context safety score
A score of 46/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
encoded payload
suspicious base64-like blobs detected in page content
cloaking
Page loads content in transparent or zero-size iframe overlay
js obfuscation
JavaScript uses Function constructor for runtime code generation
brand impersonation
The scanned domain mantis-intelligence.com serves content that fully identifies as mantissolutions.com — all canonical URLs, og:url, og:image, schema.org structured data, and contact email (hello@mantissolutions.com) point to mantissolutions.com. The site itself contains a footer Security Notice warning: 'We are aware of scams impersonating Mantis Solutions via unofficial websites.' This domain is not the canonical brand domain and mirrors its content without disclosure. (location: <link rel='canonical' href='https://www.mantissolutions.com'/>, <meta property='og:url' content='https://www.mantissolutions.com/'>, schema.org @id: https://www.mantissolutions.com/#global_business)
credential harvesting
Two forms collect PII (name, business email, and contact details) and submit via POST to the non-canonical domain mantis-intelligence.com (data-url='?m=m1794' and '?m=m3036'). Visitors believing they are on mantissolutions.com are submitting data to a different domain operator. (location: <form id='m1794' data-url='?m=m1794'> and <form id='m3036' data-url='?m=m3036'> — newsletter signup and contact forms)
hidden content
Multiple elements use display:none, visibility:hidden, and opacity:0 CSS. Two honeypot fields labeled 'Spam protection' are rendered with display:none/visibility:hidden. While these appear to be standard anti-spam honeypots, their presence alongside the domain mismatch warrants noting. (location: page-hidden.txt lines 1-4; CSS rules .hide-visibility{opacity:0;visibility:hidden} and .hidden{display:none})
curl https://api.brin.sh/domain/mantis-intelligence.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
mantis-intelligence.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.