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
phishing
The domain bpcl.in appears to impersonate or relate to BPCL (Bharat Petroleum Corporation Limited), a major Indian public sector oil company. The TLS certificate could not be validated (connected=false, cert_valid=false), which is atypical for a legitimate corporate site and consistent with phishing infrastructure. (location: metadata.json: tls.connected=false, tls.cert_valid=false)
brand impersonation
The domain bpcl.in closely mimics the brand identity of BPCL (Bharat Petroleum Corporation Limited), India's Fortune 500 oil company. The legitimate domain for BPCL is bharatpetroleum.com or bpclindia.com. A .in TLD variant with no resolvable TLS and no page content is a pattern consistent with a parked or malicious domain squatting on a well-known brand abbreviation. (location: metadata.json: domain=bpcl.in)
malicious redirect
The site returned empty page content (page.html and page-text.txt are both empty) despite the domain being reachable enough to attempt a TLS handshake. Empty page bodies with TLS failures are consistent with redirect chains, cloaking, or infrastructure used to silently forward victims to a malicious destination depending on user-agent or referrer. (location: page.html (empty), page-text.txt (empty), metadata.json: tls.connected=false)
curl https://api.brin.sh/domain/bpcl.inCommon questions teams ask before deciding whether to use this domain in agent workflows.
bpcl.in 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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