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 'dual-s-msedge.net' is crafted to impersonate Microsoft Edge (msedge), a well-known Microsoft browser product. The 'dual-s-' prefix is a common typosquatting/combosquatting technique used to deceive users and AI agents into trusting the domain as legitimate Microsoft infrastructure. (location: domain: dual-s-msedge.net)
phishing
The domain 'dual-s-msedge.net' combines a recognizable Microsoft brand term ('msedge') with an obfuscating prefix under a non-Microsoft TLD (.net). This pattern is characteristic of phishing infrastructure designed to harvest credentials or redirect users under the guise of a Microsoft service. TLS is not connected and cert is invalid, consistent with a staged or abandoned phishing domain. (location: domain: dual-s-msedge.net, metadata.json tls.connected=false)
malicious redirect
The site serves no content (empty page.html, page-text.txt, page-hidden.txt) despite the domain being active. This blank-page pattern is commonly used in redirect chains where the landing page itself holds no payload but the domain acts as a hop or relay in a multi-stage malicious redirect campaign. (location: page.html (empty), page-text.txt (empty))
credential harvesting
The combination of a Microsoft Edge brand-impersonating domain with no visible page content and invalid TLS is consistent with a credential harvesting setup that may activate conditionally (e.g., based on user-agent, referrer, or geolocation), serving a login clone only to targeted victims while appearing empty to scanners. (location: domain: dual-s-msedge.net, metadata.json)
curl https://api.brin.sh/domain/dual-s-msedge.netCommon questions teams ask before deciding whether to use this domain in agent workflows.
dual-s-msedge.net 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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