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
malicious redirect
TLS connection failed (connected=false, cert_valid=false, san_match=false) for rednotecdn.com. The site is inaccessible over HTTPS, which is consistent with a domain used for backend redirects, CDN abuse, or infrastructure that intentionally avoids TLS inspection. Legitimate CDN domains maintain valid TLS certificates. (location: metadata.json: tls object)
brand impersonation
The domain 'rednotecdn.com' mimics the branding of 'RedNote' (Xiaohongshu), a popular Chinese social media platform that saw a significant surge in Western users. The appended 'cdn' suffix is a common technique to appear as legitimate infrastructure (e.g., a content delivery network) for a known brand, deceiving users and automated agents into trusting the domain. (location: metadata.json: domain=rednotecdn.com)
hidden content
The page returned no visible text content and no HTML body content despite the domain being reachable enough to scan. Empty page responses can indicate cloaking behavior — serving content selectively based on user-agent, referrer, or IP — which is used to hide malicious content from scanners while delivering it to targeted victims or AI agents. (location: page.html, page-text.txt: empty files)
prompt injection
The combination of an empty page response, a CDN-spoofing domain name tied to a known social platform, and failed TLS is consistent with infrastructure designed to be referenced in AI agent workflows (e.g., as a 'trusted CDN source'). Embedding references to this domain in content consumed by AI agents could cause agents to fetch or trust resources from a malicious host. (location: rednotecdn.com domain pattern; metadata.json)
curl https://api.brin.sh/domain/rednotecdn.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
rednotecdn.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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