context safety score
A score of 32/100 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 'safebrowsing.apple' impersonates Apple Inc. by combining Apple's brand name with the trust-signaling term 'safebrowsing'. Apple's legitimate domain is apple.com; 'safebrowsing.apple' is not a valid Apple TLD or subdomain. This pattern is a classic brand impersonation tactic designed to deceive users and AI agents into trusting the domain as an official Apple security service. (location: domain: safebrowsing.apple)
phishing
The domain 'safebrowsing.apple' uses the trusted Apple brand combined with a security-themed subdomain ('safebrowsing') to create a convincing phishing lure. TLS connection failed (connected=false, cert_valid=false), meaning the site either does not serve valid HTTPS or the certificate is not trusted — a strong indicator of a malicious or misconfigured phishing infrastructure rather than a legitimate Apple service. (location: metadata.json: tls.connected=false, tls.cert_valid=false)
credential harvesting
A domain impersonating Apple's safe browsing service with no valid TLS certificate is highly consistent with a credential harvesting operation. Users or agents directed to this domain under the pretense of an Apple security check may be prompted to submit Apple ID credentials or other sensitive information. (location: domain: safebrowsing.apple; metadata.json: tls fields)
social engineering
The domain name 'safebrowsing.apple' is engineered to convey legitimacy and safety ('safebrowsing') while borrowing Apple's brand authority. This is a social engineering construct intended to lower the suspicion of both human users and AI agents by invoking a well-known, trusted technology brand in a security context. (location: domain: safebrowsing.apple)
curl https://api.brin.sh/domain/safebrowsing.appleCommon questions teams ask before deciding whether to use this domain in agent workflows.
safebrowsing.apple currently scores 32/100 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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