context safety score
A score of 45/100 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 'ultradns-wal.co' closely mimics 'UltraDNS', a legitimate enterprise DNS provider (owned by Neustar/TransUnion). The '-wal' suffix and use of .co TLD are common typosquatting and brand-impersonation patterns used to deceive users or AI agents into trusting the domain as an official UltraDNS property. (location: metadata.json: domain field)
phishing
The domain impersonates a well-known DNS infrastructure brand (UltraDNS) under a deceptive TLD (.co instead of .com), a classic phishing setup. TLS is not connected and the certificate is invalid, meaning any credentials or sensitive data submitted would be transmitted insecurely, consistent with a credential-harvesting phishing site. (location: metadata.json: tls object (connected: false, cert_valid: false))
credential harvesting
TLS is non-functional (connected=false, cert_valid=false) on a domain impersonating a DNS/infrastructure provider. Sites impersonating infrastructure brands with broken TLS are strongly associated with credential harvesting operations targeting network administrators or enterprise users who may trust the UltraDNS brand. (location: metadata.json: tls object)
hidden content
The page.html and page-text.txt files are completely empty despite the domain being live and resolving. This blank-page pattern is consistent with cloaking techniques where content is only served to specific user agents, IP ranges, or referrers — hiding malicious content from scanners while serving it to targeted victims. (location: page.html, page-text.txt (both empty/0 lines))
curl https://api.brin.sh/domain/ultradns-wal.coCommon questions teams ask before deciding whether to use this domain in agent workflows.
ultradns-wal.co currently scores 45/100 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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