frontend security audit
Perform evidence-based frontend security audits for XSS, CSP gaps, and insecure cookies with ranked remediation plans.
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See it in action
You say
Audit the src/components/search directory for XSS and check if our CSP in the meta tags is actually protecting us from inline script execution.
Your agent does
Audit complete for src/components/search.
Confirmed Findings: [FSA-001] Critical: Reflected XSS in SearchBar.tsx via 'query' param. No encoding at sink. [FSA-002] Medium: Insecure CSP meta tag. 'unsafe-inline' detected in script-src.
Proposed Fixes:
- Sanitize 'query' using DOMPurify.
- Move CSP to headers.
Approve?
What you get
About this skill
The problem
Static analysis tools produce too much noise, while manual security reviews are slow and easy to miss deep data-flow vulnerabilities. Frontend developers often struggle to bridge the gap between finding a potential XSS pattern and actually proving it is exploitable in their specific framework context.
What it does
- Maps the entire frontend attack surface, including route entry points, DOM sinks, and third-party script integrations.
- Traces data flow from attacker-controlled sources through transformations to context-sensitive sinks to confirm exploitability.
- Audits Content Security Policy (CSP) delivery, verifying header-level enforcement and identifying bypass-prone source lists.
- Inspects cookie attributes (Secure, HttpOnly, SameSite) and frontend-adjacent session management for leakage risks.
- Generates a severity-ranked report using a structured rubric and provides a granular, one-to-one patch plan for approval.
Frameworks & tools
Works with modern frontend frameworks (React, Vue, Svelte), server-rendered paths, and build systems. Utilizes Python-based scanning scripts for inventory and manual repository search for deep tracing.
Why this beats prompting it yourself
Generic prompts often hallucinate security risks or suggest broad, breaking changes. This skill follows a strict operating contract that enforces read-only discovery, evidence-based validation, and mandatory approval gates before any code is modified.
Use cases
- Perform a pre-release security audit of a new frontend module or component library.
- Harden an existing application against XSS and HTML injection by tracing user-controlled inputs.
- Review and fix weak CSP configurations and insecure cookie handling.
- Verify that security patches actually close the vulnerability without introducing regressions.
Known limitations
Requires local Python 3 for the automated scanning script component. Cannot claim full exploitability from pattern matches alone without manual data-flow verification.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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