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
TLS connection failed (connected=false, cert_valid=false) for a domain named xmsecu.com — 'ecu' suffix mimics credit union or financial institution branding. A legitimate financial site would have valid TLS. The inability to establish a secure connection combined with the financial-institution-style domain name is a strong indicator of a phishing or fraudulent site. (location: metadata.json: tls.connected=false, tls.cert_valid=false)
brand impersonation
The domain xmsecu.com uses the 'ecu' suffix commonly associated with credit unions (e.g., 'XM State Employees Credit Union' or similar). This pattern is frequently used to impersonate legitimate financial institutions and credit unions to harvest credentials or personal financial data. (location: metadata.json: domain=xmsecu.com)
credential harvesting
Combination of a financial-institution-mimicking domain name (xmsecu.com), failed TLS (no valid certificate), and empty page content strongly suggests a credential harvesting operation — either currently inactive/dormant or serving content conditionally to evade automated scanning. (location: metadata.json, page.html (empty), page-text.txt (empty))
hidden content
The page.html, page-text.txt, and page-hidden.txt files are all empty despite the site being reachable enough to have metadata collected. This indicates the site may be serving content conditionally (e.g., only to real browsers with JavaScript, specific user-agents, or geolocated visitors) to evade automated security scanners. (location: page.html (0 lines), page-text.txt (0 lines), page-hidden.txt (0 lines))
curl https://api.brin.sh/domain/xmsecu.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
xmsecu.com 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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