context safety score
A score of 43/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
encoded payload
suspicious base64-like blobs detected in page content
js obfuscation
JavaScript uses Function constructor for runtime code generation
brand impersonation
The page at adlibris.com (a legitimate Swedish book retailer) is serving a 'Vercel Security Checkpoint' interstitial page rather than the expected adlibris.com content. This impersonates Vercel's bot-protection branding on a domain that is not owned or operated by Vercel, misleading users and agents about the true identity of the page operator. (location: page.html:<title> and page body - 'Vercel Security Checkpoint' branding served on adlibris.com)
obfuscated code
The page contains heavily obfuscated JavaScript using string-array rotation, integer arithmetic self-checks (anti-tamper), and split string concatenation to reconstruct DOM API calls (e.g., getElementById, style.setProperty, removeEventListener). This pattern is characteristic of anti-analysis obfuscation used to hide the true behavior of client-side scripts, including potential fingerprinting, redirection, or credential harvesting logic that cannot be statically analyzed. (location: page.html:line 2 - <script type="module"> block with functions i(), M(), C(), b(), T(), P() and large obfuscated string arrays)
malicious redirect
The page is an interstitial checkpoint served on adlibris.com that withholds actual site content pending JavaScript execution and apparent browser fingerprinting. The obfuscated script controls what content is displayed and where the user is ultimately sent, creating an invisible redirect gate. Legitimate Vercel firewall pages are served from vercel infrastructure, not injected into the target domain's HTML response in this manner. (location: page.html:line 2-3 - obfuscated script controls display of #root, #header-text, #failure-text elements and page flow)
social engineering
The visible page text 'We're verifying your browser' and 'Enable JavaScript to continue' are classic social engineering prompts used to coerce users and automated agents into enabling scripting and interacting with the page, lowering their guard while obfuscated code executes. This pattern is frequently used in drive-by-download and credential-harvesting campaigns. (location: page-text.txt and page.html - #header-noscript-text and #header-text elements)
hidden content
The #root div containing all main page content is initially set to display:none (via CSS '#root{display:none}') and is only revealed by the obfuscated JavaScript after it runs. This hides the true page content from non-JS agents, crawlers, and security scanners, while delivering different or dynamic content to executing browsers. (location: page.html:line 1 - CSS rule '#root[data-astro-cid-nbv56vs3]{display:none}' and line 3 - <div id="root" style not yet overridden)
curl https://api.brin.sh/domain/adlibris.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
adlibris.com 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 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.