context safety score
A score of 49/100 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
malicious redirect
script/meta redirect patterns detected in page source
brand impersonation
The domain sageone.co.za is not an official Sage domain. The Cloudflare challenge page reveals cZone set to 'www.sage.com', and the redirect target is '/en-za/sage-business-cloud/accounting/', indicating this domain is proxying or impersonating the official Sage accounting brand (sage.com) under a lookalike South African ccTLD domain (sageone.co.za). (location: metadata.json: domain=sageone.co.za; page.html: cZone='www.sage.com', cUPMDTk path='/en-za/sage-business-cloud/accounting/')
malicious redirect
The page contains a Cloudflare challenge that redirects users to '/en-za/sage-business-cloud/accounting/' with embedded challenge tokens. The scanned domain sageone.co.za appears to be routing traffic toward www.sage.com content, suggesting a transparent proxy or redirect chain that could intercept credentials or session tokens submitted by users believing they are on the legitimate Sage site. (location: page.html and page-text.txt: cUPMDTk and fa parameters pointing to /en-za/sage-business-cloud/accounting/ with challenge tokens)
credential harvesting
A domain impersonating Sage accounting (sageone.co.za vs sage.com) that proxies or redirects to Sage Business Cloud Accounting login flows is a classic adversary-in-the-middle setup for harvesting user credentials. Users navigating to this domain and completing the Cloudflare challenge would be routed to accounting login pages while the intermediate domain could capture submitted credentials. (location: metadata.json: domain=sageone.co.za; page-text.txt: redirect target /en-za/sage-business-cloud/accounting/)
curl https://api.brin.sh/domain/sageone.co.zaCommon questions teams ask before deciding whether to use this domain in agent workflows.
sageone.co.za currently scores 49/100 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.