Compare Avocado vs. open-appsec

Mitigate lateral movement and prevent data theft by utilizing Avocado's security and visibility solutions that are both agentless and tailored for applications. This innovative approach combines app-native security with runtime policies and pico-segmentation, ensuring both simplicity and robust security at scale. By establishing microscopic perimeters around application subprocesses, threats can be contained at their most minimal definable surfaces. Additionally, by integrating runtime controls directly into these subprocesses, Avocado enables self-learning threat detection and automated remediation, regardless of the programming language or system architecture in use. Furthermore, it automatically shields your data from east-west attacks, functioning without the need for manual intervention and achieving near-zero false positives. Traditional agent-based detection methods, which rely on signatures, memory analysis, and behavioral assessments, fall short when faced with extensive attack surfaces and the persistent nature of lateral threats. Unless there is a fundamental shift in how attacks are detected, zero-day vulnerabilities and misconfiguration issues will persist, posing ongoing risks to organizational security. Ultimately, adopting such an advanced security model is essential for staying ahead of evolving cyber threats.

open-appsec is an open-source initiative that builds on machine learning to provide pre-emptive web app & API threat protection against OWASP-Top-10 and zero-day attacks. It can be deployed as add-on to Kubernetes Ingress, NGINX, Envoy and API Gateways. The open-appsec engine learns how users normally interact with your web application. It then uses this information to automatically detect requests that fall outside of normal operations, and sends those requests for further analysis to decide whether the request is malicious or not. open-appsec uses two machine learning models: 1. A supervised model that was trained offline based on millions of requests, both malicious and benign. 2. An unsupervised model that is being built in real time in the protected environment. This model uses traffic patterns specific to the environment. open-oppsec simplifies maintenance as there is no threat signature upkeep and exception handling, like common in many WAF solutions.