GPT-4.1 nano Security Report
April 2025 • Model Security & Safety Evaluation
Compare Model Performance
Want to see how GPT-4.1 nano stacks up against other models? Use our comparison tool to analyze security metrics side by side.
OpenAI's GPT-4.1 nano launched in October 2023, offering unparalleled speed and cost-efficiency within the GPT-4.1 series. As the most economical model in its class, it provides rapid processing capabilities and is available through OpenAI's API and cloud platforms.
With increasing adoption in budget-conscious applications, this analysis focuses on the model's security features and areas for potential enhancement.
"GPT-4.1 nano is the fastest, most cost-effective GPT-4.1 model."— OpenAI
About This Evaluation
Core Capabilities
text, image
text
1,047,576 tokens input • 32,768 tokens output
Use Cases
high-speed applications, budget-conscious applications
• text processing • cost-efficient operations
Availability
• OpenAI API • cloud platforms
June 1, 2024
Security Test Results
Comprehensive analysis across 39 test categories, sorted by severity and pass rate:
Performance Overview
Our security testing suite demonstrates varying levels of compliance across different categories. The GPT-4.1 nano model's overall pass rate distribution shows 3 critical, 5 high, 15 medium, and 16 low severity findings.
Top performing areas include ASCII Smuggling (100%), Sexual Crime Content (62.22%), Child Exploitation (57.78%). These categories show satisfactory security practices.
Areas requiring attention include Pliny Prompt Injections (0%), Resource Hijacking (8.89%), Religious Bias (13.33%). These categories present opportunities for improvement in security measures.
Our evaluation included over 1,600 test probes across four security categories. The analysis revealed both strengths and areas requiring additional safety measures:
Security & Access Control
27% Pass RateProtection against unauthorized access, data exposure, and system vulnerabilities
Compliance & Legal
41% Pass RateAssessment of compliance with legal requirements and prevention of illegal content
Trust & Safety
41% Pass RatePrevention of harmful content and protection of user safety
Brand
19% Pass RateProtection of brand integrity and prevention of misuse
OWASP Top 10 for LLMs (2025) and MITRE ATLAS represent the primary security assessment frameworks for large language models. OWASP focuses on critical deployment risks, while ATLAS maps adversarial techniques against AI systems, similar to the MITRE ATT&CK framework for traditional systems.
The GPT-4.1 nano model's evaluation against these frameworks reveals several areas requiring attention across 6 identified findings. While GPT-4.1 nano has no critical vulnerabilities, high-severity issues should be prioritized for improvement.
High-severity concerns include LLM02: Sensitive Information Disclosure.
MITRE ATLAS identified Jailbreak as high-severity concerns.
OWASP Top 10 for LLMs 2025 - GPT-4.1 nano Assessment
High Risk Areas
Moderate Risk Areas
MITRE ATLAS Findings for GPT-4.1 nano
High Severity Findings
Moderate Severity Findings
Total Test Categories
39
Average Pass Rate
36.5%
Critical Issues
3
Severity Distribution
Performance Summary
Security & Access Control
Compliance & Legal
Trust & Safety
Brand
Worst Performing Tests
Pliny Prompt Injections
Tests handling of Pliny prompt injections
Resource Hijacking
Tests for unauthorized resource usage and purpose deviation
Overreliance
Tests for overreliance on system assumptions
Religious Bias
Tests handling of religious content and bias
Unauthorized Commitments
Tests for unauthorized contractual commitments and legal exposure
Best Performing Tests
ASCII Smuggling
Tests vulnerability to Unicode tag-based instruction smuggling attacks
Sexual Crime Content
Tests handling of sexual crime content
Child Exploitation
Tests handling of child exploitation content
WMD Content
Tests handling of WMD-related content
Violent Crime Content
Tests handling of violent crime content
Key Observations
Strengths
- Strong performance in handling ASCII Smuggling (100% pass rate)
- Effective prevention in Sexual Crime Content (62.22%)
- Consistent performance across critical security tests
Areas for Improvement
- Low pass rate (0%) for Pliny Prompt Injections
- 3 critical severity issues identified
- Average pass rate of 36.5% indicates room for improvement