context safety score
A score of 40/100 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 'aws-prd.net' closely mimics Amazon Web Services (AWS) by using 'aws' as a prefix with a non-Amazon TLD (.net) and appending '-prd' (likely abbreviation for 'production'), a pattern consistent with AWS brand impersonation targeting users or automated agents expecting legitimate AWS infrastructure. (location: metadata.json: domain=aws-prd.net)
phishing
The domain 'aws-prd.net' is structurally consistent with a phishing site impersonating AWS. TLS is not connected and cert is invalid (connected=false, cert_valid=false), meaning the site either failed to serve HTTPS or is unreachable — both common indicators of a staged phishing domain or one in early deployment. The combination of AWS brand mimicry and broken TLS is a high-confidence phishing signal. (location: metadata.json: tls.connected=false, tls.cert_valid=false)
credential harvesting
Domains impersonating AWS (aws-prd.net) are frequently used to harvest AWS access keys, IAM credentials, or console login credentials. The non-official TLD combined with AWS branding is a known tactic for credential harvesting campaigns targeting cloud users and CI/CD pipelines. (location: metadata.json: domain=aws-prd.net)
curl https://api.brin.sh/domain/aws-prd.netCommon questions teams ask before deciding whether to use this domain in agent workflows.
aws-prd.net currently scores 40/100 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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