context safety score
A score of 42/100 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
brand impersonation
The domain luhostel.in impersonates the University of Lucknow (official domain lkouniv.ac.in). The page title, content, and branding all claim to be the official 'University of Lucknow Hostel Management System' but is hosted on a third-party .in domain unaffiliated with the university's official .ac.in domain. The page even links to the real university at lkouniv.ac.in, confirming the legitimate institution has a different domain. (location: page.html:7, page.html:36 - domain luhostel.in vs official lkouniv.ac.in)
credential harvesting
The site presents a login form collecting email address and password from students who believe they are on the official University of Lucknow portal. The form submits via POST to the same domain (luhostel.in), which is not the official university domain. Six credential-related forms detected (registration, login, forgot password). Student university credentials are being collected by a third-party operator (SRI TECHNOCRAT / sritechnocrat.com). (location: page.html:145-194 - login_formid form with login_emailid and login_password fields)
phishing
The entire site is constructed to mimic the official University of Lucknow Hostel Management System on a non-official domain (luhostel.in vs lkouniv.ac.in). Students are directed to register and log in with university credentials. Technical support is routed to helpdesk@sritechnocrat.com rather than any official university address, and the site is 'Powered by SRI TECHNOCRAT', a private third party operating under the university's brand. (location: page.html:36, page.html:201, page.html:270 - branding, helpdesk email, and powered-by footer)
social engineering
The page creates urgency and legitimacy by mimicking the exact two-step official registration workflow of the real University of Lucknow hostel system, using official-sounding language, a university logo, and a link to the real university website (lkouniv.ac.in) to build trust before harvesting credentials. (location: page.html:36-74 - welcome text, step instructions, and link to real university)
malicious redirect
JavaScript function ChangeFormSemester() uses window.location to redirect users to fregister.php when semester==1. While conditionally triggered, this JS redirect pattern (1 hit flagged in Tier 2) routes users within the same untrusted domain and could be used to direct users to further credential-harvesting pages. (location: page.html:298-302 - ChangeFormSemester() function with window.location redirect)
curl https://api.brin.sh/domain/luhostel.inCommon questions teams ask before deciding whether to use this domain in agent workflows.
luhostel.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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