context safety score
A score of 42/100 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
social engineering
The page aggressively promotes an 'investment opportunity' with unverified financial claims ($1,000,000,000+ in combined earnings, $75M raised) and urgency signals ('Sold Out', 'START EARNING'). The site current.us hosts content for modemobile.com/modephone.com, presenting a high-pressure investment pitch that combines financial services language with consumer app monetization claims — consistent with investment social engineering tactics. (location: page-text.txt:1, page-text.txt:30 — 'INVESTMENT OPPORTUNITY', '$1,000,000,000+ in combined earnings')
brand impersonation
The domain current.us is serving content branded entirely as 'Mode Mobile' / 'ModePhone' (data-wf-domain set to www.modemobile.com). The URL/domain (current.us) does not match the brand being displayed, which is a classic brand impersonation pattern where a generic or misleading domain hosts content mimicking a different brand identity. (location: page.html:1 — data-wf-domain='www.modemobile.com' served from current.us)
obfuscated code
The Smart Recognition script is loaded using a split string technique ('<scr'+'ipt ...>') to evade static analysis and content security policy scanners. It dynamically injects a third-party tracking script from portal.smartrecognition.com, passing screen resolution, referrer, timestamp, and random values — a pattern used to fingerprint visitors and bypass detection. (location: page.html:3-5 and page.html:50-52 — document.write with split string 'scr'+'ipt')
hidden content
CSS style blocks appear inline within the page-text.txt extracted visible content (lines 2-14 and 17-28), indicating style rules were not properly separated from visible text. While likely a parser artifact, inline style injection can be used to hide content from users while keeping it readable by crawlers or AI agents. (location: page-text.txt:2-14, page-text.txt:17-28 — CSS animation rules embedded in visible text extraction)
curl https://api.brin.sh/domain/current.usCommon questions teams ask before deciding whether to use this domain in agent workflows.
current.us currently scores 42/100 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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