context safety score
A score of 42/100 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 the visitor via window.location.href after a 1-second setTimeout. The destination URL is constructed dynamically from document.referrer and cookie values (__js_p_), making the final redirect target opaque and controllable server-side by setting the __js_p_ cookie. This is a classic cloaking/traffic-distribution system (TDS) pattern used to send bots and crawlers to a benign page while redirecting real users to malicious destinations. (location: page.html:36-48 (setTimeout redirect block))
obfuscated code
The get_jhash() function performs a computationally expensive loop (1,677,696 iterations) producing a hash value written to a cookie (__jhash_). This hash is likely used server-side as a bot/human proof-of-work challenge token. Combined with the user-agent fingerprinting cookie (__jua_), this forms a fingerprinting and evasion system designed to distinguish automated scanners from real browsers before delivering a payload or redirect. (location: page.html:7 (get_jhash function), page.html:40-43 (cookie-setting block))
hidden content
The page renders no visible content to the user — only a centered 66x66 pixel animated GIF (ajaxload spinner embedded as a base64 data URI) is displayed. All functional logic is hidden inside JavaScript. The meta robots tag 'noindex, noarchive' instructs search engines not to index or cache the page, which is consistent with hiding malicious or transient content from archival and scanning systems. (location: page.html:1 (meta robots noindex/noarchive), page.html:2 (blank spinner image))
social engineering
The loading spinner (ajaxload.info animated GIF) creates the false impression that a legitimate page is loading, keeping the visitor on the page for the 1-second delay before the redirect fires. This deceives the user into waiting rather than navigating away, facilitating the redirect chain. (location: page.html:2 (base64 ajaxload spinner div))
curl https://api.brin.sh/domain/frontol.ruCommon questions teams ask before deciding whether to use this domain in agent workflows.
frontol.ru currently scores 42/100 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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