CVE-2022-39327
Code Injection in Azure CLI is the command-line interface for Microsoft Azure
Executive Summary
CVE-2022-39327 is a high severity vulnerability affecting appsec. It is classified as Code Injection. Ensure your systems and dependencies are patched immediately to mitigate exposure risks.
Precogs AI Insight
"Azure CLI contains a vulnerability where it inadvertently logs sensitive information. If configured to run in CI/CD pipelines with verbose logging, it exposes Azure access tokens and secrets in plain text. Precogs PII & Secrets Scanner continuously monitors log sinks for exposed credentials."
What is this vulnerability?
CVE-2022-39327 is categorized as a high Code Injection flaw with a CVSS base score of 8.1. Based on our vulnerability intelligence, this issue occurs when the application fails to securely handle untrusted data boundaries.
Azure CLI is the command-line interface for Microsoft Azure. In versions previous to 2.40.0, Azure CLI contains a vulnerability for potential code injection. Critical scenarios are where a hosting machine runs an Azure CLI command where parameter values have been provided by an external source. The vulnerability is only applicable when the Azure CLI command is run on a Windows machine and with any version of PowerShell and when the parameter value contains the & or | symbols. If any of these prerequisites are not met, this vulnerability is not applicable. Users should upgrade to version 2.40.0 or greater to receive a a mitigation for the vulnerability.
This architectural defect enables adversaries to bypass intended security controls, directly manipulating the application's execution state or data layer. Immediate strategic intervention is required.
Risk Assessment
| Metric | Value |
|---|---|
| CVSS Base Score | 8.1 (HIGH) |
| Vector String | CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H |
| Published | October 25, 2022 |
| Last Modified | November 21, 2024 |
| Related CWEs | CWE-94, CWE-78 |
Impact on Systems
✅ Data Exfiltration: Attackers can extract sensitive data from backend databases, configuration files, or internal services.
✅ Authentication Bypass: Exploiting this flaw may allow unauthorized access to protected resources and administrative interfaces.
✅ Lateral Movement: Once initial access is gained, attackers can pivot to internal systems and escalate privileges.
How to Fix and Mitigate CVE-2022-39327
- Apply Vendor Patches: Upgrade affected components to their latest, non-vulnerable versions immediately.
- Implement Input Validation: Ensure all user-supplied data is validated, sanitized, and type-checked before processing.
- Deploy Runtime Protection: Use Precogs continuous monitoring to detect exploitation attempts in real time.
- Audit Dependencies: Review and update all third-party libraries and transitive dependencies.
Defending with Precogs AI
Azure CLI contains a vulnerability where it inadvertently logs sensitive information. If configured to run in CI/CD pipelines with verbose logging, it exposes Azure access tokens and secrets in plain text. Precogs PII & Secrets Scanner continuously monitors log sinks for exposed credentials.
Use Precogs to continuously scan your codebase, binaries, APIs, and infrastructure for this vulnerability class and related attack patterns. Our AI-powered detection engine combines static analysis with threat intelligence to identify exploitable weaknesses before attackers do.
Vulnerability Code Signature
Attack Data Flow
| Stage | Detail |
|---|---|
| Source | Untrusted payload via API or file upload |
| Vector | Input passed to a dynamic code evaluation function |
| Sink | eval(), exec(), or similar unsafe execution sink |
| Impact | Remote Code Execution (RCE), full system compromise |
Vulnerable Code Pattern
# ❌ VULNERABLE: Dynamic code evaluation
def process_data(user_input):
# Taint sink: arbitrary code execution
result = eval(user_input)
return result
Secure Code Pattern
# ✅ SECURE: Safe parsing
import ast
def process_data(user_input):
# Sanitized parsing: only evaluates literal structures
result = ast.literal_eval(user_input)
return result
How Precogs Detects This
Precogs AI Analysis Engine identifies unsafe dynamic code evaluation paths by tracking untrusted data into sinks like eval() and exec().\n