context safety score
A score of 49/100 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 conditionally redirects based on referrer or user-agent
hidden content
The page body is completely empty with no visible content (page-text.txt is blank, <body> tag is empty). The page renders nothing to users while executing JavaScript logic. This is consistent with a bot-check interstitial or cloaking technique where real content is withheld pending client-side validation. (location: page.html:<body> (line 150-152))
malicious redirect
The qauth validation success callback (qauth_handle_validate_success) performs an unconditional window.location.replace() redirect after a configurable timeout (window.qauth_reload_after, default 10ms). The redirect appends UTM tracking parameters including utm_referrer containing the full document.referrer URL, then replaces the current location. This harvests referrer data and silently redirects users. The external script /__qrator/qauth_utm_v2d_v9118.js controls the trigger for this redirect. (location: page.html:135-145)
hidden content
Core page logic is offloaded to an external script loaded from /__qrator/qauth_utm_v2d_v9118.js. This script is not present in the scanned assets and its behavior is unauditable. The qrator path prefix is associated with Qrator DDoS protection services but can also be used to deliver arbitrary JavaScript payloads to passing clients. The script controls the qauth_handle_validate_success callback, qauth_reload_after timing, and qauth_referrer_maxlen parameters. (location: page.html:7 (<script src="/__qrator/qauth_utm_v2d_v9118.js">))
social engineering
The meta tag 'referrer: no-referrer' is set, suppressing the Referer header on outbound requests from this page. Combined with the active referrer harvesting via utm_referrer query parameter injection, the page collects inbound referrer data while preventing downstream sites from seeing dns-shop.ru as the source, obscuring the traffic chain. (location: page.html:5 and page.html:7 (<meta name="referrer" content="no-referrer">))
curl https://api.brin.sh/domain/dns-shop.ruCommon questions teams ask before deciding whether to use this domain in agent workflows.
dns-shop.ru 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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