Introducing Woodpecker: Open-Source Red Teaming for AI, APIs, and Kubernetes

We're thrilled to announce the launch of Woodpecker, Operant's open-source red teaming project! At Operant, we believe red teaming should not be a privilege for a few since security threats don't discriminate based on an organization's size or resources, but it should be a foundational practice for all. That’s why we’re open-sourcing Woodpecker, an automated red teaming project designed to democratize security testing for organizations of all sizes.

Especially in the age of AI, there are many closed-sourced alternatives adding confusion and complexity, while security and engineering teams need to feel more in control not only of their LLMs, but of the entire cloud application stack in which they are operating, including APIs and Kubernetes. That's why Woodpecker doesn't just address top threats for LLMs, it addresses top threats for APIs and K8s too, so that teams can have a comprehensive and actionable understanding of their AI and cloud stacks.

In today's rapidly evolving tech stacks, securing your Kubernetes clusters, APIs, and AI systems is more critical than ever. Modern applications have changed. They’re built with APIs, deployed on Kubernetes, and increasingly powered by LLMs and autonomous agents. Threats such as prompt injection, data poisoning, and model leakage continue to rise, and organizations need a comprehensive red teaming tool to keep up with these security threats. Traditionally, comprehensive red teaming has been available only to large enterprises with dedicated security teams and substantial budgets and resources, largely limited to once in a while activity. Increasingly, resource-constrained teams often don't have an ongoing program to keep up with the velocity of changes going on in their products, leaving them open to new threats and attacks.

Enter Woodpecker: Automated Red Teaming for All

Woodpecker [GitHub: https://github.com/OperantAI/woodpecker] is designed to bring the power of automated red teaming to your fingertips. It is built to simulate real-world threats against your critical systems, kind of like pecking holes in your security posture incessantly. As anyone who has encountered a woodpecker knocking on their house can attest, it is only a matter of time until they find a weak spot to drill. Woodpecker red teaming can therefore help you uncover security weaknesses before malicious actors do, across AI, Agents, APIs, and Kubernetes.

What can Woodpecker do for you?

Woodpecker provides automated red teaming capabilities across three critical domains:

1. Kubernetes Security: Identifies misconfigurations, privilege escalations, and vulnerable deployment patterns within container orchestration environments.
2. API Security: Simulate various attack scenarios to uncover vulnerabilities in API endpoints, authentication mechanisms, and data handling processes.
3. AI Security: Tests machine learning models and AI systems for prompt injection, data poisoning, and other emerging AI-specific attack vectors.

Key features of Woodpecker include:

• Red Teaming Across Kubernetes, APIs, and AI Workflows
  
  • Provides flexible and extensible red teaming frameworks for K8s, APIs, and AI models/agents.
  • Enables multi-layer threat simulation across runtime, APIs, and LLM integrations.
• Automated LLM Red Teaming
  
  • Covers prompt injection, jailbreaks, model theft, sensitive data leakage, and more.
  • Detects vulnerabilities by testing malicious prompts originating from both adversarial and typical users.
  • Tests for output manipulation and AI guardrails.
• Compliance Mapping for Regulatory Frameworks
  
  • Covers across threat vectors for OWASP top 10 for K8s, API, and AI, MITRE ATLAS, and NIST.
• Open-Source and Free
  
  • Delivers the benefit of a powerful red teaming tool without licensing fees, fostering widespread adoption.
• Easy Integration
  
  • Integrates seamlessly into existing security workflows and CI/CD pipelines, allowing continuous testing at the pace of AI development.

Simulating Real Attacks, Safely

• Manipulate LLMs to disclose sensitive data.
• Exploiting API over-permissions
• Breaking agent boundaries via MCPs.
• Move laterally in cloud-native environments via compromised pods or tokens
• Test live, pre-prod, and staging continuously with its automated, scalable design.

Whether you’re an AI engineer, platform engineer, or security leader, Woodpecker gives you the adversarial testing muscle you need. It allows you to simulate adversarial and regular user inputs to identify threats across various threat scenarios. By testing a wide range of malicious prompts and user behaviors, you can gain a deep understanding of your system's weaknesses and strengthen its defenses.

Why Open Source?

We've chosen to release Woodpecker as an open-source product because we believe security should be a shared responsibility. And the only way we move faster than attackers is by enabling everyone to test and improve security continuously. Our aim is to:

• Make advanced security testing accessible to everyone, regardless of organization size or budget
• Harness the collective expertise of the security community to improve the tool
• Provide transparency in how security testing is conducted
• Create a common foundation for security testing that can evolve with emerging threats

We believe this tool will be a valuable asset for security teams, developers, and anyone striving to build more secure and resilient systems.

Security for All

By embracing open source and community collaboration, we're working toward a future where robust security is the norm, not the exception. We invite you to join us on this journey. Let’s make red teaming a default, not a privilege. Join the Woodpecker Flight: https://github.com/OperantAI/woodpecker