defensive-xss

Detect XSS patterns and blind XSS indicators in web logs and applications.

1|Updated Apr 27, 2026
One-click install
npx skills add https://github.com/riparino/Claude-Cyber --skill defensive-xss
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: defensive-xss
Source: https://github.com/riparino/Claude-Cyber/tree/main/Claude-Blue/Skills/defensive-xss
Command: npx skills add https://github.com/riparino/Claude-Cyber --skill defensive-xss

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Detects XSS patterns and blind XSS indicators to proactively identify client-side injection threats across logs, CSP reports, and web traffic.

Core Features & Use Cases

  • Sigma rules for SIEM to detect XSS payloads in web requests.
  • KQL queries for Azure Sentinel/MDE to surface XSS-related events.
  • Guidance on threat-hunting, incident response, and hardening to reduce exposure.

Quick Start

Load and apply the full XSS detection methodology to your logs and applications.

Frequently Asked Questions about defensive-xss

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I detect XSS patterns in web logs and WAF traffic?

To detect XSS patterns in web logs and WAF traffic, you can apply Sigma rules to your SIEM and execute KQL queries in Azure Sentinel to surface malicious payloads. This methodology maps findings to MITRE ATT&CK techniques for comprehensive threat hunting.

Can I generate Sigma rules for SIEM to identify blind XSS indicators?

Yes, you can generate Sigma rules for SIEM to identify blind XSS indicators across application logs and inbound traffic. The detection methodology translates payload patterns into deployable Sigma rules to alert on client-side injection threats.

What is the best way to hunt for cross-site scripting attacks using KQL in Azure?

The best way to hunt for cross-site scripting attacks using KQL in Azure is to run targeted queries in Azure Sentinel and MDE. These KQL queries surface XSS-related events by parsing CSP reports and web request logs for known injection signatures.

Does this approach work with CSP reports to find client-side injection threats?

Yes, this approach works with CSP reports to find client-side injection threats by analyzing violation reports alongside WAF logs. Correlating these sources helps identify both successful and attempted XSS attacks mapped to MITRE ATT&CK techniques.

How do I reduce XSS exposure after detecting payloads in application logs?

To reduce XSS exposure after detecting payloads in application logs, apply the included practical hardening guidance. This involves implementing stricter Content Security Policies and remediating the specific injection vectors identified during threat hunting.

Are there limitations to detecting XSS solely through inbound and outbound traffic analysis?

Detecting XSS solely through inbound and outbound traffic analysis may miss obfuscated payloads or blind XSS executed outside monitored endpoints. Combining WAF logs with CSP reports and application log analysis provides more reliable detection gap coverage.