context safety score
A score of 29/100 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 site nkn.in is impersonating the official Indian government website nkn.gov.in (National Knowledge Network). All assets, images, CSS, JS, and navigation links load from nkn.gov.in while the page is served from the lookalike domain nkn.in, which is not a legitimate .gov.in domain. This is a classic government brand impersonation pattern. (location: page.html: entire page, domain nkn.in vs nkn.gov.in)
phishing
The site presents itself as an official Indian Government portal ('भारत सरकार | Government of India', National Emblem, NIC branding) while operating from the non-governmental domain nkn.in. This is designed to deceive users into believing they are on an official government site, a hallmark phishing technique targeting government service users. (location: page.html:64-163, page-text.txt:8)
social engineering
The page displays the visitor's real IP address prominently ('Your IP Address: 34.96.45.221') in the top bar. This is a social engineering tactic used to create a false sense of legitimacy, surveillance authority, or to intimidate users into trusting the site as an official government monitoring portal. (location: page.html:77-79, page-text.txt:13)
malicious redirect
All navigation links, language switchers, and content links point to nkn.gov.in rather than remaining on nkn.in. Users clicking navigation items are silently redirected to the official government site, which can be used to blend the fake site into legitimate browsing sessions and evade detection while harvesting interactions on the fake domain first. (location: page.html:129,136,186-357)
hidden content
CSS and JavaScript code blocks are rendered as visible text in the page-text.txt extracted content, indicating these style blocks were placed in unusual DOM positions (outside head/body structure, e.g., inline style block at line 81 in body). The <script> block appears before <body> at line 35, outside normal document structure, which can be used to obscure behavior from static scanners. (location: page.html:35-62, page.html:81-108, page-text.txt:18-43)
curl https://api.brin.sh/domain/nkn.inCommon questions teams ask before deciding whether to use this domain in agent workflows.
nkn.in currently scores 29/100 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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