context safety score
A score of 64/100 indicates minor risk signals were detected. The entity may be legitimate but has characteristics that warrant attention.
tls connection failed
Could not establish TLS connection
phishing
TLS connection failed (connected=false, cert_valid=false, san_match=false) for a site presenting itself as an education platform. Serving content over an invalid or absent TLS certificate is a strong phishing indicator, as it suggests either a hastily stood-up site or deliberate avoidance of certificate scrutiny. (location: metadata.json: tls fields)
brand impersonation
The subdomain 'education.trendagent.ae' combines an authoritative-sounding education label with a brand-like name ('trendagent') under the .ae TLD. The empty page content combined with a live domain and failed TLS suggests the site may be in a pre-deployment or cloaking state, potentially impersonating a legitimate education or financial-services brand. (location: metadata.json: domain / url)
social engineering
The domain name 'education.trendagent.ae' is constructed to appear trustworthy (education subdomain + agent/trend branding), a classic social-engineering pattern used to lend legitimacy to a site before content is deployed or to serve content selectively to targeted visitors. (location: metadata.json: domain)
curl https://api.brin.sh/domain/education.trendagent.aeCommon questions teams ask before deciding whether to use this domain in agent workflows.
education.trendagent.ae currently scores 64/100 with a caution 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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