context safety score
A score of 27/100 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 'strpssts-ana.com' appears to be a typosquat or obfuscated imitation of 'Stripe' (strp) combined with obscuring characters. The domain structure is consistent with phishing infrastructure targeting Stripe users or brand impersonation. (location: metadata.json:domain)
brand impersonation
The domain 'strpssts-ana.com' contains 'strp' which is a likely abbreviation/obfuscation of 'Stripe', a major payment processor. Combined with 'ssts' and 'ana', the domain pattern is consistent with impersonation of Stripe or a Stripe-related service to deceive users. (location: metadata.json:domain)
phishing
TLS is not connected and certificate is invalid (connected=false, cert_valid=false). A site soliciting credentials or payments with no valid TLS is a strong phishing indicator, especially combined with a suspicious domain name. (location: metadata.json:tls)
credential harvesting
Domain age of only 167 days combined with invalid TLS, unknown hosting reputation, and a domain name obfuscating a major payment brand (Stripe) is consistent with a credential harvesting site set up recently for a targeted campaign. (location: metadata.json:whois/domain_age_days, metadata.json:tls, metadata.json:hosting)
curl https://api.brin.sh/domain/strpssts-ana.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
strpssts-ana.com currently scores 27/100 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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