Discover a single-page-app's hidden backend API from its public JS bundle, then test that API for broken access control / missing authentication. One of the highest-yield web plays in modern recon — SPAs ship their entire backend route map to the browser, and the API behind them is frequently missing the auth middleware the login page implies. Built from an authorized engagement where this play found an unauthenticated financial API that an ASM scan reporting hundreds of "Criticals" completely missed. Use whenever a target serves a JS-heavy SPA (React/Vue/Angular/Next), an "app"/"console"/"dashboard"/"portal" subdomain, or any `*api*` host shows up in recon. Leaked build artifacts (source maps / .env / .git / asset-manifest) are owned by hunt-source-leak; API version-inventory and behavioral diffing by hunt-shadow-api; this skill owns mapping a live SPA's backend routes from its JS bundle and testing them for broken access control / missing auth.
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Critical
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Security
2 findings: 1 critical severity, 1 high severity. Installing this skill is not recommended: please review these findings carefully if you do intend to do so.
Detected high-risk code patterns in the skill content — including its prompts, tool definitions, and resources — such as data exfiltration, backdoors, remote code execution, credential theft, system compromise, supply chain attacks, and obfuscation techniques.
This guide is a step‑by‑step offensive playbook for harvesting API hosts/routes/secrets from SPA bundles and probing unauthenticated endpoints to find auth bypasses and privilege-elevation vectors, enabling credential theft and unauthorized data access.
The skill handles credentials insecurely by requiring the agent to include secret values verbatim in its generated output. This exposes credentials in the agent’s context and conversation history, creating a risk of data exfiltration.
The playbook explicitly instructs harvesting secrets from JS bundles (grep for API keys/ tokens) which requires reading and thus potentially outputting secret values verbatim—an LLM following this would handle secrets directly and could exfiltrate them.
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
The outsider-authored free text risk is high: the workflow explicitly curls public target-controlled HTML/JS bundles (`curl` of `https://console.target.com/...`) and then runs `grep` over those downloaded `.js` files to extract strings/hosts/routes/secrets—those page/bundle contents are outsider-authored and become LLM-readable if any part of the fetched text is passed into the agent for analysis.
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