context safety score
A score of 44/100 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 'capcutcdn-us.com' mimics the legitimate CapCut brand (by ByteDance) by prepending 'cap', appending 'cdn-us', and using a non-official TLD pattern. This typosquat/combosquat construction is a classic brand impersonation technique designed to deceive users into believing they are interacting with official CapCut infrastructure. (location: domain: capcutcdn-us.com)
phishing
The domain is 289 days old, has no TLS connectivity (TLS connected=false, cert_valid=false), and impersonates a major consumer brand. The combination of a fake brand domain with no valid HTTPS is consistent with a phishing or malware delivery infrastructure site. Users or agents directed here cannot establish a secure connection, suggesting the site may serve malicious content over HTTP or is used as a decoy/redirect node. (location: metadata.json: tls.connected=false, tls.cert_valid=false)
malicious redirect
The domain name pattern 'capcutcdn-us.com' includes 'cdn' suggesting it may be posed as a content delivery endpoint. Combined with no valid TLS and blank page content at scan time, this is consistent with a site used for redirect chaining or payload staging — serving different content to targeted victims while appearing empty to scanners. (location: domain: capcutcdn-us.com, metadata.json: tls.connected=false)
curl https://api.brin.sh/domain/capcutcdn-us.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
capcutcdn-us.com currently scores 44/100 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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