context safety score
A score of 49/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
phishing
3 deceptive links where visible host does not match destination host
obfuscated code
Script tagged 'mng_admiral_script' uses double-nested percent-encoding (decodeURI(decodeURI(...))) to conceal the variable name it registers on window and the localStorage key it reads. The same block dynamically injects an external script from 'thebestpaints.com' — a domain unrelated to the publisher — assembled via obfuscated source string. Double-decode obfuscation is a known technique to evade static scanners while executing arbitrary third-party code. (location: page.html line 17-18, <script id='mng_admiral_script'>)
malicious redirect
An external JavaScript file is loaded from 'https://thebestpaints.com/public/q4mx_vrk5ryyx.v2.js'. This domain ('thebestpaints.com') has no affiliation with the Broomfield Enterprise or its known ad/analytics vendors. The script is injected dynamically after the window name is set via obfuscated decodeURI calls. Loading unvetted third-party scripts from unrelated domains can redirect users, exfiltrate data, or serve malicious payloads. (location: page.html line 17, A.src='https://thebestpaints.com/public/q4mx_vrk5ryyx.v2.js')
obfuscated code
The second closure in 'mng_admiral_script' accesses localStorage using a key constructed from a doubly percent-encoded string and reads a '.lgk' property to set ad targeting values via googletag pubads(). The obfuscation of both the googletag global name ('googletag') and the localStorage key obscures what data is being read and forwarded to the ad network, complicating security auditing. (location: page.html line 18, second IIFE in <script id='mng_admiral_script'>)
curl https://api.brin.sh/domain/broomfieldenterprise.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
broomfieldenterprise.com currently scores 49/100 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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