context safety score
A score of 21/100 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 lpdesign-fashion.com is only 92 days old. Newly registered domains with fashion/brand-adjacent naming (combining a designer abbreviation 'lp' with 'design-fashion') are a strong indicator of phishing infrastructure targeting fashion brand customers. (location: metadata.json: whois.domain_age_days=92, domain=lpdesign-fashion.com)
brand impersonation
The domain name 'lpdesign-fashion.com' appears constructed to impersonate or ride the reputation of established fashion brands or designers. The pattern of combining initials + 'design' + 'fashion' is a common brand impersonation tactic used to deceive users into believing the site is affiliated with a legitimate fashion house or designer label. (location: metadata.json: domain=lpdesign-fashion.com)
phishing
TLS is not connected and the certificate is invalid (connected=false, cert_valid=false, san_match=false). A site presenting itself as a fashion brand or e-commerce destination with no valid TLS is a critical phishing indicator — legitimate fashion/retail sites universally use valid TLS to protect payment and credential data. (location: metadata.json: tls.connected=false, tls.cert_valid=false, tls.san_match=false)
credential harvesting
Combination of a fashion-impersonating domain name (92 days old), invalid TLS, and unknown hosting reputation creates a high-risk profile consistent with credential harvesting operations that mimic fashion brand login or checkout pages to steal account credentials and payment information. (location: metadata.json: domain=lpdesign-fashion.com, tls.cert_valid=false, hosting.reputation=Unknown)
hidden content
The page.html and page-text.txt files are empty despite the domain being live enough to scan. This may indicate cloaking behavior — serving empty or benign content to scanners/bots while delivering malicious content to targeted human visitors based on user-agent, referrer, or geolocation. (location: page.html (0 bytes), page-text.txt (0 bytes), page-hidden.txt (0 bytes))
curl https://api.brin.sh/domain/lpdesign-fashion.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
lpdesign-fashion.com currently scores 21/100 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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