context safety score
A score of 32/100 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
The domain 'awsdns-23.co.uk' mimics Amazon Web Services (AWS) DNS infrastructure by incorporating 'awsdns' — a subdomain pattern used by Amazon Route 53 (e.g., ns-123.awsdns-23.com). Registering this as a standalone .co.uk domain impersonates AWS to deceive users and automated systems into trusting it as legitimate Amazon infrastructure. (location: domain: awsdns-23.co.uk)
phishing
The domain closely imitates an Amazon AWS nameserver pattern (awsdns-##.tld) which is used in phishing campaigns to trick users or agents into believing they are interacting with legitimate AWS DNS infrastructure. The .co.uk TLD substitution is a classic typosquatting/phishing technique. (location: domain: awsdns-23.co.uk)
malicious redirect
TLS connection failed (connected=false, cert_valid=false) and the page returned no content, which is consistent with a parked or cloaked domain that may redirect users to a malicious payload only under certain conditions (e.g., specific user-agents, geolocations, or referrers). The absence of content with an active domain registration is a strong indicator of a redirect or cloaking setup. (location: metadata.json: tls.connected=false, page.html: empty)
social engineering
The domain name 'awsdns-23.co.uk' is engineered to appear as a trusted Amazon AWS DNS server to both human users and AI agents. This naming convention exploits institutional trust in AWS brand and infrastructure naming patterns, facilitating social engineering attacks where victims believe they are contacting a legitimate AWS endpoint. (location: domain: awsdns-23.co.uk)
curl https://api.brin.sh/domain/awsdns-23.co.ukCommon questions teams ask before deciding whether to use this domain in agent workflows.
awsdns-23.co.uk currently scores 32/100 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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