context safety score
A score of 38/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
encoded payload
suspicious base64-like blobs detected in page content
brand impersonation
The domain weborama-tech.ru is impersonating the legitimate French ad-tech company Weborama (weborama.com). The HTML contains data-wf-domain="www.weborama.com", the page title is "Weborama - From Data to Value", and all branding, logos, and content are cloned from the legitimate site. The .ru TLD combined with a near-identical brand name is a classic typosquat/brand-impersonation pattern targeting Weborama's users and clients. (location: page.html:1, metadata.json domain field)
phishing
The site presents a pixel-perfect clone of the legitimate Weborama website (weborama.com) on a .ru domain (weborama-tech.ru). The navigation includes a 'Login' link, which is a high-risk phishing vector — users believing they are on the real site may submit credentials. The cloned site replicates the full visual identity to deceive visitors. (location: page.html:3 (Login link in nav), page-text.txt:1)
credential harvesting
A 'Login' call-to-action is present in the navigation of this cloned/impersonation site. Any login form linked from this page would harvest credentials from users who believe they are accessing the legitimate Weborama platform. (location: page-text.txt:1 (Login Login in nav text), page.html:3)
malicious redirect
All internal navigation links (href="/", href="/data", href="/solutions", etc.) and the logo link resolve relative to weborama-tech.ru rather than weborama.com. Users following any site link remain on the malicious domain rather than being routed to the legitimate site, keeping victims within the attacker-controlled environment. (location: page.html:3 (nav links))
curl https://api.brin.sh/domain/weborama-tech.ruCommon questions teams ask before deciding whether to use this domain in agent workflows.
weborama-tech.ru currently scores 38/100 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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