Is vasilybrabusterrinsulias.firebaseapp.com safe?

suspiciouslow confidence
43/100

context safety score

A score of 43/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.

identity
100
behavior
100
content
0
graph
30

6 threat patterns detected

critical

malicious redirect

JavaScript reads the URL fragment hash, base64-decodes it as an email address, then immediately redirects the victim to an external suspicious domain (banguscaritasdementedvisuals.work.gd) with the decoded email appended as a query parameter (?ext_user=<email>). This is a classic open-redirect/email-harvesting relay chain: a link containing a base64-encoded victim email is sent to the target, the Firebase page silently forwards them to the attacker-controlled site with their address exposed. (location: page.html:6-21)

critical

credential harvesting

The decoded email address extracted from the URL hash is passed as the 'ext_user' parameter to the destination URL (banguscaritasdementedvisuals.work.gd). This pattern is used to pre-populate phishing landing pages with the victim's email, enabling personalised credential-harvesting attacks that appear more legitimate to the target. (location: page.html:14,20)

critical

phishing

The page acts as a phishing relay: it is blank/invisible to the user (empty body, no visible content) and exists solely to silently forward victims — with their pre-identified email address — to an attacker-controlled landing page at banguscaritasdementedvisuals.work.gd, a domain with a clearly auto-generated, non-credible name indicative of a throwaway phishing asset. (location: page.html:20,25-27)

high

hidden content

The page renders completely blank (page-text.txt contains only whitespace; <body> is empty). All malicious logic is concealed inside a <head> script block, making the redirect invisible to casual inspection and to users — they see nothing before being forwarded to the attacker site. (location: page.html:25-27)

high

social engineering

The use of a Firebase-hosted URL (vasilybrabusterrinsulias.firebaseapp.com) lends superficial legitimacy via Google's infrastructure and a valid DV TLS certificate issued by Google Trust Services. This is a deliberate tactic to bypass reputation filters and victim suspicion before the transparent redirect to the malicious destination. (location: metadata.json:tls.issuer, metadata.json:hosting.reputation)

medium

obfuscated code

The victim's email address is transmitted in the URL fragment as a base64-encoded string (window.atob(hash)) rather than plaintext. This encodes the payload to evade URL-scanning tools and email security gateways that inspect raw query parameters or link destinations for email addresses. (location: page.html:14)

API

curl https://api.brin.sh/domain/vasilybrabusterrinsulias.firebaseapp.com

FAQ: how to interpret this assessment

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

Is vasilybrabusterrinsulias.firebaseapp.com safe for AI agents to use?

vasilybrabusterrinsulias.firebaseapp.com currently scores 43/100 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 6, 2026

Verdict Scale

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

Trust Graph

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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