context safety score
A score of 46/100 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 pubnubapi.com impersonates PubNub (pubnub.com), a legitimate real-time messaging and API platform. The addition of 'api' to the brand name is a common typosquatting/brandjacking technique designed to deceive developers and AI agents into believing they are interacting with an official PubNub API endpoint. (location: domain: pubnubapi.com)
phishing
The domain closely mimics the legitimate PubNub brand (pubnub.com) with the 'api' suffix, a pattern frequently used to target developers seeking API credentials or documentation, potentially harvesting API keys or authentication tokens. (location: domain: pubnubapi.com)
credential harvesting
A domain impersonating a real-time API platform (PubNub) is a high-risk vector for developer credential harvesting. Developers may be tricked into submitting API keys, subscribe/publish keys, or account credentials to this lookalike domain. (location: domain: pubnubapi.com)
malicious redirect
TLS connection failed (connected=false, cert_valid=false) for pubnubapi.com. The site is unreachable over HTTPS or returns no valid content, which is consistent with a parked/dormant domain that may be used for future phishing campaigns or silent redirects. The empty page.html and page-text.txt suggest the domain is either inactive or blocking scanners. (location: metadata.json: tls.connected=false, tls.cert_valid=false)
curl https://api.brin.sh/domain/pubnubapi.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
pubnubapi.com currently scores 46/100 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.
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