context safety score
A score of 38/100 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
js obfuscation
JavaScript uses Function constructor for runtime code generation
brand impersonation
The scanned URL is juicyads.me, a .me TLD domain, while the legitimate brand operates exclusively at juicyads.com. All canonical URLs, OG tags, structured data, and asset references in the page point to www.juicyads.com and staging.juicyads.com, not juicyads.me. The .me domain is serving content that fully impersonates the legitimate JuicyAds adult ad network brand, logo, and identity. (location: metadata.json: domain=juicyads.me; page.html line 35: canonical href=https://www.juicyads.com/; page.html line 39: og:url=https://www.juicyads.com/)
malicious redirect
The juicyads.me domain serves a full copy of the juicyads.com website with all signup, login, and action links pointing to third-party subdomains (ux13.juicyads.com, manage.juicyads.com) rather than the current .me domain itself. A user landing on juicyads.me and clicking Login or Join Now is redirected to ux13.juicyads.com/login.php and ux13.juicyads.com/signup.php — credential entry points that are off-domain from both the .me impersonation site and the canonical .com site. (location: page.html line 395: href=https://ux13.juicyads.com/login.php; page.html lines 368,376,413,422,431,910,1183,1215,1226)
credential harvesting
Login and account signup flows are funneled through ux13.juicyads.com, a subdomain not present on the scanned .me domain. Users who arrive at the impersonation domain (juicyads.me) and attempt to log in or register are directed to this external endpoint, creating a classic credential-harvesting chain where the lookalike domain drives traffic and the off-domain endpoint collects credentials. (location: page.html line 395: Login link to ux13.juicyads.com/login.php; page.html lines 368,376,910,1183,1215,1226: signup links to ux13.juicyads.com/signup.php)
social engineering
The page uses high-urgency and authority-building language combined with fabricated award claims and testimonials to lower user skepticism and drive sign-ups. Phrases such as 'you are a fool if you do not use JuicyAds', 'over 100,000 accounts activated', 'XBIZ 2020 Best Traffic Services Company', and inflated award counts (30+ awards) are deployed as social proof to manipulate user trust on what is a domain impersonating the real brand. (location: page.html lines 410-413, 958-959; page-text.txt lines 52-54, 498-499)
hidden content
An H1 element 'Juicy Ads Adult Network' is commented out in the HTML source and therefore invisible to users but potentially readable by crawlers or AI agents parsing raw HTML. While this is likely a legacy WordPress artifact, it represents suppressed markup that differs from rendered page content. (location: page-hidden.txt line 20: [HTML comment] <h1>Juicy Ads Adult Network</h1>; page.html line 362)
curl https://api.brin.sh/domain/juicyads.meCommon questions teams ask before deciding whether to use this domain in agent workflows.
juicyads.me 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.
integrate brin in minutes — one GET request is all it takes. query the api, browse the registry, or download the full dataset.