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
script/meta redirect patterns detected in page source
malicious redirect
The entire page consists of a single JavaScript redirect to a raw IP address (103.1.43.202) with no legitimate content. Redirecting to a bare IP rather than a named domain is a strong indicator of malicious infrastructure — used to evade domain-based blocklists and obscure the final destination. (location: page.html:1)
hidden content
The page renders no visible text content whatsoever (page-text.txt is empty), meaning all page behavior is covert. The sole action is a silent JavaScript redirect, hiding the true destination from casual inspection and from users without JS awareness. (location: page.html:1)
prompt injection
The page presents no human-readable content but executes an immediate JS redirect. An AI agent crawling or evaluating this URL would receive no semantic content — only an instruction to navigate to a raw IP. This pattern can be used to silently redirect agentic crawlers to attacker-controlled infrastructure for further exploitation or content injection. (location: page.html:1)
phishing
The domain smsm.ph presents no legitimate content and immediately bounces visitors to an unrelated raw IP address (103.1.43.202). This infrastructure pattern — a named domain acting purely as a redirect hop to an IP — is commonly used in phishing chains to add a layer of indirection and avoid direct IP-based detection. (location: metadata.json, page.html:1)
curl https://api.brin.sh/domain/smsm.phCommon questions teams ask before deciding whether to use this domain in agent workflows.
smsm.ph 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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