context safety score
A score of 49/100 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 'sharepoint.us' impersonates Microsoft SharePoint by using the SharePoint brand name under a non-Microsoft TLD (.us instead of the legitimate sharepoint.com or microsoft.com). This is a classic typosquatting/brand-abuse pattern used to deceive users and AI agents into believing they are interacting with an official Microsoft service. (location: domain: sharepoint.us)
phishing
The domain 'sharepoint.us' combined with a failed TLS connection (connected=false, cert_valid=false) and SharePoint brand impersonation is a strong phishing indicator. Legitimate Microsoft SharePoint never operates without valid TLS. The combination of brand impersonation and invalid/absent TLS certificate is consistent with a credential-harvesting phishing site that failed to load or is in a pre-deployment state. (location: metadata.json: tls.connected=false, tls.cert_valid=false)
credential harvesting
SharePoint brand impersonation domains are most commonly deployed to harvest Microsoft 365 credentials by presenting fake login pages. The domain pattern, brand abuse, and TLS anomaly are consistent with infrastructure staged for credential harvesting targeting enterprise users. (location: domain: sharepoint.us)
malicious redirect
The site returned no HTML content despite a fetch attempt, which may indicate the server conditionally serves content (e.g., only to browser user-agents or after a redirect chain), a common evasion technique used by phishing infrastructure to avoid automated scanners while redirecting human victims to malicious pages. (location: page.html: empty response)
curl https://api.brin.sh/domain/sharepoint.usCommon questions teams ask before deciding whether to use this domain in agent workflows.
sharepoint.us currently scores 49/100 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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