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Prompts Falco Container Threat Detection Rules

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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