context safety score
A score of 32/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
tls connection failed
Could not establish TLS connection
brand impersonation
Domain 'freefireind.in' impersonates Garena Free Fire, a popular mobile game, using an unofficial .in TLD with 'freefire' in the name to deceive players into visiting a fraudulent site. (location: domain: freefireind.in)
phishing
The domain mimics the Free Fire gaming brand on a non-official TLD (.in instead of garena.com), a common pattern for phishing pages targeting game account credentials or in-game currency. (location: domain: freefireind.in)
credential harvesting
Gaming brand impersonation sites of this type are frequently used to harvest game account login credentials. The domain pattern (freefire + country code) is consistent with credential harvesting campaigns targeting South Asian gamers. (location: domain: freefireind.in)
malicious redirect
TLS connection failed (connected=false, cert_valid=false), indicating the page may not load directly but could redirect through HTTP or serve content via a redirect chain to avoid TLS inspection, or the site was unreachable at scan time. (location: metadata.json: tls.connected=false, tls.cert_valid=false)
social engineering
The domain name pattern 'freefireind.in' (Free Fire India) is designed to appear as a legitimate regional gaming portal, exploiting geographic and brand trust to socially engineer users into interacting with the site. (location: domain: freefireind.in)
curl https://api.brin.sh/domain/freefireind.inCommon questions teams ask before deciding whether to use this domain in agent workflows.
freefireind.in currently scores 32/100 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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