context safety score
A score of 37/100 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
malicious redirect
script/meta redirect patterns detected in page source
cloaking
Page conditionally redirects based on referrer or user-agent
exfiltration
JavaScript intercepts form submissions to exfiltrate data
js obfuscation
JavaScript uses Function constructor for runtime code generation
malicious redirect
PopMagic ad script from a.magsrv.com/pemsrv.com is configured with popup_fallback:true, new_tab:true, trigger_method:2, and frequency controls. This ad network (pemsrv.com/magsrv.com) is associated with aggressive pop-under and redirect ad delivery that can send users to malicious or deceptive destinations without explicit consent. (location: page.html:28-51, adConfig block)
malicious redirect
Hidden 1x1 invisible iframe injected dynamically via Cloudflare challenge script, creating a concealed browsing context. The iframe (height=1, width=1, visibility:hidden, position:absolute) loads /cdn-cgi/challenge-platform/scripts/jsd/main.js with obfuscated parameters (r:'9d7151623ebb61ae', t:'MTc3MjYzMTg5MA=='). While this may be a legitimate Cloudflare bot-detection mechanism, the pattern of injecting a hidden iframe with encoded parameters is a known technique for covert redirects and data exfiltration. (location: page.html:1060, page-text.txt:826)
hidden content
A hidden iframe (height=1, width=1, position:absolute, top:0, left:0, border:none, visibility:hidden) is injected into the DOM at runtime. The script inside the iframe sets obfuscated window.__CF$cv$params with base64-encoded value (t:'MTc3MjYzMTg5MA==') and dynamically appends an external script. This pattern hides activity from the visible page and is used in both legitimate Cloudflare challenges and malicious tracking/redirect schemes. (location: page.html:1060)
social engineering
Header link bar includes a link labeled 'AI Sex Slave' pointing to landing.xotic.ai/go/862c1761-98d9-4935-95f3-abfb724901c0 — an affiliate landing page with a UUID-style tracking path. The deceptive label combined with an opaque redirect URL is a social engineering pattern used to lure users (including AI agents parsing link text) into clicking affiliate/tracking links under misleading pretenses. (location: page.html:111)
social engineering
Header link bar contains multiple affiliate-tracked external links (e.g., crushon.ai with utm parameters, leakifyhub.fun with affiliate=erofuscom, cmonbae.com with union_id=MTgz) embedded as seemingly editorial navigation links. These are monetized affiliate redirects disguised as peer recommendations, which can mislead users and AI agents crawling navigation structure. (location: page.html:111)
brand impersonation
The page hosts a category titled 'Fake Celebrities Sex Pictures' (/comics/fake-celebrities-sex-pictures), which explicitly aggregates content using real celebrity likenesses in pornographic contexts. This constitutes brand/identity impersonation of real public figures and is frequently used as lure content on phishing and credential-harvesting sites. (location: page.html:636-644)
curl https://api.brin.sh/domain/erofus.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
erofus.com currently scores 37/100 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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