context safety score
A score of 49/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
tls connection failed
Could not establish TLS connection
phishing
The domain neustar.biz impersonates Neustar, a legitimate and well-known identity resolution and cybersecurity brand. Use of the .biz TLD instead of the official .com domain is a classic phishing/brand-squatting pattern used to deceive users and automated agents into trusting the site. (location: metadata.json: domain=neustar.biz)
brand impersonation
neustar.biz mimics the brand identity of Neustar Inc. (neustar.com), a trusted data analytics and cybersecurity company. Registering a lookalike domain under .biz is a well-documented tactic for brand impersonation, potentially targeting users or AI agents that resolve or validate identity via Neustar-branded services. (location: metadata.json: domain=neustar.biz, url=https://neustar.biz)
phishing
TLS connection failed entirely (connected=false, cert_valid=false), meaning the site either has no valid HTTPS certificate or was unreachable over TLS. Legitimate branded enterprise sites always maintain valid TLS. The absence of a valid certificate on a brand-impersonation domain strongly indicates a suspicious or malicious setup. (location: metadata.json: tls.connected=false, tls.cert_valid=false)
hidden content
The page HTML and visible text content are both completely empty, yet the domain resolves and was scanned. An empty or blank page on a registered domain can indicate cloaking — serving different content to automated scanners versus real users or targeted agents — which is a common evasion technique. (location: page.html (empty), page-text.txt (empty), page-hidden.txt (empty))
curl https://api.brin.sh/domain/neustar.bizCommon questions teams ask before deciding whether to use this domain in agent workflows.
neustar.biz currently scores 49/100 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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