AI-SPM vs QSAG-Core

AI-SPM (AI Security Posture Management) is an open-source infrastructure layer for securing LLM pipelines running in production. It targets three attack surfaces that traditional application security doesn't cover: prompt injection (including obfuscated and multi-step variants), tool abuse via unvalidated structured outputs, and data exfiltration through PII leakage in model responses. The architecture layers a gateway intercept layer over incoming prompts, runs context inspection before the LLM sees any input, enforces policies via Open Policy Agent (OPA) for declarative, auditable rules, then pipes all events through Apache Kafka and Apache Flink for real-time streaming analysis. This means security posture can be monitored and enforced at scale without blocking the inference path. The project is genuinely fresh — posted as a Show HN today. Early community feedback pointed to capability-based token models (similar to OS kernel permission rings) as a complementary approach to content-scanning, which the author acknowledged as a meaningful gap. The timing is right: as companies push AI agents from demos to production, the security tooling layer is largely underdeveloped. AI-SPM is one of the first OSS projects to tackle it at the infrastructure layer rather than with prompt-level guardrails alone.

QSAG-Core is a Python security scanner specifically designed for the OWASP Top 10 for Agentic Applications 2026 threat model. It provides three core detection capabilities: MCP tool poisoning (26 malicious patterns across 7 categories), prompt injection (28+ attack patterns including goal hijacking, jailbreak attempts, and memory poisoning), and ghost agent detection for unauthorized API key usage. It runs as pure pattern matching — no ML, no cloud dependency — and can be integrated as a pre-execution guard in any Python-based agent pipeline. Released April 10, 2026 by the Neoxyber team, QSAG-Core fills a real operational gap as MCP-based agent deployments proliferate. While Microsoft's Agent Governance Toolkit addresses similar territory, it's heavyweight and enterprise-focused. QSAG-Core is a pip install and a few lines of code — the security-focused indie alternative that fits into a CI/CD pipeline or an existing agent framework without an enterprise contract. The threat model it addresses is timely. As MCP becomes the de facto standard for tool-calling in AI agents, malicious MCP servers and prompt injection via tool outputs are becoming documented attack vectors. Having a lightweight, open-source scanner that specifically targets these patterns is exactly what the community has been building toward. MIT licensed, 24 commits in its first day.