CVE-2014-9390
Improper Input Validation in Git before 1
Executive Summary
CVE-2014-9390 is a critical severity vulnerability affecting appsec. It is classified as CWE-20. Ensure your systems and dependencies are patched immediately to mitigate exposure risks.
Precogs AI Insight
"Git contains a vulnerability allowing remote code execution on the client side. Attackers host a malicious Git repository containing a crafted `.git/config` file (exploiting case insensitivity on Windows/Mac file systems); when a victim clones it, their local Git configuration is overwritten to execute arbitrary commands. Precogs Application Security Module tracks file-system traversal sinks."
What is this vulnerability?
CVE-2014-9390 is categorized as a critical Improper Input Validation flaw with a CVSS base score of 9.8. Based on our vulnerability intelligence, this issue occurs when the application fails to securely handle untrusted data boundaries.
Git before 1.8.5.6, 1.9.x before 1.9.5, 2.0.x before 2.0.5, 2.1.x before 2.1.4, and 2.2.x before 2.2.1 on Windows and OS X; Mercurial before 3.2.3 on Windows and OS X; Apple Xcode before 6.2 beta 3; mine all versions before 08-12-2014; libgit2 all versions up to 0.21.2; Egit all versions before 08-12-2014; and JGit all versions before 08-12-2014 allow remote Git servers to execute arbitrary commands via a tree containing a crafted .git/config file with (1) an ignorable Unicode codepoint, (2) a git~1/config representation, or (3) mixed case that is improperly handled on a case-insensitive filesystem.
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 | 9.8 (CRITICAL) |
| Vector String | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H |
| Published | February 12, 2020 |
| Last Modified | November 21, 2024 |
| Related CWEs | CWE-20 |
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-2014-9390
- 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
Git contains a vulnerability allowing remote code execution on the client side. Attackers host a malicious Git repository containing a crafted .git/config file (exploiting case insensitivity on Windows/Mac file systems); when a victim clones it, their local Git configuration is overwritten to execute arbitrary commands. Precogs Application Security Module tracks file-system traversal sinks.
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 User Input |
| Vector | Input flows through the application logic without sanitization |
| Sink | Execution or Rendering Sink |
| Impact | Application compromise, Logic Bypass, Data Exfiltration |
Vulnerable Code Pattern
# ❌ VULNERABLE: Unsanitized Input Flow
def process_request(request):
user_input = request.GET.get('data')
# Taint sink: processing untrusted data
execute_logic(user_input)
return {"status": "success"}
Secure Code Pattern
# ✅ SECURE: Input Validation & Sanitization
def process_request(request):
user_input = request.GET.get('data')
# Sanitized boundary check
if not is_valid_format(user_input):
raise ValueError("Invalid input format")
sanitized_data = sanitize(user_input)
execute_logic(sanitized_data)
return {"status": "success"}
How Precogs Detects This
Precogs AI Analysis Engine maps untrusted input directly to execution sinks to catch complex application security vulnerabilities.\n