context safety score
A score of 40/100 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
cloaking
Page loads content in transparent or zero-size iframe overlay
prompt injection
Hidden HTML element contains AI-targeting instructions
brand impersonation
The site grammarly.net fully replicates the official Grammarly brand (title, meta description, OG tags, Twitter card, logo assets, and all content) while operating on the lookalike domain grammarly.net instead of the legitimate grammarly.com. All canonical and alternate link tags point to www.grammarly.com, confirming the serving domain is not the brand owner. (location: page.html line 1 – <title>, canonical href, og:url all reference grammarly.com while the scanned URL is https://grammarly.net)
malicious redirect
The page is served from grammarly.net but every canonical link, og:url, and hreflang alternate explicitly redirects/points visitors to https://www.grammarly.com. This domain-squatting pattern is commonly used to intercept traffic, inject ads, or conditionally redirect users to phishing pages before forwarding to the legitimate site. (location: page.html line 1 – <link rel="canonical" href="https://www.grammarly.com/"/> and all hreflang alternates)
phishing
The page presents a sign-up flow ('Sign up – It's free', 'Sign up with Google') on a non-official domain (grammarly.net). Users who submit credentials or OAuth consent on this domain are interacting with infrastructure not controlled by Grammarly Inc., posing a credential-harvesting risk. (location: page-text.txt lines 1-2 – sign-up CTAs rendered on grammarly.net)
curl https://api.brin.sh/domain/grammarly.netCommon questions teams ask before deciding whether to use this domain in agent workflows.
grammarly.net currently scores 40/100 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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