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Developer releases AI Guard Gateway v0.1.0 to block prompt injection and endpoint hijacking

A developer known as MagoPredator has released AI Guard Gateway v0.1.0, an open-source reverse proxy designed to secure AI inference APIs such as Ollama and LiteLLM against unauthorized access and abuse. The tool was built in response to documented vulnerabilities involving exposed AI endpoints that can be exploited without any traditional exploit, simply by accessing unsecured APIs anonymously. AI Guard Gateway addresses key threat vectors including endpoint hijacking, prompt injection, resource exhaustion, and PII leakage through components such as mandatory API key or JWT authentication, sliding-window rate limiting, and automatic redaction of sensitive data. The project was developed using Spec-Driven Development and validated through pytest test coverage, a Bandit security scan returning zero high or medium severity findings, and continuous analysis via a SonarCloud CI/CD pipeline. The gateway is available on GitHub under the AGPL-3.0 license and is intended to be deployed in front of any language model serving infrastructure.

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ProgrammingDEV Community ·

How to Build Production-Grade Observability Using OpenTelemetry, Prometheus, and Grafana

Modern software engineering teams increasingly require full observability — not just uptime monitoring — to diagnose complex failures in distributed systems. A detailed technical guide published on DEV Community outlines how to implement production-ready observability using OpenTelemetry, Prometheus, and Grafana for Node.js microservices. The approach uses OpenTelemetry's vendor-neutral SDK to instrument a sample checkout endpoint, capturing both request throughput and latency distribution with high-cardinality attributes. Metrics are exported via a Prometheus exporter and can be visualized through Grafana dashboards, giving engineering teams direct insight into root causes during incidents. The guide also recommends pairing this observability stack with an automated CI/CD validation workflow to ensure instrumentation integrity across deployments.

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ProgrammingDEV Community ·

Java While vs Do-While Loops: Key Difference Every Developer Should Know

Java's while and do-while loops both repeat a block of code based on a condition, but differ in when that condition is evaluated. A while loop checks its condition before executing, meaning the code block may never run if the condition is false from the start. A do-while loop runs the code block first and checks the condition afterward, guaranteeing at least one execution regardless of the condition's initial value. For example, with a ticketCount set to zero, a while loop prints nothing, while a do-while loop prints the message once before stopping. Developers should choose while loops for pre-condition checks and do-while loops when the code must execute at least once.

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ProgrammingDEV Community ·

Solon 4.0.3 Adds AI Loop Module and Standalone Code Talent Plugin

The Solon team released version 4.0.3 of the Java framework on July 2, 2026, marking the third general availability release in under four weeks. The update introduces solon-ai-loop, a controlled iterative execution module that allows AI agents to repeat reasoning steps — such as writing, testing, and fixing code — until a defined termination condition is met. A previously bundled code-talent plugin has been extracted into its own lightweight dependency, solon-ai-talent-code, making it reusable outside the full Harness environment. The release also adds ScopeLocalJdk25, which automatically enables JDK 25 scoped-value support when the framework detects that runtime, requiring no configuration changes from developers. Version 4.0.x carries LTS status with open-source support through December 2026 and commercial support through June 2029.

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