context safety score
A score of 43/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
malicious redirect
A hidden zero-size iframe is injected via JavaScript pointing to 'googletagmanoger.com' — a typosquat of 'googletagmanager.com'. The domain substitutes 'manager' with 'manoger', a classic typosquatting technique used to impersonate Google Tag Manager infrastructure while loading attacker-controlled content. The iframe is explicitly hidden (display:none, visibility:hidden, height=0, width=0) to avoid detection. (location: page.html:47-61 (script block and noscript fallback))
brand impersonation
The domain 'googletagmanoger.com' impersonates Google's legitimate 'googletagmanager.com' service by using a visually similar misspelling ('manoger' vs 'manager'). This is used to lend the malicious iframe apparent legitimacy, mimicking a standard Google Tag Manager integration. (location: page.html:47,61)
hidden content
A zero-dimension iframe (height=0, width=0, display:none, visibility:hidden) is injected both via inline JavaScript and a noscript fallback tag, loading content from the typosquatted domain 'googletagmanoger.com'. This content is completely invisible to the user but executes in the browser context, enabling data exfiltration, tracking, or further payload delivery. (location: page.html:46-61)
obfuscated code
The malicious iframe is injected dynamically via a self-executing anonymous JavaScript function rather than being declared as a static HTML element. This pattern obscures the presence of the iframe from casual HTML inspection and may bypass simple static content filters that only scan for raw iframe tags. (location: page.html:44-60 (script block after closing </html> tag))
curl https://api.brin.sh/domain/vrajras.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
vrajras.com currently scores 43/100 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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