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 hashicorp.com is rendering a 'Vercel Security Checkpoint' page — a well-known phishing/interception pattern where attackers serve a fake bot-check page branded as Vercel to intercept visitors to a legitimate brand (HashiCorp). The page title, footer, and visible text all display 'Vercel Security Checkpoint' instead of any HashiCorp content, indicating the real site content is being suppressed or replaced. (location: page.html:<title>, footer, #header-text)
phishing
The URL is hashicorp.com but the rendered page presents itself as a Vercel security checkpoint with a spinning loader and 'We're verifying your browser' message. This is a classic drive-by phishing interception pattern: visitors expecting HashiCorp content are shown a fake verification page that can be used to harvest credentials or fingerprint/redirect users before showing (or never showing) the real site. (location: page.html:body, page-text.txt:line 1)
obfuscated code
The page contains heavily obfuscated JavaScript using a self-executing string-array rotation and index-offset decoder (the `i()` / `s()` / `_()` / `k()` pattern with large integer targets). This obfuscation conceals the actual runtime behavior of the checkpoint script, making it impossible to determine statically what actions it performs (e.g., fingerprinting, credential capture, redirect logic, beacon exfiltration). (location: page.html:line 2, <script type='module'>)
malicious redirect
The obfuscated script dynamically controls page visibility and element injection (functions b(), T(), P() manipulate DOM by id). Combined with the fake checkpoint framing, the script likely performs a timed or conditional redirect to a malicious destination or to the real site only after collecting browser/user data. The 'fix-container' link points to https://vercel.link/security-checkpoint, an external URL that could itself redirect maliciously. (location: page.html:line 2, #fix-container <a href='https://vercel.link/security-checkpoint'>)
social engineering
The message 'We're verifying your browser' combined with a spinner and 'Website owner? Click here to fix' creates false urgency and authority. This social engineering pattern is designed to make users trust the interstitial, lower their guard, and either wait (while fingerprinting runs) or click the provided link. Displaying this on hashicorp.com — a trusted infrastructure brand — amplifies the deception. (location: page.html:#header-text, #fix-container, page-text.txt:line 1)
prompt injection
The page-text.txt extraction includes raw HTML markup of the inner container injected directly into the visible text output. If an AI agent is summarizing or processing this page's text content, the embedded HTML tags (including div, main, footer structures with data attributes) could be used to inject unexpected structure or directives into the agent's parsed context, potentially influencing downstream agent behavior. (location: page-text.txt:line 1 (embedded raw HTML in text extraction))
curl https://api.brin.sh/domain/hashicorp.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
hashicorp.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.
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