Is toogoodtogo.com safe?

suspiciouslow confidence
40/100

context safety score

A score of 40/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.

identity
100
behavior
80
content
0
graph
30

7 threat patterns detected

medium

encoded payload

suspicious base64-like blobs detected in page content

high

js obfuscation

JavaScript uses Function constructor for runtime code generation

high

brand impersonation

The page at toogoodtogo.com renders a 'Vercel Security Checkpoint' page, impersonating Vercel's bot protection UI. toogoodtogo.com has no known affiliation with Vercel. Serving a fake Vercel checkpoint page on a non-Vercel-owned domain is a classic brand impersonation tactic used to deceive users and automated agents into trusting the page as a legitimate infrastructure gate. (location: page.html <title>Vercel Security Checkpoint</title> and footer text)

high

obfuscated code

The page contains heavily obfuscated JavaScript using string-array rotation, numeric index obfuscation (e.g. parseInt(c(167))/1+parseInt(c(171))/2...), and shuffled lookup arrays. This pattern is characteristic of tools like javascript-obfuscator and is used to hide the true intent of the script — commonly seen in credential harvesting, fingerprinting, or redirect chains — from static analysis tools and security scanners. (location: page.html <script type="module"> block, lines 2)

medium

social engineering

The page presents a fake 'browser verification' spinner with the message 'We're verifying your browser', a common social engineering technique used to stall users while obfuscated scripts execute in the background (fingerprinting, token theft, or redirect preparation). The noscript fallback instructs users to 'Enable JavaScript to continue', pressuring execution of the hidden script payload. (location: page.html #header-text and #header-noscript-text elements)

high

malicious redirect

The obfuscated JavaScript dynamically manipulates DOM elements (via string-concatenated getElementById, style, and removal calls) and is structured to execute conditional logic after a simulated 'verification' delay. This pattern is strongly associated with client-side redirect chains where the user is forwarded to a malicious destination only after the script completes its checks, making the redirect invisible to static crawlers. (location: page.html <script type="module"> — functions b(), T(), P() and the obfuscated self-invoking function)

medium

hidden content

The #root container is initially set to display:none in CSS, and the #fix-container div is explicitly set to style='display: none;'. Content is revealed dynamically by the obfuscated script. This means the true page content and any injected elements are hidden from static analysis and non-JS crawlers, a technique used to conceal malicious payloads from automated scanners. (location: page.html CSS rule '#root{display:none}' and <div id='fix-container' style='display: none;'>)

API

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

FAQ: how to interpret this assessment

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

Is toogoodtogo.com safe for AI agents to use?

toogoodtogo.com currently scores 40/100 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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