context safety score
A score of 46/100 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 'vercel-dns-013.com' impersonates Vercel, a well-known cloud deployment platform, by incorporating the brand name 'vercel' combined with a fake infrastructure-sounding suffix '-dns-013'. This pattern is consistent with typosquatting and brand impersonation used to deceive users or AI agents into trusting the domain as an official Vercel service. (location: domain: vercel-dns-013.com)
phishing
The domain closely mimics Vercel's branding and infrastructure naming conventions (vercel + dns), which is a common phishing tactic to trick users or automated systems into believing they are interacting with a legitimate Vercel DNS or deployment endpoint. (location: domain: vercel-dns-013.com)
hidden content
TLS connection failed (connected=false, cert_valid=false), meaning the page content could not be retrieved over a secure channel. The HTML and text content files are empty, suggesting the site may only serve content under specific conditions (targeted delivery, user-agent filtering, or referrer checks), a technique used to evade automated scanners while delivering malicious content to real targets. (location: metadata.json: tls.connected=false; page.html and page-text.txt empty)
malicious redirect
Empty page content combined with a deceptive Vercel-branded domain and failed TLS suggests the site may perform conditional redirects or cloaking — serving benign or empty responses to crawlers while redirecting human visitors or specific user-agents to a phishing or credential harvesting page. (location: domain: vercel-dns-013.com; page.html empty)
curl https://api.brin.sh/domain/vercel-dns-013.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
vercel-dns-013.com currently scores 46/100 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.
integrate brin in minutes — one GET request is all it takes. query the api, browse the registry, or download the full dataset.