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Agent Breaker
Break, test, and secure AI agents before production
Agent Breaker is a chaos engineering and security testing framework for AI agents. 2000+Pypi Installs: https://pypi.org/project/agent-breaker Test LangGraph applications against prompt injection, tool misuse, and other adversarial scenarios before deployment. Features: • Automated adversarial testing • Failure detection and reporting • LangGraph integration • Security-focused evaluation • ML Based Judge for evaluation Build safer, more reliable AI agents by breaking them before your users do
While building and studying AI agents, I noticed that most developers focus on making agents work, but spend far less time testing how they fail.
Traditional software has unit tests, integration tests, load tests, and chaos engineering. AI agents often have none of these protections despite having access to tools, memory, and external systems.
I built Agent Breaker to help developers automatically stress-test LangGraph applications using adversarial attacks and failure scenarios. The goal is simple: find vulnerabilities, unsafe behaviors, and reliability issues before users do.
This is an open-source project, and I'd love feedback from anyone building AI agents, agent frameworks, or evaluation systems.
What are the biggest failures you've encountered while building AI agents?
About Agent Breaker on Product Hunt
“Break, test, and secure AI agents before production”
Agent Breaker was submitted on Product Hunt and earned 7 upvotes and 2 comments, placing #78 on the daily leaderboard. Agent Breaker is a chaos engineering and security testing framework for AI agents. 2000+Pypi Installs: https://pypi.org/project/agent-breaker Test LangGraph applications against prompt injection, tool misuse, and other adversarial scenarios before deployment. Features: • Automated adversarial testing • Failure detection and reporting • LangGraph integration • Security-focused evaluation • ML Based Judge for evaluation Build safer, more reliable AI agents by breaking them before your users do
On the analytics side, Agent Breaker competes within Developer Tools, Artificial Intelligence and Development — topics that collectively have 994.5k followers on Product Hunt. The dashboard above tracks how Agent Breaker performed against the three products that launched closest to it on the same day.
Who hunted Agent Breaker?
Agent Breaker was hunted by Gokul Polavarapu. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Agent Breaker including community comment highlights and product details, visit the product overview.
Gokul Polavarapu
Hey Product Hunt! 👋
I'm Gokul, the creator of Agent Breaker.
While building and studying AI agents, I noticed that most developers focus on making agents work, but spend far less time testing how they fail.
Traditional software has unit tests, integration tests, load tests, and chaos engineering. AI agents often have none of these protections despite having access to tools, memory, and external systems.
I built Agent Breaker to help developers automatically stress-test LangGraph applications using adversarial attacks and failure scenarios. The goal is simple: find vulnerabilities, unsafe behaviors, and reliability issues before users do.
This is an open-source project, and I'd love feedback from anyone building AI agents, agent frameworks, or evaluation systems.
What are the biggest failures you've encountered while building AI agents?