context safety score
A score of 41/100 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 huobi.pro impersonates the legitimate Huobi cryptocurrency exchange (huobi.com/htx.com) by using the brand name with a .pro TLD. This is a classic typosquatting/brand impersonation pattern targeting crypto users who may enter credentials or funds. (location: domain: huobi.pro)
phishing
The domain replicates the Huobi brand on a non-official TLD (.pro) with a failed TLS connection (connected=false, cert_valid=false, san_match=false), consistent with a phishing site that may serve credential-harvesting login forms to unsuspecting users or block automated analysis. (location: domain: huobi.pro, TLS metadata)
credential harvesting
Cryptocurrency exchange impersonation domains are routinely used to harvest login credentials and 2FA tokens. The combination of brand impersonation and invalid TLS strongly suggests this infrastructure is designed to capture user credentials for the real Huobi platform. (location: domain: huobi.pro)
malicious redirect
The page returns empty content to crawlers (page.html and page-text.txt are blank) while the domain is live, a common technique used by phishing sites to evade automated scanners while serving malicious content to real browser sessions, potentially including redirects to credential-harvesting pages. (location: page.html, page-text.txt (empty content))
curl https://api.brin.sh/domain/huobi.proCommon questions teams ask before deciding whether to use this domain in agent workflows.
huobi.pro currently scores 41/100 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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