context safety score
A score of 46/100 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
The domain 'apple-dns.net' directly incorporates the 'Apple' brand name combined with 'dns' to appear as a legitimate Apple infrastructure or DNS service. This is a classic brand impersonation pattern designed to deceive users and automated systems into trusting the domain as affiliated with Apple Inc. (location: domain: apple-dns.net)
phishing
The domain 'apple-dns.net' uses a .net TLD combined with the Apple brand name, a common phishing technique to register lookalike domains that impersonate official Apple services (apple.com). The TLS connection failed (connected=false, cert_valid=false), indicating the site may be non-operational, parked, or actively avoiding TLS inspection — consistent with a phishing or malicious infrastructure domain. (location: domain: apple-dns.net, TLS status: connected=false)
malicious redirect
The domain is unresolvable or non-responsive (TLS connected=false, no page content retrieved), which is consistent with a parked or dormant domain that may be used as a redirect hop or infrastructure node in a malicious redirect chain. Apple-branded domains not operated by Apple are frequently used as intermediary redirectors. (location: domain: apple-dns.net, metadata.json tls.connected=false)
hidden content
Page HTML and visible text content are both empty despite the domain being active enough to appear in scan context. This absence of content on a brand-impersonating domain may indicate cloaking behavior — serving different content to scanners vs. real users, or content gated behind specific request headers or user-agent strings. (location: page.html (empty), page-text.txt (empty), page-hidden.txt (empty))
curl https://api.brin.sh/domain/apple-dns.netCommon questions teams ask before deciding whether to use this domain in agent workflows.
apple-dns.net currently scores 46/100 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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