context safety score
A score of 30/100 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 'allegrolokalnie.38139fs72.sbs' directly incorporates 'allegro' and 'lokal' (referencing 'Allegro Lokalnie', the Polish e-commerce/classifieds platform) as a subdomain prefix on a randomly-generated third-party domain '38139fs72.sbs'. This is a classic brand impersonation pattern designed to deceive users into believing they are visiting a legitimate Allegro service. (location: domain: allegrolokalnie.38139fs72.sbs)
phishing
The domain construction (well-known brand name + 'lokal' subdomain on a disposable .sbs TLD with random-looking second-level domain) is highly consistent with phishing infrastructure targeting Allegro Lokalnie users. TLS connection failure suggests the site may be inactive, taken down, or misconfigured — all common traits of short-lived phishing domains. (location: domain: allegrolokalnie.38139fs72.sbs, metadata.json tls.connected=false)
malicious redirect
The .sbs TLD combined with a randomized SLD ('38139fs72') and brand-impersonating subdomain is a known pattern used in redirect chains and phishing kits. The domain may serve as a landing or redirect node in a multi-stage phishing or credential harvesting campaign targeting Allegro users. (location: domain: allegrolokalnie.38139fs72.sbs)
credential harvesting
Allegro Lokalnie is a Polish peer-to-peer marketplace. Fake lookalike domains for this platform are frequently used to harvest login credentials and payment information from buyers and sellers. The domain structure strongly indicates this use case. (location: domain: allegrolokalnie.38139fs72.sbs)
curl https://api.brin.sh/domain/allegrolokalnie.38139fs72.sbsCommon questions teams ask before deciding whether to use this domain in agent workflows.
allegrolokalnie.38139fs72.sbs currently scores 30/100 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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