context safety score
A score of 42/100 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 mgovcloud.in impersonates an official Indian government service by presenting itself as 'NICeMail Services' — a branding associated with NIC (National Informatics Centre), which operates under nic.in and gov.in. The domain mgovcloud.in is a commercial .in TLD, not an official .gov.in domain, making this a likely lookalike impersonating Indian government email infrastructure. (location: domain: mgovcloud.in, page title: 'Help Guides and FAQs | NICeMail Services', canonical URL: https://www.mgovcloud.in/mail/help/)
brand impersonation
The page is built on Zoho's web framework (CSS classes zw-page-165, zw-product-3, zw-product-mgov-mail, zw-global-header, zc-getting-started.png) and promotes 'Zia Search' — an exclusive Zoho AI product — while presenting everything under the 'NICeMail' government brand with no attribution to Zoho. This conceals the true service provider from users and misrepresents the platform's origin. (location: page.html body class attribute: 'zw-page-165 zw-product-3 zw-product-mgov-mail', img data-src: '/sites/nweb/images/commonroot/zc-getting-started.png', visible text: 'Zia Search')
social engineering
The help/FAQ page is designed to build user trust in a platform hosted on a non-government domain (mgovcloud.in) by mimicking official government email support content. This legitimization tactic is commonly used to lower user suspicion before credential harvesting occurs on login pages within the same domain. (location: page-text.txt: 'NICeMail platform', 'Onboarding Guide', 'first-time login, authentication methods and recovery options', contact email: helpdesk-email@gov.in)
phishing
The site exhibits multiple phishing infrastructure indicators: unknown domain age (null WHOIS), DV-only TLS certificate expiring in 29 days (short-lived cert consistent with phishing campaigns), unknown hosting reputation, and a .in commercial domain masquerading as an Indian government (.gov.in) email service portal. The onboarding and login guidance pages linked from this help page are prime candidates for credential harvesting. (location: metadata.json: domain_age_days=null, tls.days_until_expiry=29, tls.cert_type=Dv, hosting.reputation=Unknown)
curl https://api.brin.sh/domain/mgovcloud.inCommon questions teams ask before deciding whether to use this domain in agent workflows.
mgovcloud.in currently scores 42/100 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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