building-detection-rules-with-sigma
Builds vendor-agnostic detection rules using the Sigma rule format for threat detection across SIEM platforms including Splunk, Elastic, and Microsoft Sentinel. Use when creating portable detection logic from threat intelligence, mapping rules to MITRE ATT&CK techniques, or converting community Sigma rules into platform-specific queries using sigmac or pySigma backends.
72
—
Does it follow best practices?
Impact
—
No eval scenarios have been run
Advisory
Suggest reviewing before use
Security
1 medium severity finding. This skill can be installed but you should review these findings before use.
W011: Third-party content exposure detected (indirect prompt injection risk)
What this means
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.
Why it was flagged
Third-party content exposure detected (high risk: 0.75). The required runtime workflow ingests Sigma rule YAML files from a user-supplied directory (`--directory` / `Path(directory).rglob("*.yml")`), and those YAMLs are free-form text authored by outsiders (e.g., community Sigma rules or downloaded rule sets), which the agent parses into LLM-readable strings (e.g., `rule.title`, `rule.tags`, and error messages) and includes in the generated JSON report (`sigma_output.json`).
- Repository
- mukul975/Anthropic-Cybersecurity-Skills
- Commit
673da1f
- Audited
- Security analysis
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.