Is pusat-nonton.space safe?

suspiciouslow confidence
36/100

context safety score

A score of 36/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.

identity
100
behavior
55
content
0
graph
30

7 threat patterns detected

medium

encoded payload

suspicious base64-like blobs detected in page content

critical

brand impersonation

The page hosted at pusat-nonton.space renders a full replica of Google's reCAPTCHA/unusual-traffic interstitial, including Google branding, Google Trust Services TLS cert, and a reference to Google's Terms of Service. The actual domain is unrelated to Google, making this a deliberate impersonation of Google's security infrastructure to deceive users and AI agents. (location: page.html:3-33, <title> set to 'https://www.google.com/')

critical

phishing

The page mimics Google's CAPTCHA challenge page (title set to 'https://www.google.com/') on a non-Google domain (pusat-nonton.space). A hidden form field named 'continue' is set to 'https://www.google.com/', likely to redirect victims after form submission, making the phishing lure convincing by eventually landing on Google. (location: page.html:17, hidden input name='continue' value='https://www.google.com/')

high

malicious redirect

The form posts to 'index' (action='index') with a hidden 'continue' parameter pointing to 'https://www.google.com/' and a hidden 'q' parameter containing an opaque encoded token. This pattern is consistent with a phishing relay: the site harvests the reCAPTCHA response/token and then redirects the user to Google to avoid suspicion. (location: page.html:7,17, form action='index', hidden inputs 'q' and 'continue')

high

prompt injection

The page is designed to appear as a legitimate Google security challenge. An AI agent crawling or rendering this page would read content asserting 'Our systems have detected unusual traffic' and instructions to 'solve the CAPTCHA', potentially causing the agent to interact with the form, submit credentials or tokens, or follow the redirect chain — all on a malicious third-party domain. (location: page.html:24-27, visible body text impersonating Google automated-traffic detection)

medium

obfuscated code

A hidden form input named 'q' contains a long opaque base64/encoded token value. This token is submitted silently with the form and its purpose is not disclosed to the user. It likely encodes tracking, session, or redirect state for the phishing backend. (location: page.html:17, <input type='hidden' name='q' value='EhAmABkAAAAtCQ...'>)

high

social engineering

The page uses authoritative Google-style language ('Our systems have detected unusual traffic from your computer network') combined with a fake CAPTCHA to pressure users into submitting the form, exploiting trust in Google's brand to manufacture urgency and compliance. (location: page.html:24, page-text.txt:21-24)

API

curl https://api.brin.sh/domain/pusat-nonton.space

FAQ: how to interpret this assessment

Common questions teams ask before deciding whether to use this domain in agent workflows.

Is pusat-nonton.space safe for AI agents to use?

pusat-nonton.space currently scores 36/100 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.

How should I interpret the score and verdict?

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.

How does brin compute this domain score?

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.

What do identity, behavior, content, and graph mean for this domain?

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.

Why does brin scan packages, repos, skills, MCP servers, pages, and commits?

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.

Can I rely on a safe verdict as a full security guarantee?

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.

When should I re-check before using an entity?

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.

Last Scanned

March 4, 2026

Verdict Scale

safe80–100
caution50–79
suspicious20–49
dangerous0–19

Disclaimer

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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