context safety score
A score of 48/100 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
brand impersonation
The domain lunalabs.io is serving a full replica of the Unity Technologies website (unity.com), including Unity branding, Unity product names (Unity Engine, Unity LevelPlay, Tapjoy, ironSource, etc.), Unity navigation structure, and Unity-branded CTAs such as 'Turn your game into a business with Unity'. The serving domain lunalabs.io has no affiliation with Unity Technologies and is not unity.com. (location: https://lunalabs.io — entire page content, page.html line 98, page-text.txt line 1)
malicious redirect
Primary CTA button 'Get started' links to //cloud.unity.com/home/products?category=grow using a protocol-relative URL. When served from lunalabs.io, this redirects users to cloud.unity.com, a legitimate Unity domain, but the pattern of hosting Unity content on a third-party domain while redirecting auth/account flows to the real Unity cloud portal is consistent with a session-hijacking or credential-harvesting relay setup. (location: page.html line 98, href='//cloud.unity.com/home/products?category=grow')
phishing
The page presents itself as the official Unity Technologies homepage on a domain (lunalabs.io) unrelated to Unity. This is a classic phishing pattern: a convincing brand clone hosted on a lookalike or unrelated domain to deceive users into believing they are on the legitimate site, potentially capturing credentials or session tokens when users attempt to log in. (location: https://lunalabs.io — full page, metadata.json domain field)
hidden content
Multiple HTML elements are rendered with aria-hidden='true', opacity:0, pointer-events:none, and absolute positioning (e.g., dropdown menu panels). While these are standard UI patterns in Next.js/React navigation, several panels contain full navigation trees invisible to users but fully traversable by automated agents and crawlers, including links to docs.unity.com and other external resources. (location: page.html lines 49, 61 — aria-hidden='true' style='position:absolute;pointer-events:none;opacity:0')
curl https://api.brin.sh/domain/lunalabs.ioCommon questions teams ask before deciding whether to use this domain in agent workflows.
lunalabs.io currently scores 48/100 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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