context safety score
A score of 27/100 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 'www-ledger-updates.recyclepu.com' impersonates Ledger, a well-known cryptocurrency hardware wallet brand, by embedding 'ledger-updates' in the subdomain of an unrelated registrant domain 'recyclepu.com'. This naming pattern is a hallmark of crypto phishing infrastructure targeting Ledger users. (location: domain: www-ledger-updates.recyclepu.com)
phishing
The domain combines brand impersonation of Ledger with an invalid TLS certificate (connected=false, cert_valid=false), a 178-day-old domain, and unknown hosting reputation. These are strong composite indicators of an active phishing site targeting cryptocurrency users, likely to harvest seed phrases or credentials. (location: domain: www-ledger-updates.recyclepu.com)
credential harvesting
Sites impersonating Ledger with 'updates' in the domain name are consistently associated with fake firmware update flows designed to trick users into entering their 24-word recovery seed phrase. The empty page content suggests bot/geo-gating to evade automated scanners while serving malicious content to real victims. (location: domain: www-ledger-updates.recyclepu.com)
hidden content
The page returned completely empty HTML and text content despite the domain being active (DNS resolves). This is consistent with cloaking techniques that serve benign or empty content to crawlers/scanners while delivering malicious payloads to targeted human visitors based on user-agent, IP geolocation, or referrer. (location: page.html, page-text.txt (both empty))
curl https://api.brin.sh/domain/www-ledger-updates.recyclepu.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
www-ledger-updates.recyclepu.com currently scores 27/100 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.
integrate brin in minutes — one GET request is all it takes. query the api, browse the registry, or download the full dataset.