context safety score
A score of 44/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
tls connection failed
Could not establish TLS connection
phishing
Domain 'bank.in' is a generic banking-themed domain with no TLS connection possible (TLS connected=false, cert_valid=false). A domain named 'bank.in' without a valid TLS certificate is a strong indicator of a phishing or fraudulent banking site attempting to impersonate legitimate banking institutions. (location: metadata.json: domain=bank.in, tls.connected=false, tls.cert_valid=false)
brand impersonation
The domain 'bank.in' uses the generic term 'bank' as the primary domain name, which is a common tactic to impersonate or appear affiliated with legitimate banking brands without targeting a specific institution. This broad impersonation can deceive users into believing the site is an official or trusted banking portal. (location: metadata.json: domain=bank.in)
phishing
TLS/SSL certificate is invalid and the connection failed entirely (connected=false, cert_valid=false, san_match=false). Legitimate banking sites universally use valid TLS certificates. The absence of a valid certificate on a banking-themed domain significantly increases phishing risk and means any credentials entered would be transmitted insecurely. (location: metadata.json: tls object - connected=false, cert_valid=false, san_match=false)
curl https://api.brin.sh/domain/bank.inCommon questions teams ask before deciding whether to use this domain in agent workflows.
bank.in currently scores 44/100 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.
integrate brin in minutes — one GET request is all it takes. query the api, browse the registry, or download the full dataset.