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
phishing
Domain name 'secure-booker.com' uses trust-inducing keyword 'secure' combined with a generic service term 'booker', a common phishing pattern to impersonate legitimate booking or financial services. TLS connection failed (connected=false, cert_valid=false), meaning the site cannot establish a valid HTTPS session despite presenting as 'secure', which is a strong indicator of a deceptive or misconfigured phishing site. (location: metadata.json: domain, tls fields)
brand impersonation
The domain 'secure-booker.com' appears crafted to impersonate legitimate booking platforms (e.g., Booking.com, hotel/travel booking services) by combining 'secure' and 'booker' into a plausible-looking service domain. This typosquat/lookalike pattern is frequently used to deceive users into trusting the site. (location: metadata.json: domain)
hidden content
The context file references a 'page-hidden.txt' for extracted hidden content, and the page.html is empty — suggesting the page either failed to render/load or content was intentionally stripped/hidden. A site that presents no visible content while maintaining an active domain with a deceptive name warrants scrutiny for cloaking or conditional content delivery (serving malicious content only to targeted victims). (location: page.html, page-hidden.txt, .brin-context.md)
phishing
TLS is entirely non-functional (connected=false, cert_valid=false, san_match=false, issuer=null) on a domain branded as 'secure-booker.com'. Claiming security in the domain name while operating without valid TLS is a hallmark of phishing infrastructure, credential harvesting pages, or sites in early deployment stages before targeting victims. (location: metadata.json: tls object)
credential harvesting
The combination of a trust-signaling domain name ('secure-booker.com'), failed TLS, unknown hosting reputation, and empty page content is consistent with a credential harvesting site that may be under construction, cloaking content, or selectively serving its payload. Booking-themed sites are commonly used to harvest payment card data and login credentials. (location: metadata.json: domain, tls, hosting fields)
curl https://api.brin.sh/domain/secure-booker.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
secure-booker.com 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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