Is patagonia.com safe?

suspiciouslow confidence
37/100

context safety score

A score of 37/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.

identity
100
behavior
60
content
0
graph
30

9 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

medium

cloaking

Page uses meta refresh redirect

high

malicious redirect

The POST form action is set to 'file:///Users/jreyesco/Downloads/$(original_url)' — a local file:// URI combined with an unresolved ESI variable. This routes POST submissions (including checkout data) to a local attacker-controlled path rather than the legitimate Patagonia server. This is a hallmark of a bot-failover page that has been tampered with or exfiltrated from a CDN and repurposed locally. (location: page.html:220)

critical

credential harvesting

The ESI POST replay form (id='wr', name='waitroomform') captures and re-submits all POST body parameters — including checkout form fields — via hidden inputs. The form action targets a local file:// path ('file:///Users/jreyesco/Downloads/$(original_url)'), meaning all submitted data (credentials, payment info, PII) would be sent to an attacker-controlled local destination rather than Patagonia's servers. The Luhn-check logic strips valid credit card numbers before storage, but all other POST fields (names, addresses, passwords, tokens) are preserved and replayed. (location: page.html:220-322)

high

hidden content

The page contains extensive ESI (Edge Side Includes) markup including esi:vars, esi:function, esi:foreach, esi:assign, and esi:choose blocks that are invisible to the end user but process and manipulate POST data server-side. These blocks implement a full Luhn algorithm for credit card detection and conditionally suppress CC numbers while capturing all other POST fields. This logic is hidden from the browser's rendered view. (location: page.html:219-322)

high

brand impersonation

The page impersonates the legitimate Patagonia brand using the official Patagonia logo (/media/SPA-sitefailover/sitedownpage/images/patagonia-logo.png), official customer service email addresses (customer_service@patagonia.com, directsales.europe@patagonia.com, customerservice.japan@patagonia.com), official phone numbers, and Patagonia's visual design language. The page was saved locally (file:///Users/jreyesco/Downloads/botfailover%20(5).html) and appears to be a cloned/exfiltrated copy of Patagonia's Akamai CDN failover page repurposed for credential capture. (location: page.html:2, page.html:333, page.html:347)

high

social engineering

The page title reads 'Hang Tight! Routing to checkout...' and the visible message reassures users the site will automatically refresh and redirect them back. This creates a false sense of legitimacy and patience, keeping victims on the page while their POST data (checkout/payment submissions) is harvested. The 30-second auto-submit timer (setTimeout 30000ms) ensures POST data is silently re-submitted to the attacker's endpoint. (location: page.html:32, page.html:313-319)

medium

obfuscated code

The file was saved locally as 'botfailover (5).html' (evidenced by the HTML comment on line 2) but is being served or analyzed in the context of patagonia.com. The ESI variables such as $(original_url), $(POST), $(REQUEST_METHOD), and $(QUERY_STRING) are CDN-layer template variables that would be processed by Akamai's ESI engine before delivery. When served outside that environment (e.g., locally or via a rogue proxy), these variables remain unresolved, making the true redirect destination dynamic and difficult to statically analyze. (location: page.html:2, page.html:184-220)

API

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

FAQ: how to interpret this assessment

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

Is patagonia.com safe for AI agents to use?

patagonia.com 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.

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.

start scoring agent dependencies.

integrate brin in minutes — one GET request is all it takes. query the api, browse the registry, or download the full dataset.