context safety score
A score of 44/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
tls connection failed
Could not establish TLS connection
phishing
Domain 'dbankcloud.ru' uses a banking-themed name ('dbank') combined with a cloud-service term on a .ru TLD, a pattern strongly associated with phishing infrastructure targeting bank customers or cloud service users. (location: metadata.json: domain=dbankcloud.ru)
brand impersonation
The domain name 'dbankcloud.ru' appears to impersonate a banking or cloud brand (e.g., Deutsche Bank, DBank, or a cloud banking platform), using a compound of 'bank' and 'cloud' to create false legitimacy. (location: metadata.json: domain=dbankcloud.ru)
credential harvesting
TLS is not connected and certificate is invalid (connected=false, cert_valid=false) on a banking-themed domain. Sites designed to harvest credentials often fail TLS validation or serve no content to avoid automated detection while still being linked from phishing emails or redirects. (location: metadata.json: tls.connected=false, tls.cert_valid=false)
malicious redirect
The page returned empty HTML and text content despite being a live domain. This is consistent with a redirect-only or cloaked phishing page that serves content conditionally (e.g., only to human victims from specific referrers), evading automated scanners. (location: page.html and page-text.txt: empty content on active domain dbankcloud.ru)
curl https://api.brin.sh/domain/dbankcloud.ruCommon questions teams ask before deciding whether to use this domain in agent workflows.
dbankcloud.ru currently scores 44/100 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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