context safety score
A score of 40/100 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 'nice-protect.com' uses security-themed branding ('protect') which is a common phishing tactic to establish false trust. The site failed TLS connection (connected=false, cert_valid=false), meaning it cannot serve HTTPS content securely — highly anomalous for any legitimate security or protection service. (location: metadata.json: domain, tls fields)
brand impersonation
The domain name 'nice-protect.com' mimics the naming conventions of legitimate cybersecurity or protection services. Combined with a young domain age (261 days) and failed TLS, this pattern is consistent with a lookalike/impersonation domain. (location: metadata.json: domain, whois.domain_age_days)
social engineering
The domain name incorporates 'protect' as a trust signal, a classic social engineering technique to lower user guard. The site appears to render no content (empty page.html, page-text.txt, page-hidden.txt), which may indicate cloaking — serving different content to bots/crawlers than to real users. (location: metadata.json: domain; page.html, page-text.txt, page-hidden.txt (all empty))
hidden content
All page content files (page.html, page-text.txt, page-hidden.txt) are completely empty despite the domain resolving and having a detectable presence. This is a strong indicator of cloaking: the site detects automated scanners and withholds malicious content, serving it only to real human victims. This technique is widely used in phishing and credential harvesting campaigns. (location: page.html (0 bytes), page-text.txt (0 bytes), page-hidden.txt (0 bytes))
curl https://api.brin.sh/domain/nice-protect.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
nice-protect.com currently scores 40/100 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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