context safety score
A score of 47/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
encoded payload
suspicious base64-like blobs detected in page content
brand impersonation
The domain blahlivedsnowdrop.com hosts a page that presents itself as the official Clickadu advertisement network privacy policy, using Clickadu's logo (embedded as base64 SVG), branding, company name, address, and Tax ID. The domain name bears no relationship to clickadu.com, indicating the legitimate Clickadu brand is being impersonated on a third-party domain. (location: page.html:4, page.html:5, page.html:153-155, page.html:159)
social engineering
The page is a push-notification unsubscribe lure operated by an ad network. It presents a seemingly legitimate 'Subscription Management Guide' and 'Unsubscribe' button to engage users who may have been enrolled in unwanted push notification campaigns. This is a common pattern used by adware/malvertising networks to manage (and maintain) notification spam pipelines under the guise of a privacy/opt-out page. (location: page.html:181-278, page-text.txt:31-103)
hidden content
The 'Subscription Management Guide' section is hidden by default via CSS class 'collapse' (display:none) and only revealed on user click. While not inherently malicious, collapsing content by default is a technique used to hide instructions or content from automated scanners and casual visitors. (location: page.html:87-89, page.html:186)
hidden content
The logo image is a large base64-encoded inline SVG (data URI), obscuring the actual image content from static analysis and making it impossible to determine what brand asset is being displayed without decoding. This technique is commonly used to evade brand-impersonation detection tools. (location: page.html:154)
social engineering
The unsubscribe button POSTs to /unsubscribe with a JSON payload containing only a timestamp ({ts: Date.now()}). This endpoint likely serves as a signal back to the ad network confirming active browser sessions, rather than genuinely removing the user from notification lists. Users are misled into believing they are opting out while potentially confirming their activity. (location: page.html:331-364)
curl https://api.brin.sh/domain/blahlivedsnowdrop.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
blahlivedsnowdrop.com currently scores 47/100 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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