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
Domain 'bedrockplatform.bid' mimics Amazon Web Services 'Amazon Bedrock' branding (AWS's managed AI/ML service). The use of 'bedrock' combined with 'platform' on a non-AWS TLD (.bid) strongly suggests impersonation of AWS Bedrock to deceive users or AI agents into trusting the domain as a legitimate AWS service. (location: metadata.json: domain=bedrockplatform.bid)
phishing
Domain uses a .bid TLD — a high-risk TLD commonly associated with phishing infrastructure. Combined with brand impersonation of AWS Bedrock, this domain pattern is consistent with a phishing site targeting AWS/cloud users. TLS is not connected and certificate is invalid, indicating either a parked phishing domain or one that serves content over HTTP to avoid certificate scrutiny. (location: metadata.json: tls.connected=false, tls.cert_valid=false, domain=bedrockplatform.bid)
malicious redirect
The page returned empty HTML and no visible text content despite the domain being reachable enough to have metadata collected. This is consistent with a cloaked or redirect-based phishing site that serves content conditionally (e.g., only to victims from specific referrers, user-agents, or geolocations) while presenting a blank page to scanners. (location: page.html (empty), page-text.txt (empty))
hidden content
All content files (page.html, page-text.txt, page-hidden.txt) are empty, yet the domain exists and has metadata. This absence of detectable content is a known evasion technique where malicious content is hidden behind JavaScript rendering, bot-detection cloaking, or conditional serving, making static analysis impossible and suggesting deliberate obfuscation. (location: page.html (0 bytes), page-text.txt (0 bytes), page-hidden.txt (0 bytes))
curl https://api.brin.sh/domain/bedrockplatform.bidCommon questions teams ask before deciding whether to use this domain in agent workflows.
bedrockplatform.bid 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.
integrate brin in minutes — one GET request is all it takes. query the api, browse the registry, or download the full dataset.