context safety score
A score of 48/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
tls connection failed
Could not establish TLS connection
brand impersonation
Domain 'capcutw.us' mimics the legitimate CapCut brand (owned by ByteDance) using a typosquat/combosquat pattern ('capcut' + 'w' + '.us' TLD). This is a common technique to deceive users into believing they are visiting the official capcut.com site. (location: domain: capcutw.us)
phishing
The site fails TLS connectivity (connected=false, cert_valid=false, san_match=false) while impersonating a well-known brand. Lack of valid HTTPS on a brand-impersonation domain is a strong indicator of a phishing or malicious credential-harvesting page, or a staging/redirect phishing asset. (location: metadata.json: tls.connected=false, tls.cert_valid=false)
malicious redirect
The page returned no HTML or visible text content despite being a registered domain impersonating CapCut. Empty page bodies are commonly used as redirect intermediaries or cloaked pages that serve malicious content conditionally (e.g., only to mobile users or specific geographies). (location: page.html (empty), page-text.txt (empty))
social engineering
The domain name 'capcutw.us' targets users of the popular CapCut video editing app. Users searching for or typing the CapCut URL may land on this domain and be subjected to fake download prompts, credential harvesting, or malware delivery disguised as the legitimate app. (location: domain: capcutw.us)
curl https://api.brin.sh/domain/capcutw.usCommon questions teams ask before deciding whether to use this domain in agent workflows.
capcutw.us currently scores 48/100 with a suspicious verdict and medium 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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