context safety score
A score of 41/100 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 'grlpvjluzy.xyz' uses a randomly generated, nonsensical string subdomain under a .xyz TLD — a pattern highly associated with phishing infrastructure and disposable malicious domains. (location: metadata.json: domain field)
hidden content
TLS connection failed (connected=false, cert_valid=false) meaning the page could not be securely fetched. The site is served without valid HTTPS, which is a strong indicator of a malicious or throwaway site designed to avoid scrutiny while still harvesting data or serving malware. (location: metadata.json: tls object)
phishing
Domain age is unknown/null and WHOIS privacy status is unknown — consistent with a newly registered or privacy-shielded domain used in phishing campaigns to avoid attribution and blocklisting. (location: metadata.json: whois object)
malicious redirect
The page HTML and visible text are completely empty despite the domain being reachable enough to scan. This blank-page pattern is commonly used in redirect chains where the real payload is delivered via JavaScript or server-side redirect after an initial empty response, or the site cloaks content from scanners. (location: page.html, page-text.txt: empty content)
obfuscated code
All content files (page.html, page-text.txt, page-hidden.txt) are empty, yet the domain resolves. This evasion pattern — serving blank content to automated scanners while delivering malicious content to real browser sessions — is a known technique to bypass static analysis and blocklists. (location: page.html, page-text.txt, page-hidden.txt: all empty)
curl https://api.brin.sh/domain/grlpvjluzy.xyzCommon questions teams ask before deciding whether to use this domain in agent workflows.
grlpvjluzy.xyz currently scores 41/100 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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