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
cloaking
Page conditionally redirects based on referrer or user-agent
js obfuscation
JavaScript uses Function constructor for runtime code generation
obfuscated code
Page loads a WAF JavaScript challenge from ByteDance CDN (lf3-short.ibytedapm.com and lf-waf-js.byted-static.com). The challenge script collects detailed browser fingerprint data including navigator.plugins, navigator.platform, navigator.webdriver, navigator.vendor, navigator.languages, document.referrer, and window.history.length. This data is exfiltrated to a third-party ByteDance-controlled endpoint before any page content is rendered. (location: page.html, inline script body onload=readygo())
obfuscated code
The page embeds a base64-encoded challenge token (variable 'cs') and runs a brute-force SHA-256 proof-of-work loop (up to 1,000,000 iterations) entirely client-side before setting a cookie and reloading. This obfuscated challenge mechanism is used to gate access, obscuring the true destination or payload behind the redirect. (location: page.html, readygo() function; page-text.txt line 1)
malicious redirect
After completing the WAF proof-of-work challenge, window.location.reload() is triggered with a session cookie set, redirecting the user to the actual site content. The real destination of amemv.com is concealed behind this challenge layer; amemv.com is a known domain associated with TikTok/Douyin infrastructure but the landing page pattern is consistent with bot-gating used to hide phishing or credential-harvesting pages from automated scanners. (location: page.html, readygo() function — window.location.reload() call)
hidden content
The entire visible page content consists only of 'Please wait...' text with no links, branding, or user-facing information. All real page content is hidden behind a JavaScript-gated challenge, making static analysis or content inspection impossible. This technique is commonly used to conceal malicious payloads from security scanners. (location: page-text.txt line 1; page.html body)
social engineering
The page displays only 'Please wait...' to users, creating a false sense of a legitimate loading process while the browser fingerprint is silently collected and a proof-of-work challenge is executed. Users are given no indication that their browser data is being harvested. (location: page-text.txt line 1; page.html body onload)
curl https://api.brin.sh/domain/amemv.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
amemv.com 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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