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May 2025 • Model Security & Safety Evaluation
Want to see how Gemini 2.5 Flash stacks up against other models? Use our comparison tool to analyze security metrics side by side.
Google's Gemini 2.5 Flash launched on April 17, 2025, marking a significant advancement in hybrid reasoning capabilities while maintaining the speed and cost efficiency of its predecessor. Available through the Gemini API via Google AI Studio and Vertex AI, this model is currently in preview mode.
As the model enters the preview phase, this analysis aims to evaluate its security features and identify areas for potential improvement, ensuring robust protection as enterprise adoption grows.
"Building upon the popular foundation of 2.0 Flash, this new version delivers a major upgrade in reasoning capabilities, while still prioritizing speed and cost. Gemini 2.5 Flash is our first fully hybrid reasoning model, giving developers the ability to turn thinking on or off."— Google
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24,576 tokens input • 24,576 tokens output
hybrid reasoning
• complex task analysis • math problem solving • research question analysis
• Gemini API via Google AI Studio • Vertex AI
January 2025
Comprehensive analysis across 39 test categories, sorted by severity and pass rate:
Our security testing suite demonstrates varying levels of compliance across different categories. The Gemini 2.5 Flash model's overall pass rate distribution shows 3 critical, 5 high, 15 medium, and 16 low severity findings.
Top performing areas include Unauthorized Commitments (82.22%), Divergent Repetition (77.78%), Excessive Agency (75.56%). These categories show satisfactory security practices.
Areas requiring attention include Disinformation Campaigns (20%), Graphic Content (35.56%), Dangerous Activity Content (37.78%). These categories present opportunities for improvement in security measures.
Tests for unauthorized contractual commitments and legal exposure
Tests for training data leaks through repetitive pattern exploitation that causes model divergence
Tests for fabrication of false or misleading information
Our evaluation included over 1,600 test probes across four security categories. The analysis revealed both strengths and areas requiring additional safety measures:
Protection against unauthorized access, data exposure, and system vulnerabilities
Assessment of compliance with legal requirements and prevention of illegal content
Prevention of harmful content and protection of user safety
Protection 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 Gemini 2.5 Flash model's evaluation against these frameworks reveals several areas requiring attention across 7 identified findings. While Gemini 2.5 Flash has no critical vulnerabilities, high-severity issues should be prioritized for improvement.
High-severity concerns include LLM02: Sensitive Information Disclosure.
MITRE ATLAS identified Prompt Injections and Jailbreak as high-severity concerns.
39
54.3%
3
Tests handling of false information campaigns
Tests handling of graphic or violent content
Tests handling of dangerous activity instructions
Tests handling of methamphetamine-related content
Tests handling of Pliny prompt injections
Tests for unauthorized contractual commitments and legal exposure
Tests for training data leaks through repetitive pattern exploitation that causes model divergence
Tests for unauthorized actions beyond defined system boundaries
Tests handling of hate speech and discriminatory content
Tests handling of political content and bias