DeepTeam vs PromptRedTeam

DeepTeam is an open-source Python framework for red teaming large language model systems. It offers more than 50 ready-to-use vulnerability checks covering bias, toxicity, personal-information leakage, prompt leakage, and security risks. Simulated attacks include jailbreaks, prompt injection, automated evasion, data extraction, and response manipulation. Vulnerability-specific LLM-as-a-Judge metrics return a binary score with reasoning. Supported reference frameworks include OWASP, NIST AI RMF, MITRE ATLAS, the EU AI Act, BeaverTails, and Aegis. Listed model providers include OpenAI, Claude, Gemini, Azure OpenAI, AWS Bedrock, Vertex AI, Mistral, LiteLLM, and Portkey. CI/CD listings include GitHub Actions, GitLab CI, Jenkins, CircleCI, Buildkite, and Azure Pipelines. Installation uses pip in a Python virtual environment, and attacks are dynamically simulated without a prepared dataset. Results can be saved locally or sent to Confident AI for centralized viewing and production red teaming through a UI. The framework is Apache 2.0 licensed and supports self-hosted or API use.

PromptRedTeam is an open-source tool that scans user input before it reaches a large language model. It detects direct injection, role manipulation, zero-width injection, delimiter injection, and encoded payloads. Direct-injection checks examine override keywords, conflicting instructions, and prompt structure. Role checks cover known jailbreak patterns, role-play scenarios, and bypass attempts. The tool detects hidden zero-width characters, normalizes Unicode, analyzes Base64 and other encodings, and can decode suspicious text before scanning again. Delimiter checks look for context-breaking markers, Markdown abuse, and structural manipulation. Applications can call the hosted API with a POST request to https://api.promptredteam.com/test, or run PromptRedTeam through self-hosted deployment. The live tester accepts up to 1,000 characters and allows 10 requests per minute; self-hosting provides unlimited usage. Python, JavaScript, and cURL examples are provided. The suggested workflow is to scan incoming text, then block detected threats or log them for review. PromptRedTeam is available through web, API, and self-hosted platforms, with automated detection and hybrid deployment. It is released under the MIT License.