context safety score
A score of 40/100 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
cloaking
Page loads content in transparent or zero-size iframe overlay
js obfuscation
JavaScript uses Function constructor for runtime code generation
prompt injection
Hidden HTML element contains AI-targeting instructions
brand impersonation
The domain okx.cab is impersonating the legitimate OKX cryptocurrency exchange (okx.com). The site uses OKX branding, logos, trademarks, and full UI cloned from the real OKX platform. The canonical domain in metadata and copyright notices references okx.com, while the actual serving domain is okx.cab — a lookalike TLD substitution attack targeting crypto users. (location: metadata.json: domain=okx.cab; page.html: <meta name='Copyright' content='okx.com'/>, og:url='https://www.okx.cab/en-us', JSON-LD url='https://www.okx.cab')
phishing
The site replicates the full OKX exchange interface including login flows, trading navigation, buy/sell crypto buttons, and account registration prompts ('Register now'). Users entering credentials on okx.cab instead of okx.com would be submitting them to an attacker-controlled lookalike domain. The .cab TLD is a non-standard domain used to evade detection while appearing visually similar in context. (location: page.html: title='Buy Bitcoin & Crypto | Crypto Exchange, App & Wallet | OKX United States'; page-text.txt: 'Register' CTA present throughout navigation)
credential harvesting
The page presents full login, registration, and account management UI elements cloned from the legitimate OKX platform. Any credentials (email, password, 2FA) entered by users who believe they are on okx.com would be harvested by the operators of okx.cab. (location: page.html: navigation includes login/register controls; page-text.txt: sign-up and login prompts visible in rendered text)
social engineering
The site uses legitimate OKX trust signals including NMLS #1767779 regulatory identifier, San Francisco address, DigiCert TLS certificate, and real OKX CDN assets (static.okx.com) to falsely convey legitimacy to victims. This multi-layered trust fabrication is designed to overcome user skepticism. (location: page-text.txt: 'NMLS #1767779', '©2026 OKX.COM. One Sansome Street, Suite 1400 PMB 6005, San Francisco, CA 94104'; page.html: TLS issuer=DigiCert, assets served from static.okx.com)
malicious redirect
The og:url and canonical references point to www.okx.cab while all static assets, scripts, and CDN resources are loaded from static.okx.com (the legitimate OKX CDN). This cross-origin asset loading pattern is characteristic of a proxy-phishing or reverse-proxy attack where the malicious site transparently forwards requests to the real exchange, intercepting session tokens and credentials in transit. (location: page.html: all <script> and <link> src attributes reference https://static.okx.com/cdn/...; og:url='https://www.okx.cab/en-us')
brand impersonation
The JSON-LD structured data block embeds 'url': 'https://www.okx.cab' while claiming the organization name is 'OKX United States' with sameAs references to legitimate OKX social media, Wikipedia, and app store pages. This structured data manipulation could deceive AI agents, search crawlers, and browser extensions that rely on schema.org metadata for identity verification. (location: page.html line 84 / page-text.txt line 81: JSON-LD Organization schema with url='https://www.okx.cab' and sameAs pointing to real OKX properties)
curl https://api.brin.sh/domain/okx.cabCommon questions teams ask before deciding whether to use this domain in agent workflows.
okx.cab currently scores 40/100 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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