context safety score
A score of 21/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
brand impersonation
Page title, OG tags, and Twitter card reference 'NetFlixMirror' and 'NetMirror', directly mimicking Netflix branding. Meta keywords explicitly list 'netflix', 'PrimeVideo', 'Disney+', 'Hotstar' to impersonate multiple major streaming platforms. Primary color CSS variable is set to #e50914, which is Netflix's exact brand red. (location: page.html:5-22, page.html:44-46)
phishing
Site presents a fake 'Verify I'm Human' CAPTCHA gate on a domain (net20.cc) that impersonates Netflix/streaming services. The CAPTCHA form auto-submits on completion via verifyCallback, redirecting users into a phishing funnel without user intent. The form action is not shown, meaning submission destination is obscured. (location: page.html:584-621)
malicious redirect
Canonical URL and OG/Twitter URLs point to net22.cc, a different domain than the served domain net20.cc. This is a cross-domain redirect chain between .cc TLD domains (net20.cc -> net22.cc), a common pattern in phishing infrastructure to rotate domains and evade blocklists. (location: page.html:10-19)
social engineering
Page presents a fake human verification screen ('Verify I'm Human') designed to build false trust and legitimacy. This pattern is used to trick users into completing an action (CAPTCHA) that triggers an automatic form submission to an undisclosed endpoint, bypassing user awareness. (location: page.html:584-622)
hidden content
A zero-dimension tracking pixel is embedded in a hidden span element using whos.amung.us to silently track visitor analytics without disclosure. The element is styled display:none with width=0 height=0, making it completely invisible to users. (location: page.html:596)
hidden content
The form submission target (action attribute) is absent from the botverify form, and the verifyCallback auto-submits on CAPTCHA completion. The actual destination of harvested CAPTCHA tokens and any accompanying data (cookies, fingerprint) is not disclosed in the HTML, suggesting a server-side handler that may exfiltrate data covertly. (location: page.html:586-621)
brand impersonation
Meta description claims to offer content from Netflix, Amazon Prime Video, Disney+, and Hotstar across 50+ OTT platforms, falsely implying official affiliation with these services to attract victims searching for legitimate streaming content. (location: page.html:7, page.html:15)
curl https://api.brin.sh/domain/net20.ccCommon questions teams ask before deciding whether to use this domain in agent workflows.
net20.cc currently scores 21/100 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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