security professional security skill risk: medium
Falco Container Threat Detection Rules
Deploy and manage Falco rules for runtime security detection in containerized environments. Parse Falco alerts for incident response.
- Policy sensitive
- Human review
SKILL 4 files · 2 folders
SKILL.md
---
name: performing-cloud-native-forensics-with-falco
description: "Uses Falco YAML rules for runtime threat detection in containers and Kubernetes, monitoring syscalls for shell"
---
# Performing Cloud Native Forensics with Falco
## When to Use
- When conducting security assessments that involve performing cloud native forensics with falco
- When following incident response procedures for related security events
- When performing scheduled security testing or auditing activities
- When validating security controls through hands-on testing
## Prerequisites
- Familiarity with cloud security concepts and tools
- Access to a test or lab environment for safe execution
- Python 3.8+ with required dependencies installed
- Appropriate authorization for any testing activities
## Instructions
Deploy and manage Falco rules for runtime security detection in containerized
environments. Parse Falco alerts for incident response.
```yaml
# Custom Falco rule for detecting shell in container
- rule: Shell Spawned in Container
desc: Detect shell process started in a container
condition: >
spawned_process and container
and proc.name in (bash, sh, zsh, dash, csh)
and not proc.pname in (docker-entrypo, supervisord)
output: >
Shell spawned in container
(user=%user.name command=%proc.cmdline container=%container.name
image=%container.image.repository)
priority: WARNING
tags: [container, shell, mitre_execution]
```
Key detection rules:
1. Shell spawn in non-interactive containers
2. Sensitive file access (/etc/shadow, /etc/passwd)
3. Outbound connections from unexpected containers
4. Privilege escalation via setuid/setgid
5. Container escape via mount or ptrace
## Examples
```bash
# Run Falco with custom rules
falco -r /etc/falco/custom_rules.yaml -o json_output=true
# Parse JSON alerts
cat /var/log/falco/alerts.json | python3 -c "import json,sys; [print(json.loads(l)['output']) for l in sys.stdin]"
```
REQUIRED CONTEXT
- lab or test environment
- python 3.8+
EXPECTED OUTPUT
- Format
- markdown
- Constraints
- include yaml rules
- include bash examples
- list key detection rules
EXAMPLES
Includes one custom Falco YAML rule and two bash command examples for running Falco and parsing alerts.
CAVEATS
- Missing context
- Target audience or user expertise level beyond the listed prerequisites
- Exact output format expected from the AI (e.g., step-by-step commands, full rule files, analysis report)
- Lab environment constraints or Falco version compatibility
- Ambiguities
- Instructions section gives high-level goals ('Deploy and manage Falco rules... Parse Falco alerts') without concrete steps or success criteria.
- Does not specify desired output format or length for alert parsing or rule deployment.
QUALITY
- OVERALL
- 0.52
- CLARITY
- 0.75
- SPECIFICITY
- 0.55
- REUSABILITY
- 0.35
- COMPLETENESS
- 0.50
IMPROVEMENT SUGGESTIONS
- Add explicit placeholders (e.g., {{rule_file_path}}, {{container_name}}) to improve reusability as a template.
- Replace the vague 'Instructions' paragraph with numbered, actionable steps for deploying rules and parsing alerts.
- Specify the expected response structure (e.g., 'Return a validated YAML file plus sample Python parser code').
USAGE
Copy the prompt above and paste it into your AI of choice — Claude, ChatGPT, Gemini, or anywhere else you're working. Replace any placeholder sections with your own context, then ask for the output.
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