context safety score
A score of 35/100 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 'fnbconnect.co.za' impersonates FNB (First National Bank of South Africa). The legitimate domain is fnb.co.za. The subdomain-style prefix 'fnbconnect' is a classic typosquat/lookalike pattern used to deceive users into believing they are on an official FNB portal. (location: domain: fnbconnect.co.za)
phishing
The domain mimics a major South African bank (FNB) with a lookalike name, TLS is not connected or valid, and all page content is empty — consistent with a phishing site that blocks automated crawlers while serving credential-harvesting pages to real visitors. (location: https://fnbconnect.co.za)
credential harvesting
Combination of bank brand impersonation (FNB lookalike domain) and failed TLS strongly suggests this domain is used or intended to harvest online banking credentials from victims who believe they are visiting a legitimate FNB site. (location: https://fnbconnect.co.za)
hidden content
All page content files (page.html, page-text.txt, page-hidden.txt) are completely empty, yet the domain resolves and has a TLS handshake attempt. This indicates the site actively blocks crawlers/scanners and serves content only to targeted human visitors, a common evasion technique in phishing campaigns. (location: page.html, page-text.txt, page-hidden.txt)
malicious redirect
TLS connection failed entirely (connected: false), which may indicate the site redirects HTTP traffic in ways that bypass standard crawler TLS negotiation, potentially routing victims through intermediate phishing infrastructure. (location: metadata.json: tls.connected=false, tls.cert_valid=false)
curl https://api.brin.sh/domain/fnbconnect.co.zaCommon questions teams ask before deciding whether to use this domain in agent workflows.
fnbconnect.co.za currently scores 35/100 with a suspicious verdict and low 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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