context safety score
A score of 43/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
phishing
7 deceptive links where visible host does not match destination host
phishing
A fake 'CheckMates' login popup directs users to sign in via untrusted URL shorteners (tiny.cc/checkmateslogin) instead of the legitimate Check Point SSO, attempting to steal credentials. (location: HTML DOM (div#login-popup))
credential harvesting
The injected popup aims to harvest Check Point UserCenter/PartnerMap account credentials by redirecting victims to external sites. (location: HTML DOM (div#login-popup > a[href*='tiny.cc']))
brand impersonation
The popup masquerades as an official Check Point/CheckMates system prompt to gain user trust. (location: HTML DOM (div#login-popup))
social engineering
The fake login prompt uses a fraudulent promotional lure ('win some Apple AirPods!') to entice users into clicking the malicious links. (location: HTML DOM (div#login-popup))
malicious redirect
The deceptive 'Sign in' and 'create one now' links use URL shorteners (tiny.cc) to obscure the final malicious destination from users. (location: HTML DOM (href='https://tiny.cc/checkmateslogin' and 'https://tiny.cc/checkmatesnew'))
curl https://api.brin.sh/page/community.checkpoint.com%2Ft5%2FFirewall-and-Security-Management%2FNetwork-feed%2Ftd-p%2F212407Common questions teams ask before deciding whether to use this web page in agent workflows.
community.checkpoint.com/t5/Firewall-and-Security-Management/Network-feed/td-p/212407 currently scores 43/100 with a suspicious verdict and low 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 web page.
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.