context safety score
A score of 42/100 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 'steam-api.com' impersonates Valve's Steam platform by combining the well-known 'Steam' brand with 'api', a technical term commonly used to lend legitimacy. This typosquat/combo-squatting pattern is frequently used to deceive developers, AI agents, and users into trusting the domain as an official Steam API endpoint. (location: domain: steam-api.com)
phishing
The domain steam-api.com mimics a legitimate Steam API service. Developers or AI agents seeking Steam API credentials or integration may be deceived into submitting API keys or credentials to this lookalike domain. (location: domain: steam-api.com)
credential harvesting
A domain impersonating the Steam API (steam-api.com) is a classic credential harvesting vector, targeting Steam API keys, OAuth tokens, or user credentials from developers and automated agents interacting with what they believe to be an official Valve/Steam service. (location: domain: steam-api.com)
malicious redirect
TLS connection failed (connected=false, cert_valid=false, san_match=false) for steam-api.com. The site may be down, may redirect HTTP traffic insecurely, or may use a misconfigured/self-signed certificate to intercept traffic. Absence of valid TLS on a domain claiming to be an API endpoint is a significant risk indicator. (location: metadata.json: tls block)
social engineering
The domain name steam-api.com is engineered to appear as a developer resource or official API gateway, socially engineering developers and AI agents into trusting it for programmatic integrations, potentially leading to unauthorized data submission or API key exposure. (location: domain: steam-api.com)
curl https://api.brin.sh/domain/steam-api.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
steam-api.com currently scores 42/100 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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