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
malicious redirect
script/meta redirect patterns detected in page source
cloaking
Page conditionally redirects based on referrer or user-agent
malicious redirect
Page immediately redirects all visitors via window.location.href after a 1-second delay (setTimeout). The destination URL is dynamically constructed from the referrer and cookie values, meaning the redirect target is not static or auditable. This is a classic cloaking/redirect gate used to send users (or bots) to different destinations based on traffic source. (location: page.html:44, script setTimeout block)
obfuscated code
The get_jhash() function performs a computationally expensive loop (1,677,696 iterations) to derive a hash value stored in a cookie (__jhash_). This pattern is consistent with bot-detection fingerprinting or challenge mechanisms designed to distinguish human browsers from automated crawlers, enabling differentiated content delivery (cloaking) to security scanners vs. real users. (location: page.html:7, function get_jhash)
hidden content
The page has no visible content for users — only a centered spinner GIF (base64 encoded, 66x66px) and JavaScript. The meta tag 'noindex, noarchive' instructs search engines and archiving services not to index or cache the page. This suppresses forensic visibility while the page operates as a redirect gateway. (location: page.html:1, <meta name='robots' content='noindex, noarchive'>)
social engineering
The page harvests the visitor's User-Agent string and stores it in a cookie (__jua_) before redirecting. Combined with the referrer analysis (distinguishing organic search from direct/referral traffic via get_utm_medium), this enables fingerprinting of visitors to tailor the redirect destination or serve different payloads to targeted user segments. (location: page.html:43, document.cookie __jua_ assignment)
malicious redirect
The construct_utm_uri() function reads UTM parameters and referrer hostname to build a redirect URL that appends tracking parameters (utm_source, utm_medium, utm_campaign, utm_referrer) derived from the inbound referrer. This allows the operator to track which traffic sources deliver victims and to pass referrer context to downstream phishing or malicious pages. (location: page.html:10-34, function construct_utm_uri)
curl https://api.brin.sh/domain/hoster.kzCommon questions teams ask before deciding whether to use this domain in agent workflows.
hoster.kz 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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