Is brooklynmuseum.org 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

7 threat patterns detected

medium

encoded payload

suspicious base64-like blobs detected in page content

high

js obfuscation

JavaScript uses Function constructor for runtime code generation

high

brand impersonation

The page at brooklynmuseum.org renders a 'Vercel Security Checkpoint' interstitial page. The actual Brooklyn Museum website content is not served; instead, the page impersonates Vercel's bot-protection UI. This could be a misconfiguration or a spoofed checkpoint page used to intercept visitors expecting the Brooklyn Museum site. (location: page.html:<title> and page-text.txt: 'Vercel Security Checkpoint' footer/header)

high

obfuscated code

The page contains heavily obfuscated JavaScript with string array rotation, integer-based index obfuscation, and self-defending anti-tampering patterns (anti-debugger constructs via toString/search regex checks). The obfuscation technique is consistent with tools like javascript-obfuscator and is atypical for a legitimate Vercel checkpoint page, raising the possibility of injected malicious logic hidden within the obfuscated routines. (location: page.html: <script type="module"> block, lines 2)

medium

prompt injection

The page-text.txt file contains raw HTML markup embedded within what should be visible text content. This raw HTML injection into the text extraction layer could be used to confuse or manipulate AI agents that consume the text output, potentially injecting false context or instructions into agent pipelines that process page text. (location: page-text.txt: embedded raw HTML div/main/footer markup within visible text)

medium

social engineering

The interstitial displays 'We’re verifying your browser' and 'Enable JavaScript to continue', which are classic social engineering patterns used to coerce users into enabling JavaScript or completing actions. When served on a domain the user trusts (brooklynmuseum.org), this mismatch between expected content and displayed content can be exploited to manipulate user behavior. (location: page.html: #header-text, #header-noscript-text elements; page-text.txt line 1)

medium

malicious redirect

The page includes a visible link to 'https://vercel.link/security-checkpoint' with rel='noopener noreferrer nofollow', which is an off-domain redirect. While vercel.link is a known Vercel domain, its presence on brooklynmuseum.org without the expected museum content suggests the site may be hijacked or misconfigured, and the redirect could lead users away from the intended destination. (location: page.html: <a id='fix-text' href='https://vercel.link/security-checkpoint'>)

API

curl https://api.brin.sh/domain/brooklynmuseum.org

FAQ: how to interpret this assessment

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

Is brooklynmuseum.org safe for AI agents to use?

brooklynmuseum.org 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 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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