context safety score
A score of 20/100 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 'allegrolokalnie.23849441.xyz' impersonates Allegro Lokalnie, a major Polish e-commerce marketplace. The subdomain 'allegrolokalnie' directly mimics the legitimate brand name 'Allegro Lokalnie' while hosted under a suspicious numeric domain '23849441.xyz', a classic typosquatting/brand-hijacking pattern used for phishing. (location: domain: allegrolokalnie.23849441.xyz)
phishing
The combination of brand impersonation of a major e-commerce platform (Allegro Lokalnie), TLS connection failure (connected=false, cert_valid=false), unknown domain age, unknown hosting reputation, and a randomly-numbered .xyz TLD are strong composite indicators of an active phishing site targeting Polish e-commerce users. (location: metadata.json: tls, domain fields)
credential harvesting
Sites impersonating Allegro Lokalnie typically harvest login credentials, payment information, or personal data by mimicking the legitimate platform's login and transaction flows. The infrastructure signals (invalid TLS, opaque registrar, numeric .xyz domain) are consistent with credential harvesting operations. (location: domain: allegrolokalnie.23849441.xyz)
malicious redirect
The domain uses a numeric subdomain pattern ('23849441.xyz') commonly associated with redirect chains and fast-flux infrastructure used in phishing campaigns. TLS failure and inability to connect suggest the page may be part of a redirect or dead-drop phishing chain. (location: metadata.json: tls.connected=false, domain structure)
curl https://api.brin.sh/domain/allegrolokalnie.23849441.xyzCommon questions teams ask before deciding whether to use this domain in agent workflows.
allegrolokalnie.23849441.xyz currently scores 20/100 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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