context safety score
A score of 38/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
obfuscated code
A hidden 1x1 pixel iframe is injected with style position:absolute, top:0, left:0, border:none, visibility:hidden. JavaScript inside the iframe executes obfuscated Cloudflare challenge code using hex-encoded variables (_0xh, _0xi, _0xj) and a base64-encoded parameter blob. This pattern is consistent with bot-detection evasion or covert script execution infrastructure. (location: page.html:1 — inline script block using _0xh iframe + _0xi/_0xj variable names with obfuscated JS string injection)
hidden content
A 1x1 invisible iframe (height=1, width=1, visibility:hidden, position:absolute at top-left corner) is dynamically created and appended to the document body. Script content is injected into this hidden iframe via innerHTML, executing code outside the main document context and invisible to the user. (location: page.html:1 — var _0xh=document.createElement('iframe'); _0xh.height=1; _0xh.width=1; _0xh.style.visibility='hidden')
malicious redirect
An external script is loaded from celebrated-torte-4dc31b.netlify.app — a third-party Netlify subdomain unrelated to the declared domain policyedunet.com. The path mimics a Cloudflare CDN path (/cdn-cgi/apps/head/...) but is served from a non-Cloudflare host. This is a known technique to load malicious payloads while appearing to be legitimate CDN infrastructure. (location: page.html:1 — <script src=https://celebrated-torte-4dc31b.netlify.app/cdn-cgi/apps/head/ZkSypcFVzxgkXwU-ZX8mbB-lcE0.js>)
credential harvesting
A fetch() call to the current page URL includes a custom header 'ts-request-embed-key' containing what appears to be a UUID and a long hex token (d138e818-0299-42ab-a30f-5086dc24ab38:123f9c89948d9802250f31013c08453f452525ac71dd58f049c21bf711249dc8). This pattern is used to exfiltrate session tokens, embed keys, or track/harvest visitor credentials by beaconing back to a server with identifying data. (location: page.html:1 — fetch(window.location.href,{method:"GET",headers:{"ts-request-embed-key":"d138e818-0299-42ab-a30f-5086dc24ab38:123f9c89948d9802250f31013c08453f452525ac71dd58f049c21bf711249dc8"}}))
brand impersonation
The domain policyedunet.com combines 'policy', 'edu', and 'net' to suggest legitimacy as an educational policy network, yet the page content is entirely a 'Match Emoji' game with no educational or policy content. The domain name is designed to appear credible and institutional while hosting unrelated content, consistent with brand impersonation of educational or government entities. (location: metadata.json — domain: policyedunet.com; page.html:1 — <title>Match Emoji</title>)
obfuscated code
The Cloudflare challenge script uses hex literal values (0x8d30a6fb4d, 0xa8b17765cc) embedded in an array within a stringified JS payload that is dynamically eval'd inside a hidden iframe. The use of hex obfuscation and dynamic script injection into a sandboxed iframe context is a classic obfuscation technique to evade static analysis. (location: page.html:1 — s:[0x8d30a6fb4d,0xa8b17765cc] inside window['__CF$cv$params'] string injected via innerHTML)
curl https://api.brin.sh/domain/policyedunet.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
policyedunet.com currently scores 38/100 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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