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
The domain 'g-ha-1und1.de' is constructed to closely mimic the legitimate German hosting/ISP brand '1und1.de' (1&1 IONOS). The pattern of prepending characters to the brand name ('g-ha-1und1.de') is a classic typosquatting and brand impersonation technique used to deceive users into believing they are interacting with the legitimate 1&1 IONOS service. (location: domain: g-ha-1und1.de)
phishing
The domain impersonates 1und1.de (a major German web hosting and ISP brand) and has a failed/invalid TLS connection with no page content returned. This combination is consistent with a phishing infrastructure that may serve credential-harvesting pages conditionally (e.g., by geography, referrer, or user-agent), and is currently inactive or blocking automated scanners. (location: https://g-ha-1und1.de)
credential harvesting
Sites impersonating 1und1.de (IONOS) typically target customer login credentials for web hosting control panels, email accounts, and billing portals. The domain structure and brand impersonation pattern is strongly associated with credential harvesting campaigns targeting 1&1 IONOS customers. (location: domain: g-ha-1und1.de)
malicious redirect
The TLS connection failed (connected=false, cert_valid=false) and the page returned empty content, which may indicate the site conditionally redirects victims based on traffic source, user-agent, or geolocation — a common evasion technique used by phishing and malware distribution sites to avoid detection by automated scanners. (location: https://g-ha-1und1.de, TLS metadata)
curl https://api.brin.sh/domain/g-ha-1und1.deCommon questions teams ask before deciding whether to use this domain in agent workflows.
g-ha-1und1.de 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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