context safety score
A score of 46/100 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 'principalaws.com' closely mimics 'Principal' financial services brand combined with 'AWS' (Amazon Web Services), suggesting deliberate brand impersonation to deceive users or AI agents into trusting the domain as a legitimate financial or cloud services entity. (location: metadata.json: domain field)
brand impersonation
The domain 'principalaws.com' combines two well-known brands: Principal Financial Group and Amazon Web Services (AWS). This compound impersonation could deceive users expecting legitimate services from either brand, facilitating credential harvesting or trust exploitation. (location: metadata.json: domain=principalaws.com)
credential harvesting
TLS is not connected and certificate is invalid (connected=false, cert_valid=false), meaning any credentials submitted would be transmitted without valid encryption. Combined with the suspicious brand-impersonating domain name, this is consistent with a credential harvesting operation. (location: metadata.json: tls object)
malicious redirect
The site returned empty page content (page.html and page-text.txt are empty) despite the domain being resolvable. This pattern — a live domain with no rendered content — is consistent with a redirect-only or cloaking setup that serves different content to targeted victims versus crawlers/scanners. (location: page.html, page-text.txt (empty content))
curl https://api.brin.sh/domain/principalaws.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
principalaws.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.
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