context safety score
A score of 47/100 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
brand impersonation
The domain qy.net is serving a full clone of the iQIYI (爱奇艺) streaming platform, including iQIYI's favicon, title, meta descriptions, structured data, and all branding assets. qy.net is not an official iQIYI domain (iqiyi.com). This constitutes brand impersonation of a major Chinese streaming service. (location: page.html: <title>, <meta name='description'>, <link rel='icon' href='//www.iqiyi.com/favicon.ico'>, ld+json schema referencing https://www.iqiyi.com)
malicious redirect
The page hosted on qy.net loads scripts and resources directly from www.iqiyi.com (e.g. //www.iqiyi.com/prelw/portal/lw/v7/channel/recommend) and cross-links all navigation URLs to iqiyi.com. Users interacting with this page will be silently redirected or mixed-origin content will be loaded, creating a spoofed portal that funnels users toward the legitimate site while qy.net intermediates the session. (location: page.html line 1: <script async src='//www.iqiyi.com/prelw/...'> and ld+json hasPart URLs pointing to iqiyi.com)
hidden content
The page injects a hidden <img> element (alt='', hidden=true) as a telemetry/tracking beacon to //qmsg.qy.net/qos with extensive parameters including the current page URL (purl=location.href), timestamps, user agent context, and session probe data. This silent beacon exfiltrates browsing context without user awareness. (location: page-text.txt: defaultTrace function creating hidden img with src='//qmsg.qy.net/qos?p1=1_10_101&t=9&...')
curl https://api.brin.sh/domain/qy.netCommon questions teams ask before deciding whether to use this domain in agent workflows.
qy.net currently scores 47/100 with a suspicious verdict and medium 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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