ru) smart home platform, served from a third-party domain mysmartflat.ru rather than the official domain. (location: page.html, <meta property='og:title' content='Copy of Умный дом Ujin' />)
social engineering
The site impersonates the Ujin smart home brand with full branding (logos, product imagery, IoT device listings, app store links) to appear as an official Ujin product page, potentially deceiving users into submitting contact/lead forms or downloading apps under false pretenses. (location: page.html — full page content, title: 'Система умный дом от производителя | Ujin')
hidden content
The VK Pixel noscript tracking image uses 'position:fixed; left:-999px' to hide a 1x1 tracking pixel off-screen, a technique used to conceal tracking beacons from visual inspection. Similarly, the Yandex Metrika noscript pixel uses 'position:absolute; left:-9999px'. (location: page.html — <noscript><img src='https://vk.com/rtrg?p=VK-RTRG-1092814-eqzq8' style='position:fixed; left:-999px;' /> and <img src='https://mc.yandex.ru/watch/55570948' style='position:absolute; left:-9999px;' />)
curl https://api.brin.sh/domain/mysmartflat.ruCommon questions teams ask before deciding whether to use this domain in agent workflows.
mysmartflat.ru currently scores 40/100 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.
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