context safety score
A score of 32/100 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
Domain 'awsdns-cn-16.biz' closely mimics Amazon Web Services (AWS) DNS infrastructure naming conventions (awsdns). The .biz TLD combined with a fake AWS DNS subdomain pattern is a strong indicator of brand impersonation targeting AWS customers or services. Legitimate AWS DNS domains use awsdns-XX.{com,net,org,co.uk} TLDs, never .biz. (location: domain: awsdns-cn-16.biz)
phishing
The domain impersonates AWS DNS infrastructure (awsdns-cn-16.biz) using a pattern consistent with typosquatting/lookalike domains used in phishing campaigns targeting cloud infrastructure users, developers, or automated systems that interact with AWS DNS endpoints. (location: domain: awsdns-cn-16.biz)
malicious redirect
TLS connection failed (connected=false, cert_valid=false) on a domain mimicking AWS DNS infrastructure. This is consistent with a domain used for DNS hijacking, traffic interception, or malicious redirection of requests intended for legitimate AWS DNS resolvers. Attackers may use such domains to redirect DNS queries or deceive automated agents/tools that resolve AWS-style hostnames. (location: metadata.json: tls.connected=false, tls.cert_valid=false)
social engineering
The domain name 'awsdns-cn-16.biz' is crafted to appear as a legitimate AWS DNS server (AWS names its resolvers e.g. ns-1234.awsdns-56.com). The inclusion of 'cn' (suggesting China region) and a sequential number mimics real AWS resolver naming, potentially deceiving administrators, developers, or AI agents into trusting or interacting with this domain as if it were genuine AWS infrastructure. (location: domain: awsdns-cn-16.biz)
curl https://api.brin.sh/domain/awsdns-cn-16.bizCommon questions teams ask before deciding whether to use this domain in agent workflows.
awsdns-cn-16.biz currently scores 32/100 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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