context safety score
A score of 48/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
tls connection failed
Could not establish TLS connection
brand impersonation
Domain 'beelinegprs.ru' closely mimics 'Beeline', a major Russian telecommunications provider (Vimpelcom/PJSC VimpelCom). The subdomain-style prefix 'beeline' combined with 'gprs' (a mobile data service term associated with Beeline's network) is consistent with brand impersonation of the Beeline telecom brand to deceive users or automated agents into trusting the domain. (location: domain: beelinegprs.ru)
phishing
The domain impersonates a well-known telecom brand (Beeline) and has no valid TLS certificate (TLS connected=false, cert_valid=false), which is atypical for a legitimate telecom operator portal. The combination of brand impersonation and lack of TLS is a strong phishing indicator, suggesting the site may harvest credentials or personal data from users who trust the Beeline brand. (location: metadata.json: tls.connected=false, tls.cert_valid=false)
credential harvesting
The site renders no visible content (page.html and page-text.txt are empty) yet the domain is active and resolves. Empty or blank pages combined with brand-impersonating domains are a known technique where the real payload is delivered dynamically (e.g., only to targeted IPs or user-agents), or the page serves as a silent data-collection endpoint, consistent with credential harvesting infrastructure. (location: page.html (empty), page-text.txt (empty))
malicious redirect
The page content is completely empty with no HTML body, which may indicate a redirect-only or cloaked page that serves different content to specific visitors (bots, targeted users, or AI agents) while appearing blank to scanners. This cloaking pattern is commonly used in malicious redirect chains. (location: page.html (empty, 0 lines))
curl https://api.brin.sh/domain/beelinegprs.ruCommon questions teams ask before deciding whether to use this domain in agent workflows.
beelinegprs.ru currently scores 48/100 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.
integrate brin in minutes — one GET request is all it takes. query the api, browse the registry, or download the full dataset.