context safety score
A score of 39/100 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
phishing
1 deceptive links where visible host does not match destination host
malicious redirect
script/meta redirect patterns detected in page source
cloaking
Page conditionally redirects based on referrer or user-agent
malicious redirect
The page implements a back-button hijacking script using history.pushState() called twice to duplicate history entries, combined with window.onpopstate to intercept browser back navigation. When a user attempts to navigate back, they are silently redirected to a randomly selected URL from a hardcoded list of internal pages rather than their actual previous page. This traps users on the site and prevents normal browser navigation. (location: page.html - inline <script> block: backredirect() function with history.pushState and window.onpopstate)
social engineering
The site uses the '.ai' TLD to lend a technology/legitimacy veneer to an adult content aggregator site. The domain 'buceta.ai' is designed to appear as an AI-powered platform, potentially lowering user guard and increasing trust. The title and branding claim to be the 'largest and best' site with 'daily updates', using superlatives to build false authority. (location: metadata.json - domain: buceta.ai; page.html - <title> and meta description)
hidden content
A full secondary navigation menu (Categorias sidebar with ~35 category links including Beeg, Brazzers, Cam4, Chaturbate, Eporner, Pornhub, Redtube, XNXX, Xvideos) is rendered in a hidden/off-canvas state, not directly visible to users but present in the DOM. This content is duplicated from visible navigation, suggesting SEO keyword stuffing via hidden elements. (location: page-hidden.txt - line 1; page.html - hidden sidebar nav)
curl https://api.brin.sh/domain/buceta.aiCommon questions teams ask before deciding whether to use this domain in agent workflows.
buceta.ai currently scores 39/100 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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