context safety score
A score of 40/100 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
js obfuscation
JavaScript uses Function constructor for runtime code generation
obfuscated code
The page contains heavily obfuscated JavaScript using character-code arithmetic (String.fromCharCode with offset arithmetic), hex-encoded strings, and self-modifying window property overrides. The 'bobcmn' and 'failureConfig' variables contain hex-encoded payloads, and the main script block uses multi-layered obfuscation to conceal its true behavior, including bot/automation detection and dynamic function replacement. (location: page.html: <script> block inside <APM_DO_NOT_TOUCH>, lines 6-20 of page-text.txt)
obfuscated code
The 'failureConfig' window variable is a hex-encoded string that decodes to: 'Roops....something went wrong.... your support id is: %DOSL7.challenge.support_id%.' This encodes a DDoS-protection challenge failure message, concealing the actual error template from plain-text inspection. (location: page.html: window["failureConfig"] assignment in obfuscated script block)
hidden content
A Yandex Metrika tracking pixel is loaded via an offscreen image (position:absolute; left:-9999px) and a full analytics script is injected, silently tracking all user interactions including click maps, link tracking, and bounce rate for Yandex counter ID 88898237. This constitutes covert behavioral surveillance of visitors without visible disclosure. (location: page.html: <noscript> Yandex.Metrika div and inline script at end of body; page-hidden.txt lines 1-2)
social engineering
The visible page content (Russian) tells users their site is unavailable when using VPN services and asks them to disable VPN or submit a CAPTCHA form to 'bypass blocking.' This pressures users to disable privacy tools (VPN) and submit interaction data, a social engineering pattern that manipulates user behavior under a false technical pretext. (location: page-text.txt lines 34-48; page.html body div)
prompt injection
The page is served by rt.ru (RT, Russian state media). The page instructs users (and potentially AI agents crawling the page) that the site is 'unavailable with VPN' and requests CAPTCHA submission. An AI agent processing this page as instructions could be directed to disable anonymization, submit form data, or treat the CAPTCHA bypass message as a legitimate action directive. (location: page-text.txt lines 34-48; page.html body)
curl https://api.brin.sh/domain/rt.ruCommon questions teams ask before deciding whether to use this domain in agent workflows.
rt.ru currently scores 40/100 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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