DEVOPSdigest

Operant AI announced Woodpecker, an open-source, automated red teaming engine, that will make advanced security testing accessible to organizations of all sizes.

Woodpecker is designed to help organizations proactively detect and address security vulnerabilities across AI systems, Kubernetes environments, and APIs.

With the launch of Woodpecker, Operant is democratizing advanced security testing, making it accessible to every organization, regardless of their size or expertise. Woodpecker already simulates >50% of OWASP top 10 threats across APIs, Kubernetes, and LLMs, exceeding the threat simulation scope of leading commercial red teaming products. Woodpecker enables security teams, developers, and DevOps professionals to proactively identify vulnerabilities and build more resilient applications, without the cost and complexity of traditional solutions.

“Security vulnerabilities don't discriminate based on an organization's size or resources, we believe red teaming should not be a privilege for a few, it should be a foundational practice for all,” said Vrajesh Bhavsar, CEO and co-founder of Operant AI. "With Woodpecker, we're leveling the playing field by providing enterprise-grade red teaming capabilities in an open-source solution that any organization can deploy. Security testing at this depth should be a universal right, not a privilege reserved for those with the largest security budgets."

Woodpecker is purpose-built to address modern threats targeting AI applications, cloud APIs, and Kubernetes environments and is designed to mimic how real attackers operate across multiple layers of infrastructure.

Woodpecker provides automated red teaming capabilities across three critical domains:

- Kubernetes Security: Identifies misconfigurations, privilege escalations, and vulnerable deployment patterns within container orchestration environments.

- API Security: Simulate various attack scenarios to uncover vulnerabilities in API endpoints, authentication mechanisms, and data handling processes.

- AI Security: Tests machine learning models and AI systems for prompt injection, data poisoning, and other emerging AI-specific attack vectors.

“As AI agents arrive, limiting red-teaming to testing just AI components is no longer enough,” asserted Dr. Priyanka Tembey, co-founder and CTO of Operant AI. “What is needed is testing across the runtime, API and AI layers as all of the attack paths within these more traditional domains of an organization's application stack have now suddenly opened to third party AI and the supply chain risks they bring. This makes Woodpecker the only open-source comprehensive red teaming solution for the AI agents age.”

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; and 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.

Operant's Woodpecker is now available as an open-source project.