context safety score
A score of 62/100 indicates minor risk signals were detected. The entity may be legitimate but has characteristics that warrant attention.
phishing
1 deceptive links where visible host does not match destination host
malicious redirect
The page is hosted at eshop.tomket.com but presents itself as NejlevnejsiPNEU.cz with a full brand identity, logo, and domain references to www.nejlevnejsipneu.cz. The HTML title, meta description, Google Analytics config (cookie_domain: '.www.nejlevnejsipneu.cz'), and all visible branding are for nejlevnejsipneu.cz, while the actual serving domain is eshop.tomket.com. This domain mismatch constitutes a redirect/domain-spoofing scenario where the crawled URL differs from the presented brand domain. (location: page.html:9, page.html:18, metadata.json:domain)
brand impersonation
The page served from eshop.tomket.com fully impersonates the NejlevnejsiPNEU.cz brand, including its logo, title, meta description, contact details, and copyright notice. While tomket.com appears to be the parent company operating nejlevnejsipneu.cz (a legitimate relationship), users navigating to eshop.tomket.com are presented with a site that visually and textually identifies entirely as a different domain (nejlevnejsipneu.cz). This could confuse users about which entity they are transacting with. (location: page.html:9-10, page.html:162, page.html:768)
social engineering
The page uses urgency-based messaging to pressure users into purchasing tires immediately: 'Nedostatek letních pneumatik!' (Shortage of summer tires!) with a claim that a shortage is expected due to trade wars. This is a classic artificial scarcity/urgency social engineering tactic to drive impulsive purchasing decisions. (location: page.html:172, page.html:306-308, page-text.txt:87, page-text.txt:215-216)
curl https://api.brin.sh/domain/eshop.tomket.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
eshop.tomket.com currently scores 62/100 with a caution verdict and medium 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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