context safety score
A score of 46/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
malicious redirect
script/meta redirect patterns detected in page source
js obfuscation
JavaScript uses Function constructor for runtime code generation
prompt injection
Hidden HTML element contains AI-targeting instructions
malicious redirect
Third-party script loaded from paslsa.com (//paslsa.com/c/jobbmintatv.online.js), an unrecognized and suspicious domain with no clear legitimate ownership. This script runs asynchronously and has full DOM access, enabling drive-by redirects, ad fraud, or malware delivery without user interaction. (location: page.html:353)
hidden content
Ad iframe loaded from api.indidata.com (https://api.indidata.com/zone_view.html?zona_id=10826) rendered with display:none on its parent div (ntdBnrId_10292). Hidden ad units can be used for click fraud, invisible tracking, or loading malicious payloads outside the visible viewport. (location: page.html:1101-1102)
malicious redirect
Script loaded from admanager.netadclick.com (https://admanager.netadclick.com/admanager.js) — a third-party ad network with no established reputation. Such scripts have broad DOM access and can inject redirects, popups, or malicious payloads targeting visitors. (location: page.html:364)
social engineering
Site presents itself as a free Hungarian movie and TV streaming platform (jobbmintatv.pro) offering 2144 series and 7424 films. The .pro TLD combined with the free streaming proposition is commonly used to lure users into accepting notification prompts, installing browser extensions, or engaging with aggressive ad networks that may serve malware. (location: page.html:340-343, page-text.txt:791)
curl https://api.brin.sh/domain/jobbmintatv.proCommon questions teams ask before deciding whether to use this domain in agent workflows.
jobbmintatv.pro 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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