context safety score
A score of 42/100 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
phishing
1 deceptive links where visible host does not match destination host
brand impersonation
The StatCounter tracking code in the HTML comments is labeled 'Default Statcounter code for Laviewddns.com' and references 'http://www.laviewddns.com', indicating this page's analytics code was copied from or is impersonating a different DDNS service (Laviewddns.com). The site presents itself as dvrlists.com but uses analytics tied to a different brand. (location: page.html:164-165)
credential harvesting
The page presents a login form that collects username/email and password via POST to 'loginaction.aspx'. The domain dvrlists.com is a DDNS provider whose credentials, if harvested, would grant access to DNS records and potentially allow attackers to redirect network traffic for DVR/IoT devices. The feedback contact email (sam@dyndnsservices.com) belongs to a different domain than the site itself, raising authenticity concerns. (location: page.html:116-138)
phishing
The site operates as a DDNS login portal for DVR/IoT devices. The analytics snippet embedded in the page was originally written for a different domain (laviewddns.com), suggesting this page may be a copy or clone of another DDNS service's login page, potentially used to phish credentials from users of that service. (location: page.html:164-178)
hidden content
The StatCounter tracking script uses sc_invisible=1, making the tracker invisible to users. While StatCounter commonly uses this setting, it obscures analytics collection from visitors. Combined with the mismatched domain in the comment, this warrants attention. (location: page.html:168)
curl https://api.brin.sh/domain/dvrlists.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
dvrlists.com currently scores 42/100 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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