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
brand impersonation
The domain 'gstatic.cn' directly impersonates Google's static content delivery domain 'gstatic.com'. The .cn TLD substitution is a well-known typosquatting/brand impersonation technique used to deceive users and AI agents into trusting content or resources served from this domain as if they originated from Google infrastructure. (location: domain: gstatic.cn)
malicious redirect
TLS connection failed (connected=false, cert_valid=false, san_match=false) on a domain impersonating a major CDN/static asset host. This configuration is consistent with a domain used for redirect chains, traffic interception, or serving content without valid HTTPS — potentially routing victims through an insecure or attacker-controlled channel. (location: metadata.json: tls object)
phishing
The combination of a Google brand-impersonating domain (gstatic.cn vs gstatic.com), failed TLS, and no blocklist hit is characteristic of a phishing infrastructure domain that has not yet been reported — potentially newly activated or used in targeted campaigns. The domain age of 12880 days (~35 years) is anomalous and likely spoofed or represents a re-registered domain, which is a common evasion tactic. (location: metadata.json: domain, whois.domain_age_days, tls)
curl https://api.brin.sh/domain/gstatic.cnCommon questions teams ask before deciding whether to use this domain in agent workflows.
gstatic.cn 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.
integrate brin in minutes — one GET request is all it takes. query the api, browse the registry, or download the full dataset.