context safety score
A score of 38/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
js obfuscation
JavaScript uses eval() with String.fromCharCode — common obfuscation
js obfuscation
JavaScript appears to use a common packer pattern (p,a,c,k,e,d)
obfuscated code
The entire page consists of a single heavily obfuscated JavaScript payload using a packed eval() pattern (Dean Edwards p,a,c,k,e,r packer). The code is deliberately obscured to hide its logic from static analysis and security tools. (location: page.html:1)
malicious redirect
The obfuscated script performs automatic browser redirection via `location.href = h() ? v : B()`. The redirect destination is determined at runtime based on user-agent sniffing (iOS, Android, macOS, Windows, Linux) and URL query parameters, routing users to different app store URLs or a fallback domain (dlink.cloud). This is a classic traffic distribution system (TDS) used in malvertising and phishing campaigns. (location: page.html:1)
social engineering
The script silently redirects users without any visible page content (page-text.txt is empty) — the page renders nothing to the user but immediately executes a redirect. This invisible redirect technique is used to deceive users and bypass security awareness, as victims see no warning before being sent to a destination URL. (location: page.html:1, page-text.txt)
hidden content
The page has no visible text content whatsoever (page-text.txt is empty, page-hidden.txt is empty), yet contains active JavaScript that silently executes and redirects the user. The entire page behavior is hidden from the user and from simple text-based content scanners. (location: page.html:1)
prompt injection
The page targets AI agents and automated crawlers by presenting an empty visible surface while hiding all logic inside a packed eval() script. An AI agent visiting this URL would receive no textual context about the page's true purpose, making it difficult to reason about or flag the destination. The use of query-parameter-driven redirect logic (utm_campaign, utm_source, utm_content, referrer fields) suggests the operator can craft URLs to manipulate agent behavior or tracking attribution. (location: page.html:1)
curl https://api.brin.sh/domain/deeplink.devCommon questions teams ask before deciding whether to use this domain in agent workflows.
deeplink.dev currently scores 38/100 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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