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August 2025 • Model Security & Safety Evaluation
Want to see how Claude Opus 4.1 stacks up against other models? Use our comparison tool to analyze security metrics side by side.
Anthropic's Claude Opus 4.1 launched on August 5, 2025, as the pinnacle of their AI model lineup, offering substantial advancements in agentic tasks, coding, and reasoning capabilities. Available through API, Amazon Bedrock, and Google Cloud's Vertex AI, this model sets a new standard for intelligence and capability.
As Claude Opus 4.1 gains traction in enterprise environments, this security analysis aims to evaluate its safety features and identify areas for enhancement.
"Claude Opus 4.1 represents the highest level of intelligence and capability in Anthropic's model lineup."— Anthropic
Multilingual, Vision
Text, Code
200K tokens input • 32,000 tokens output
Advanced coding, Complex reasoning
• Multi-file code refactoring • Debugging and error correction • In-depth research and data analysis • Agentic task execution • Multilingual applications • Image processing and analysis • Long-context document processing
• API Platform • Amazon Bedrock • Google Cloud's Vertex AI
March 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 Claude Opus 4.1 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%), Divergent Repetition (100%), PII via Direct Exposure (97.78%). These categories demonstrate exceptional security practices and robust implementation.
Areas requiring attention include Pliny Prompt Injections (20%), CyberSecEval Dataset (71.11%), Dangerous Activity Content (73.33%). 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 Claude Opus 4.1 model's evaluation against these frameworks reveals several areas requiring attention across 6 identified findings. While Claude Opus 4.1 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.
39
87.1%
3
Tests handling of Pliny prompt injections
Tests prompt injection attacks from Meta's CyberSecEval dataset
Tests for unauthorized impersonation of entities
Tests handling of graphic or violent content
Tests handling of dangerous activity instructions
Tests for training data leaks through repetitive pattern exploitation that causes model divergence
Tests vulnerability to Unicode tag-based instruction smuggling attacks
Tests for direct PII exposure vulnerabilities
Tests handling of unauthorized professional advice
Tests handling of harassment and bullying content