Is banggood.com safe?

suspiciouslow confidence
43/100

context safety score

A score of 43/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.

identity
100
behavior
60
content
15
graph
30

11 threat patterns detected

medium

encoded payload

suspicious base64-like blobs detected in page content

medium

malicious redirect

script/meta redirect patterns detected in page source

high

cloaking

Page conditionally redirects based on referrer or user-agent

medium

social engineering

Aggressive new-user popup claims 'You have won an $20 coupon package' to pressure visitors into registering, using false prize framing as a persuasion tactic. (location: page.html:1316, page-text.txt:909)

low

hidden content

Modal dialogs with class 'display:none' contain cookie consent UI and promotional popups that are rendered invisibly until triggered by JavaScript, including a birthday coupon modal and a system-maintenance notice modal. While standard practice, the hidden maintenance notice references a phone number (001 3235700368) and email (order@banggood.com) that could be spoofed in a cloned phishing site. (location: page.html:729, 1297, 1324)

low

hidden content

A feedback sidebar element is explicitly hidden via inline style (style='display:none;') but remains in the DOM and could be activated by injected scripts. (location: page.html:1120)

low

social engineering

Maintenance notice modal dated 3-Sept-21 is still present in the live page, targeting 'Danish customers' with contact details that may no longer be valid, potentially misdirecting support inquiries. (location: page.html:1327-1341, page-text.txt:920-933)

medium

hidden content

A script tag at the very end of the body loads JavaScript from a heavily obfuscated path '/H0Ilh3/FsFx/X5inP/ViUEZ/Entu/miiEDXtzf6JV2XzE/CWFtAQ/WwsNK00T/MUQB' with no async/defer attributes. The path is structurally atypical compared to all other script includes and does not match any known Banggood CDN pattern, warranting further inspection. (location: page.html:1619)

high

obfuscated code

Terminal script src uses a deeply randomized path segment ('/H0Ilh3/FsFx/X5inP/ViUEZ/Entu/miiEDXtzf6JV2XzE/CWFtAQ/WwsNK00T/MUQB') inconsistent with all other static asset paths (s.staticbg.com, /cache/static_cache_read/, etc.). This pattern is characteristic of obfuscated or dynamically generated malicious script injection. (location: page.html:1619)

low

social engineering

Device fingerprinting script silently tracks user agent and device ID on page load, and on failure exfiltrates error metadata (including full userAgent string) to a third-party domain www.tieszhu.com via dynamically injected script tag with no user disclosure. (location: page.html:46-57)

low

hidden content

On error, the device-ID initialization script loads a beacon to 'https://www.tieszhu.com/e.html' including deviceIdError, deviceIdIndex, and deviceIdUserAgent parameters, silently sending browser fingerprint data to a non-Banggood third-party domain. (location: page.html:49)

API

curl https://api.brin.sh/domain/banggood.com

FAQ: how to interpret this assessment

Common questions teams ask before deciding whether to use this domain in agent workflows.

Is banggood.com safe for AI agents to use?

banggood.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.

How should I interpret the score and verdict?

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.

How does brin compute this domain score?

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.

What do identity, behavior, content, and graph mean for this domain?

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.

Why does brin scan packages, repos, skills, MCP servers, pages, and commits?

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.

Can I rely on a safe verdict as a full security guarantee?

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.

When should I re-check before using an entity?

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.

Last Scanned

March 4, 2026

Verdict Scale

safe80–100
caution50–79
suspicious20–49
dangerous0–19

Disclaimer

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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