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 'awsdns-36.net' mimics Amazon Web Services DNS infrastructure (AWS Route 53 uses 'awsdns' in its legitimate nameserver hostnames, e.g., ns-123.awsdns-45.com). The .net TLD and numeric suffix pattern is designed to appear as an authoritative AWS DNS endpoint, potentially deceiving users or automated systems into trusting it as a legitimate AWS service. (location: domain: awsdns-36.net)
phishing
The domain closely imitates Amazon Web Services naming conventions used for Route 53 DNS servers. This pattern is commonly used in phishing infrastructure to impersonate AWS services, harvest credentials, or serve as a convincing C2 or redirect domain targeting cloud-savvy users and automated agents. (location: domain: awsdns-36.net)
malicious redirect
TLS connection failed (connected=false, cert_valid=false), meaning the site either does not serve HTTPS properly or is down. A domain impersonating AWS DNS infrastructure with no valid TLS certificate is suspicious — it may be used for DNS hijacking, traffic interception, or as a redirect hop in a malicious chain rather than as a direct content-serving site. (location: metadata.json: tls block)
social engineering
The domain 'awsdns-36.net' is engineered to exploit implicit trust in AWS infrastructure naming. Automated agents, scripts, or security tools that pattern-match on 'awsdns' as a trusted AWS indicator could be deceived into whitelisting or trusting this domain, constituting a social engineering vector targeting both humans and AI-driven security systems. (location: domain: awsdns-36.net)
curl https://api.brin.sh/domain/awsdns-36.netCommon questions teams ask before deciding whether to use this domain in agent workflows.
awsdns-36.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.
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