context safety score
A score of 37/100 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
malicious redirect
script/meta redirect patterns detected in page source
cloaking
Page checks user-agent for bot/crawler strings to serve different content
cloaking
Page conditionally redirects based on referrer or user-agent
js obfuscation
JavaScript uses Function constructor for runtime code generation
malicious redirect
Mobile-device-specific script dynamically injects two external scripts from cdnflex.me (a known ad/malware network) only when isMobileDevice() is true, hiding the behaviour from desktop analysis. The loaded scripts use obfuscated site_key parameters (ninfp0p, ninfpage) and could deliver pop-unders, forced redirects, or malware payloads to mobile users. (location: page.html line 24 / page-text.txt line 9: addScript('//cdnflex.me/lib.php?site_key=ninfp0p&d=l1&v=1721016565&r=54') and addScript('//cdnflex.me/lib.php?site_key=ninfpage&d=inpage&v=1721015597&r=375'))
hidden content
A 1x1 pixel invisible iframe is injected into the page body via JavaScript (height=1, width=1, position:absolute, visibility:hidden). A child script is then written into this iframe to load Cloudflare challenge platform scripts. While Cloudflare bot-challenge scripts are common, the pattern of injecting them via a hidden iframe rather than a normal script tag is atypical and obscures the execution context from page inspection. (location: page.html line 25 / page-text.txt line 10: iframe with height=1, width=1, style visibility:hidden injecting cdn-cgi/challenge-platform/scripts/jsd/main.js)
obfuscated code
The Cloudflare challenge parameters are base64-encoded inline (t:'MTc3MjYzNjUyNQ==') and injected as a string via innerHTML into a hidden iframe's document head, obscuring their purpose. The value MTc3MjYzNjUyNQ== decodes to 1772636525, consistent with a Unix timestamp, but the delivery mechanism (hidden iframe + innerHTML script injection) is an obfuscation pattern that evades straightforward static analysis. (location: page.html line 25: d.innerHTML containing window.__CF$cv$params with base64 value t:'MTc3MjYzNjUyNQ==')
social engineering
Compliance trust-badge images (RTA, ASACP, Pineapple Support) and a legal age disclaimer are displayed, but the anchor hrefs for these badges are set to '#' (no actual destination), meaning they are non-functional decoys used to fabricate an appearance of regulatory compliance rather than genuine membership or certification links. (location: page.html lines 10-16: <a href="#" class="link" rel="nofollow noreferrer noopener"> wrapping rta-logo, asacp, and pineapple-support images)
curl https://api.brin.sh/domain/ninfomaniacas.blogCommon questions teams ask before deciding whether to use this domain in agent workflows.
ninfomaniacas.blog currently scores 37/100 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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