context safety score
A score of 37/100 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
malicious redirect
script/meta redirect patterns detected in page source
cloaking
Page conditionally redirects based on referrer or user-agent
js obfuscation
JavaScript uses Function constructor for runtime code generation
credential harvesting
The page contains an inline JavaScript block that hooks (monkey-patches) the browser's Storage.prototype.setItem, getItem, and removeItem methods to intercept ALL localStorage read/write/delete operations. All values written to or read from localStorage are captured into a local object (localStorageData) and queued for processing. This is a classic credential/session-token harvesting technique: authentication tokens, session IDs, and other sensitive values stored by the site's own scripts are silently captured before they reach native storage. The code even dumps the entire existing localStorage contents at execution time. Comments are in Chinese, indicating the code is not part of the legitimate daraz.pk codebase and was likely injected. (location: page.html lines 15-110, inside the first inline <script> block in <head>)
hidden content
The localStorage-hijacking script is conditionally activated only for iOS 18+ (iosVersion >= 18) based on User-Agent parsing, making it invisible to most desktop scanners and analysts running non-iOS environments. The condition 'if (iosVersion < 18) { return; }' gates the entire interception payload, meaning it executes silently on targeted iOS devices while appearing inactive elsewhere. This is a deliberate evasion technique to avoid detection during standard security scans. (location: page.html lines 26-37, inside the first inline <script> block in <head>)
obfuscated code
All comments and log strings inside the localStorage-hooking script are written in Chinese (e.g., '通过ua判断系统为ios26，开始劫持localStorage', '劫持到数据setItem', '处理任务时发生错误'), while the rest of the page is in English. The script uses a task-queue deferred-write pattern (setInterval processTaskQueue) to obscure its write-back behavior. This obfuscation—mixing languages, deferred execution, and conditional activation—is designed to evade automated threat detection and human code review. (location: page.html lines 39-110)
curl https://api.brin.sh/domain/daraz.pkCommon questions teams ask before deciding whether to use this domain in agent workflows.
daraz.pk currently scores 37/100 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.
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