context safety score
A score of 56/100 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
prompt injection
The cookie consent banner HTML (rendered inside a <script type='text/template'> block and also directly in the DOM) contains verbatim ChatGPT conversation markup including div classes 'min-h-8 text-message', 'data-message-author-role="assistant"', 'data-message-id', and 'data-message-model-slug="gpt-4o"' / 'gpt-4o-mini'. This is ChatGPT UI scaffolding injected into the page content, strongly indicating the cookie consent descriptions were copy-pasted from a ChatGPT session with the full assistant message wrapper HTML included. An AI agent scraping this page would encounter 'data-message-author-role="assistant"' signals that could confuse role boundaries or be exploited to inject false assistant context into agent memory/context windows. (location: page.html lines 1250-1381 (cky-notice-des and cky-accordion-header-des blocks); also duplicated in ckyBannerTemplate script block lines 1371-1503)
hidden content
The header logo anchor tag has an empty href ('') and empty text content with no visible label beyond the aria-label, and multiple footer social media links (Instagram, Facebook, Tumblr, Twitter) all point to href='/' (the homepage) rather than actual social profiles. This is deceptive link construction: icons labeled as social network links that do not navigate to those networks. The Tier 2 scan flagged 1 deceptive link count, consistent with this pattern. (location: page.html line 135 (logo anchor href=''), lines 1240-1251 (social links all href='/'))
hidden content
The close menu icon and mobile logo placeholders in the header contain empty HTML comment placeholders ('<!-- icon menu -->', '<!-- logo mobile -->') with no actual content, and images are loaded from the third-party domain codigobeta.es (the web agency) rather than from climars.es. While this is a common agency pattern, static assets being loaded cross-domain from a non-CDN third party introduces a supply-chain dependency where codigobeta.es could modify delivered assets. (location: page.html lines 138, 159-165, 1241-1358 (codigobeta.es asset references))
curl https://api.brin.sh/domain/climars.esCommon questions teams ask before deciding whether to use this domain in agent workflows.
climars.es currently scores 56/100 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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