context safety score
A score of 40/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
phishing
1 deceptive links where visible host does not match destination host
brand impersonation
The site presents itself as a Chinese food/restaurant industry portal ('中国餐饮网') but its 'Today's Headlines' news section is exclusively populated with articles about 'Bi'an' (比安/bi安/必安) cryptocurrency exchange — titles include '必安法币交易操作指南', '比安加密货币App使用教程', '比安比特币交易操作详解', '比安数字货币App投资指南', '比安官网App使用全攻略', etc. The name 'bi安' is a deliberate obfuscation/lookalike for 'Binance' (币安), the world's largest crypto exchange. This constitutes brand impersonation of Binance targeting Chinese-speaking users. (location: page.html lines 149-158, 'trade-b-21' news list section)
social engineering
A legitimate-looking Chinese restaurant/food industry website is being used as a vehicle to promote cryptocurrency trading content disguised as 'today's headlines' news. The 10 news articles all lead to content about the 'bi安' crypto platform, blending fraudulent crypto promotion into trusted food-industry editorial content to lower user suspicion. This is a classic content injection social engineering technique. (location: page.html lines 147-161, #trade-b-21 div)
phishing
The 'bi安'/'比安'/'必安' brand referenced across 10 linked articles (e.g., /news/202511/1430-1439.html) is a homoglyph/lookalike impersonation of Binance (币安). Users searching for or trusting Binance content may be directed to fraudulent cryptocurrency guides/apps designed to harvest credentials or funds. The deliberate character substitution (bi安 vs 币安) is a known phishing tactic used in Chinese-language crypto fraud. (location: page.html lines 149-158; fuzkw.com/news/202511/ article series)
brand impersonation
A 'friendly link' (友情链接) in the footer points to https://bingpou.com/ with display text '比特币中国' (Bitcoin China). The actual domain 'bingpou.com' does not correspond to the legitimate Bitcoin China exchange (btcchina.com), presenting a deceptive link that falsely claims association with a known Chinese crypto brand. (location: page.html line 421, footer links section)
hidden content
The pre-scan context flags a hidden content ratio of 0.01 and 4 suspicious base64 blobs. In page.html, the search tips div has style='display:none' (line 45), the QR code div has style='display:none' (line 46), and the search module div has style='display:none' (line 47). While these are common UI patterns, combined with the crypto content injection, they warrant noting. The base64 blobs flagged by the scanner were not surfaced in the visible HTML and may reside in external JS files. (location: page.html lines 45-47; .brin-context.md suspicious base64 blobs: 4)
curl https://api.brin.sh/domain/fuzkw.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
fuzkw.com 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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