Protect your AI applications and agents from attacks, fakes, unauthorized access, and malicious data inputs.
Control your GenAI applications and agents and assure their alignment with their business purpose.
Proactively test GenAI models, agents, and applications before attackers or users do
The only real-time multi-language multimodality technology to ensure your brand safety and alignment with your GenAI applications.
Ensure your app is compliant with changing regulations around the world across industries.
Proactively identify vulnerabilities through red teaming to produce safe, secure, and reliable models.
Detect and prevent malicious prompts, misuse, and data leaks to ensure your conversational AI remains safe, compliant, and trustworthy.
Protect critical AI-powered applications from adversarial attacks, unauthorized access, and model exploitation across environments.
Provide enterprise-wide AI security and governance, enabling teams to innovate safely while meeting internal risk standards.
Safeguard user-facing AI products by blocking harmful content, preserving brand reputation, and maintaining policy compliance.
Secure autonomous agents against malicious instructions, data exfiltration, and regulatory violations across industries.
Ensure hosted AI services are protected from emerging threats, maintaining secure, reliable, and trusted deployments.
Executive Summary Prompt injection attacks undermine the reliability of generative AI systems by manipulating model behavior, bypassing safeguards, and exposing sensitive information. The ActiveFence AI Security Benchmark Report (2025) evaluates six leading detection models across over 28,000 adversarial and benign prompts. The findings highlight how enterprises can minimize operational risks from false positives while ensuring harmful prompts are effectively blocked. Key takeaways:
Prompt injection attacks undermine the reliability of generative AI systems by manipulating model behavior, bypassing safeguards, and exposing sensitive information. The ActiveFence AI Security Benchmark Report (2025) evaluates six leading detection models across over 28,000 adversarial and benign prompts. The findings highlight how enterprises can minimize operational risks from false positives while ensuring harmful prompts are effectively blocked. Key takeaways:
Prompt injection is one of the most urgent security concerns for enterprises deploying GenAI-powered applications. Attackers can insert adversarial instructions into inputs that cause a model to ignore safety guardrails, reveal sensitive data, or generate harmful content. These vulnerabilities create financial, reputational, and regulatory risks for organizations.
The 2025 ActiveFence AI Security Benchmark Report provides an in-depth comparison of six security detection models, including commercial APIs and open-source systems. By testing across benign prompts, adversarial injections, and multilingual datasets, the benchmark highlights how different models handle real-world attack strategies and operational trade-offs.
Prompt injections are adversarial inputs that manipulate AI models into producing unsafe or unintended outputs. Common techniques include:
These attacks can lead to content moderation failures, exposure of sensitive data, and compliance violations.
ActiveFence tested more than 28,000 prompts across categories defined by OWASP and MITRE ATLAS. The dataset included:
Testing covered 13 languages, including English, Chinese, French, German, Hebrew, Japanese, Korean, Portuguese, Russian, and Spanish.
The benchmark compared six models: ActiveFence, Deepset, Llama Prompt Guard 2, ProtectAI, Bedrock, and Azure.
Comparative Performance
Source: ActiveFence AI Security Benchmark Report, Prompt Injections, 2025.
ActiveFence delivered the best balance of precision and recall, with significantly fewer false positives than open-source alternatives.
Security models must detect adversarial behavior in multiple languages. The benchmark found:
Source: ActiveFence AI Security Benchmark Report, Prompt Injections, 2025
Enterprises integrating GenAI for customer service, content generation, or automation face high exposure to prompt injection risks. Models with high false positive rates increase operational costs and frustrate users, while low precision risks letting harmful prompts through.
ActiveFence Guardrails combines precision, multilingual support, and resilience against jailbreaks, making it suitable for enterprise-scale safety stacks.
The 2025 benchmark shows the ActiveFence AI Safety and Security model as the most reliable choice for enterprises launching global AI applications and requiring low false positives, high detection accuracy, and multilingual resilience.
Get a full breakdown of the tests.
ActiveFence provides cutting-edge AI Content Safety solutions, specifically designed for LLM-powered applications. By integrating with NVIDIA NeMo Guardrails, we’re making AI safety more accessible to businesses of all sizes.
ActiveFence is expanding its partnership with NVIDIA to bring real-time safety to a new generation of AI agents built with NVIDIA’s Enterprise AI Factory and NIM. Together, we now secure not just prompts and outputs, but full agentic workflows across enterprise environments.
Learn how ActiveFence red teaming supports Amazon as they launch their newest Nova models.