context safety score
A score of 32/100 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
brand impersonation
Page impersonates Google Play Store by displaying 'Installing from Google Play Store...' and a fake installation progress bar (0%), while the actual domain is s5qlfahupkra.com — a randomly-named domain with no affiliation to Google. This deceives users into trusting a fake app install flow. (location: page.html:84, page.html:61-66)
social engineering
The page simulates an app installation process with a progress counter (0%), a 'Verified' badge, a loading spinner, and 'Installing from Google Play Store...' text to manipulate users into believing they are installing a legitimate app from a trusted source. The fake UX is designed to lower user suspicion and drive downloads of likely malicious APKs. (location: page.html:55-66, page.html:79-84)
malicious redirect
Clicking the 'service' div triggers linkTg(), which redirects users to 'https://direct.lc.chat/19139344/2' — a live chat platform link. This is a common tactic used in gambling/fraud sites to funnel victims to operators for further social engineering or credential harvesting via live chat agents. (location: page.html:23, page.html:87-90)
obfuscated code
A base64-encoded encrypted string is stored in variable 'ss' and loaded inline. The value appears to be a CryptoJS-encrypted payload (given the inclusion of crypto-js_4.1.1 library). The actual content and purpose of this payload is concealed — it is likely decoded and executed at runtime by logichandle.js to hide malicious logic from static analysis. (location: page.html:74-75, page.html:11)
hidden content
All meaningful page content (text labels, button states, app name, verified status) is injected dynamically via JavaScript after DOMContentLoaded, rendering the page effectively blank to static crawlers and security scanners. This evasion technique hides the true nature of the page from automated analysis tools. (location: page.html:78-85)
brand impersonation
The page title and branding reference 'MJ77.COM', an online gambling brand, displayed on a domain (s5qlfahupkra.com) with no apparent affiliation to that brand. This suggests either an unauthorized affiliate/phishing clone or a malicious distribution site using the MJ77 brand to attract users. (location: page.html:6, page.html:52)
social engineering
The domain is only 157 days old with a randomized, non-descriptive name (s5qlfahupkra.com), consistent with a throwaway domain used in fraud campaigns. The site uses a Chinese-language HTML structure (lang='zh-CN') targeting Chinese-speaking users while presenting an English-language fake Google Play interface — a layered deception strategy. (location: metadata.json, page.html:2)
curl https://api.brin.sh/domain/s5qlfahupkra.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
s5qlfahupkra.com currently scores 32/100 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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