context safety score
A score of 31/100 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
cloaking
Page conditionally redirects based on referrer or user-agent
credential harvesting
The initAccount() function reads 'token', 'account', 'password', and 'loginType' from IndexedDB and transmits them via postMessage to a parent window with wildcard origin '*'. This exfiltrates stored credentials to any listening parent frame without origin validation, enabling cross-origin credential theft. (location: page.html:81 — window.parent.postMessage({ type: 'fixToken', accountInfo: res }, '*'))
credential harvesting
The message event listener accepts 'fixToken' messages from any origin (no origin check on event.origin) and writes received token, account, password, and loginType directly into IndexedDB. This allows any malicious parent frame or cross-origin page to inject or overwrite stored credentials. (location: page.html:85-93 — window.addEventListener('message', ...) with no origin validation)
brand impersonation
The domain 637yyt60.com presents itself as 'JiLi168' / 'JiLi168.CC' in all meta tags (og:site_name, og:title, twitter:title, description) while operating from an unrelated random-looking domain. This is a classic brand impersonation pattern where a throwaway domain masquerades as an established gambling brand to lure users. (location: page.html:1-13 — meta og:site_name='JiLi168', og:url='637yyt60.com')
social engineering
The page advertises a 'free random sign up bonus' withdrawable after one round of betting — a common gambling social engineering lure designed to harvest user registrations and financial credentials under false incentive pretenses. (location: page.html:1 — meta description: 'get a free random sign up bonus and withdraw it after one round of betting')
obfuscated code
window.__APP_CONFIG__ contains a 'domainInfo' field set to a very long Base64-like encoded string (prefixed '==AR3UCR3U...'). This obfuscated payload is decoded at runtime and likely contains configuration data including domain routing, redirect targets, or operator keys hidden from static analysis. (location: page.html:18 — window.__APP_CONFIG__ = { domainInfo: '==AR3UCR3U...' })
malicious redirect
The isInIframe() function checks for a 'unTopWindow=true' URL parameter combined with 'domainType != google' to determine iframe context and alter credential-passing behavior. This parameter-driven branching logic is consistent with cloaking: showing normal content to Google crawlers while enabling credential exfiltration flows for real users embedded in iframe delivery chains. (location: page.html:21-24 — isInIframe() checks unTopWindow and domainType query params)
phishing
The site is a 115-day-old domain with a randomized name (637yyt60.com) impersonating the JiLi168 gambling brand, soliciting user registration including account credentials. The combination of brand impersonation, bonus lures, and credential storage/transmission infrastructure is consistent with a phishing operation targeting gambling platform users. (location: metadata.json + page.html — domain age 115 days, brand mismatch between 637yyt60.com and JiLi168.CC)
curl https://api.brin.sh/domain/637yyt60.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
637yyt60.com currently scores 31/100 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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