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 'govdnr.ru' uses the 'gov' prefix to impersonate a government entity while using a .ru TLD. This pattern is characteristic of sites attempting to appear as official government resources (e.g., DNR/Donetsk People's Republic or a fabricated government agency) to deceive users into trusting the site. (location: domain: govdnr.ru)
phishing
The combination of a government-impersonating domain name ('govdnr.ru'), failed TLS connection (connected=false, cert_valid=false), and no retrievable page content is consistent with a phishing infrastructure site — potentially dormant, under construction, or actively blocking automated scanners while serving malicious content to targeted victims. (location: metadata.json: tls.connected=false, tls.cert_valid=false)
malicious redirect
The site returned no HTML content despite being reachable enough to have metadata collected. This blank-page pattern is commonly used in redirect chains where the real payload is delivered via JavaScript redirects, server-side redirects, or user-agent/geo-targeting — meaning automated scanners see nothing while targeted users are redirected to malicious destinations. (location: page.html: empty, page-text.txt: empty)
hidden content
Despite the domain being active and metadata being collectible, all content files (page.html, page-text.txt, page-hidden.txt) are completely empty. This suggests content cloaking — the server is deliberately withholding content from the scanning agent while potentially serving malicious content to real users or specific targets. (location: page.html: 0 bytes, page-text.txt: 0 bytes, page-hidden.txt: 0 bytes)
curl https://api.brin.sh/domain/govdnr.ruCommon questions teams ask before deciding whether to use this domain in agent workflows.
govdnr.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.
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