context safety score
A score of 74/100 indicates minor risk signals were detected. The entity may be legitimate but has characteristics that warrant attention.
malicious redirect
Meta refresh redirect with 0-second delay targets '/.well-known/sgcaptcha/' with URL parameters embedding what appears to be a visitor IP address (34.96.45.153) and timestamp (1774511272.269). This pattern is consistent with bot-detection evasion or traffic redirection infrastructure used in phishing and malware delivery chains. The 'ipr:' prefix in the 'y' parameter encodes the visitor's IP, enabling fingerprinting and targeted redirection. (location: page.html:1 — <meta http-equiv="refresh" content="0;/.well-known/sgcaptcha/?r=%2F&y=ipr:34.96.45.153:1774511272.269">)
social engineering
The redirect destination mimics a CAPTCHA verification flow ('sgcaptcha') under the '.well-known' path, which typically hosts legitimate metadata (RFC 5785). Abusing this well-known path for a fake CAPTCHA creates a false sense of legitimacy, a common social engineering tactic to build user trust before presenting malicious content. (location: page.html:1 — redirect target /.well-known/sgcaptcha/)
hidden content
The page renders no visible text content (page-text.txt is empty) despite having HTML. The entire page body is a silent redirect with no user-facing content, concealing the redirect behavior from casual inspection and making the page appear benign while functioning as a traffic redirector. (location: page.html:1 — empty body with invisible meta-refresh redirect)
curl https://api.brin.sh/domain/efsgnj.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
efsgnj.com currently scores 74/100 with a caution 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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