SecGPT is an open-source security framework designed to protect large language model applications. It provides pre-built modules and customizable rule definitions to detect prompt injections, simulate adversarial attacks, enforce compliance policies, and validate outputs within your LLM pipelines.
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SecGPT
SecGPT is an open-source security framework designed to protect large language model applications. It provides pre-built modules and customizable rule definitions to detect prompt injections, simulate adversarial attacks, enforce compliance policies, and validate outputs within your LLM pipelines.
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What is SecGPT?
SecGPT wraps LLM calls with layered security controls and automated testing. Developers define security profiles in YAML, integrate the library into their Python pipelines, and leverage modules for prompt injection detection, data leakage prevention, adversarial threat simulation, and compliance monitoring. SecGPT generates detailed reports on violations, supports alerting via webhooks, and seamlessly integrates with popular tools like LangChain and LlamaIndex to ensure safe and compliant AI deployments.
Who will use SecGPT?
- AI developers
- Security engineers
- DevSecOps teams
- Compliance officers
- Research labs
How to use the SecGPT?
- Step1: Install SecGPT with pip install secgpt
- Step2: Define your security profile in a YAML file with rules and policies
- Step3: Import SecGPT and initialize the SecGPT client in your Python code
- Step4: Attach SecGPT middleware to your LLM pipeline (e.g., LangChain)
- Step5: Configure desired modules (injection detection, adversarial simulation, compliance checks)
- Step6: Run your application and review generated security reports for any violations
Platform
- Linux
- Mac
- Windows
SecGPT's Core Features & Benefits
The Core Features
- Prompt injection detection
- Adversarial attack simulation
- Data leakage prevention
- Compliance policy enforcement
- Output validation and filtering
- Detailed security reporting
- Integration with LangChain and LlamaIndex
The Benefits
- Automated vulnerability assessments
- Customizable security rules
- Seamless integration into existing pipelines
- Improved compliance and governance
- Reduced risk of malicious inputs
SecGPT's Main Use Cases & Applications
- Securing customer support chatbots against prompt injections
- Auditing LLM-powered document summarization for data leaks
- Compliance testing for regulated AI deployments
- Threat modeling and adversarial testing of generative agents
- Automated security reporting for LLM applications
FAQs of SecGPT
SecGPT Company Information
- LLM Platform Security
SecGPT Reviews
5/5
SecGPT's Main Competitors and alternatives?
Cocoon Guardrails
PromptGuard
OpenAI Moderation API
AI Security Engine
LangSecOps
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