context safety score
A score of 34/100 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
The domain 'microsoftazuread-sso.com' is a typosquat/impersonation of Microsoft's Azure Active Directory SSO service. It combines the legitimate Microsoft product name 'Azure AD' with 'sso' to mimic the appearance of an official Microsoft authentication endpoint, designed to deceive users and AI agents into trusting it as a legitimate Microsoft identity provider. (location: domain: microsoftazuread-sso.com)
phishing
The domain is constructed to impersonate Microsoft Azure AD SSO, a common target for credential phishing. Users or automated agents directed to this domain may be tricked into submitting Microsoft credentials (username/password, MFA tokens) believing they are on a legitimate Microsoft login page. (location: domain: microsoftazuread-sso.com)
credential harvesting
Domains impersonating Microsoft SSO/Azure AD authentication infrastructure are a well-known vector for harvesting corporate credentials. The domain pattern 'microsoftazuread-sso.com' is consistent with adversary-in-the-middle (AiTM) phishing kits that capture session tokens and credentials in real time. (location: domain: microsoftazuread-sso.com)
malicious redirect
TLS connection failed (connected=false, cert_valid=false), yet the domain is named to impersonate a Microsoft authentication endpoint. This is consistent with a parked or dormant phishing domain that may redirect victims to a credential harvesting page or serve as a relay in an AiTM proxy attack chain. (location: metadata.json: tls.connected=false, tls.cert_valid=false)
curl https://api.brin.sh/domain/microsoftazuread-sso.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
microsoftazuread-sso.com currently scores 34/100 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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