context safety score
A score of 45/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
malicious redirect
script/meta redirect patterns detected in page source
social engineering
Site promises users can 'Earn up to $9 per Survey' and displays inflated statistics (36,649,149 registered users, 135,470,513 surveys launched, present in 197 countries) with no verifiable source, consistent with a get-paid-to scam using false urgency and exaggerated reward claims to harvest personal data via registration. (location: page.html:85, page.html:178-200)
credential harvesting
Registration form is loaded via a cross-origin iframe from https://app.surveoo.com/en/landing/1/module — personal data (name, email, potentially payment info) is collected through an embedded third-party frame, obscuring the actual data recipient from the user. (location: page.html:99)
malicious redirect
A postMessage listener on the parent window unconditionally sets window.location.href to any URL value received from the embedded iframe (e.data.url), enabling the iframe origin (app.surveoo.com) to redirect the top-level browsing context to an arbitrary URL without user interaction. (location: page.html:122-124)
brand impersonation
PayPal and Amazon logos are prominently displayed as reward options in the hero section to imply partnership and legitimacy. Footer disclaimers clarify neither brand is sponsoring the promotion, indicating their visual presence is used to borrow trust rather than reflect a genuine relationship. (location: page.html:88-93, page.html:249)
hidden content
A Google Tag Manager noscript iframe (height=0, width=0, display:none, visibility:hidden) is injected into the page body, silently tracking users even without JavaScript execution. (location: page.html:44-45)
curl https://api.brin.sh/domain/surveoo.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
surveoo.com currently scores 45/100 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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