context safety score
A score of 48/100 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
The domain 'p-msedge.net' impersonates Microsoft Edge ('msedge') by incorporating the well-known Microsoft Edge browser identifier into a non-Microsoft domain. The 'p-' prefix is a common typosquatting/subdomain-spoofing pattern used to mimic official Microsoft infrastructure (e.g., edge.microsoft.com, msedge.net is not a registered Microsoft domain). (location: domain: p-msedge.net)
phishing
The domain pattern 'p-msedge.net' is consistent with phishing infrastructure designed to impersonate Microsoft services. TLS is not connected and the certificate is invalid, which is atypical for a legitimate Microsoft property and consistent with hastily deployed phishing pages or redirect infrastructure. (location: metadata.json: tls.connected=false, tls.cert_valid=false)
malicious redirect
The site returned empty page content (page.html, page-text.txt, and page-hidden.txt are all empty) despite the domain being active. This is consistent with a cloaking or conditional redirect setup where content is only served to targeted victims (e.g., based on user-agent, referrer, or geolocation), hiding malicious behavior from scanners. (location: page.html, page-text.txt, page-hidden.txt (all empty))
hidden content
All content files (page.html, page-text.txt, page-hidden.txt) are completely empty, yet the domain resolves and was scanned. This may indicate server-side cloaking where malicious content is withheld from automated scanners while being served to human targets or specific user agents. (location: page.html, page-text.txt, page-hidden.txt)
curl https://api.brin.sh/domain/p-msedge.netCommon questions teams ask before deciding whether to use this domain in agent workflows.
p-msedge.net currently scores 48/100 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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