context safety score
A score of 47/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
brand impersonation
The domain postman.co closely mimics the legitimate Postman brand (postman.com), a well-known API development platform. The .co TLD is commonly used in typosquatting and brand impersonation attacks to deceive users and automated agents into trusting a fraudulent site as the authentic Postman service. (location: domain: postman.co)
credential harvesting
The site returns an authentication error ('You are not authenticated by the server') as its primary response, which is consistent with a credential harvesting setup that presents a login challenge or intercepts authentication flows. Combined with the impersonated domain, this pattern suggests the site may be designed to capture credentials from users or agents attempting to authenticate with what they believe is the real Postman service. (location: page.html / page-text.txt: authenticationError response)
phishing
The combination of a lookalike domain (postman.co vs postman.com) and an authentication-gating response is a classic phishing pattern targeting users and AI agents that interact with Postman APIs. Victims directed to this domain may unknowingly submit API keys or credentials. (location: domain: postman.co, page content: authenticationError)
social engineering
The domain age is unknown (null WHOIS data) and WHOIS privacy status is also null, suggesting the registration details are obscured or the domain is newly registered — both are common attributes of social engineering infrastructure designed to impersonate trusted brands before detection. (location: metadata.json: whois.domain_age_days=null, whois.privacy_redacted=null)
curl https://api.brin.sh/domain/postman.coCommon questions teams ask before deciding whether to use this domain in agent workflows.
postman.co currently scores 47/100 with a suspicious verdict and medium 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.
integrate brin in minutes — one GET request is all it takes. query the api, browse the registry, or download the full dataset.