context safety score
A score of 48/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
tls connection failed
Could not establish TLS connection
brand impersonation
The domain 'zscalerthree.net' directly impersonates Zscaler, a well-known enterprise cybersecurity and zero-trust networking company. The pattern of appending a word ('three') to a brand name is a classic typosquatting and brandjacking technique used to deceive users and automated agents into trusting the domain. (location: domain: zscalerthree.net)
phishing
The combination of Zscaler brand impersonation via domain name and a non-functional TLS connection (connected=false, cert_valid=false) is consistent with a phishing or credential-harvesting infrastructure domain. Legitimate Zscaler services always serve valid HTTPS. The empty page content may indicate a dormant phishing page or a backend used for redirect chains. (location: domain: zscalerthree.net, metadata.json tls fields)
credential harvesting
Domains impersonating security vendors like Zscaler are frequently used for credential harvesting, targeting enterprise users who may be directed to fake SSO or VPN login portals. The empty page content is consistent with a backend harvesting endpoint or a domain awaiting payload deployment. (location: domain: zscalerthree.net)
malicious redirect
The domain returns no page content but resolves and has active infrastructure signals. This is consistent with a redirect-only domain used in multi-stage phishing or malware delivery chains, where the domain itself serves as a hop point rather than a final destination. (location: domain: zscalerthree.net, page.html (empty))
curl https://api.brin.sh/domain/zscalerthree.netCommon questions teams ask before deciding whether to use this domain in agent workflows.
zscalerthree.net currently scores 48/100 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.
integrate brin in minutes — one GET request is all it takes. query the api, browse the registry, or download the full dataset.