detecting-supply-chain-attacks-in-ci-cd

name	detecting-supply-chain-attacks-in-ci-cd
description	Scans GitHub Actions workflows and CI/CD pipeline configurations for supply chain attack vectors including unpinned actions, script injection via expressions, dependency confusion, and secrets exposure. Uses PyGithub and YAML parsing for automated audit. Use when hardening CI/CD pipelines or investigating compromised build systems.
domain	cybersecurity
tags	["detecting","supply","chain","attacks"]
subdomain	security-operations
version	1.0
author	oyi77
license	Apache-2.0
atlas_techniques	["AML.T0010","AML.T0104"]
nist_ai_rmf	["GOVERN-5.2","MAP-1.6","MANAGE-2.2"]
nist_csf	["DE.CM-01","RS.MA-01","GV.OV-01","DE.AE-02"]

Detecting Supply Chain Attacks In Ci Cd

Overview

Cybersecurity skill for detecting supply chain attacks in ci cd. Follows industry best practices and security standards.

When to Use

Trigger phrases:

• "detecting supply chain attacks in ci cd"

• "When investigating security incidents that require detecting supply chain attack"

• "When building detection rules or threat hunting queries for this domain"

• "When SOC analysts need structured procedures for this analysis type"

• When investigating security incidents that require detecting supply chain attacks in ci cd

• When building detection rules or threat hunting queries for this domain

• When SOC analysts need structured procedures for this analysis type

• When validating security monitoring coverage for related attack techniques

When NOT to Use

• When you lack proper authorization for testing
• For production systems without change management
• When the task requires legal or compliance expertise beyond technical scope

Prerequisites

• Familiarity with security operations 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

Workflow

# Example: IOC detection
import re

IOC_PATTERNS = {
    "ip": r"\b(?:\d{1,3}\.){3}\d{1,3}\b",
    "domain": r"\b[a-z0-9-]+\.[a-z]{2,}\b",
    "hash_md5": r"\b[a-f0-9]{32}\b",
    "hash_sha256": r"\b[a-f0-9]{64}\b",
}

def extract_iocs(text: str) -> dict:
    return {k: re.findall(v, text) for k, v in IOC_PATTERNS.items()}