Is climars.es safe?

cautionmedium confidence
56/100

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.

identity
90
behavior
60
content
37
graph
71

4 threat patterns detected

high

phishing

1 deceptive links where visible host does not match destination host

high

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)

medium

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='/'))

low

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))

API

curl https://api.brin.sh/domain/climars.es

FAQ: how to interpret this assessment

Common questions teams ask before deciding whether to use this domain in agent workflows.

Is climars.es safe for AI agents to use?

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.

How should I interpret the score and verdict?

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.

How does brin compute this domain score?

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.

What do identity, behavior, content, and graph mean for this domain?

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.

Why does brin scan packages, repos, skills, MCP servers, pages, and commits?

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.

Can I rely on a safe verdict as a full security guarantee?

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.

When should I re-check before using an entity?

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.

Last Scanned

March 25, 2026

Verdict Scale

safe80–100
caution50–79
suspicious20–49
dangerous0–19

Trust Graph

Disclaimer

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.

start scoring agent dependencies.

integrate brin in minutes — one GET request is all it takes. query the api, browse the registry, or download the full dataset.