atlas-detect vs qsag-core

atlas-detect is an open-source Rust tool that maps MITRE ATLAS techniques to real-time detection rules for LLM systems and AI agents. MITRE ATLAS is the adversarial threat landscape framework for AI — think ATT&CK but for machine learning systems — and atlas-detect is the first practical, deployable detection engine built on top of it. It ships with 97 pre-built detection rules covering 16 adversarial tactics, from prompt injection and model inversion to training data poisoning. The engine is written in Rust and designed for single-pass regex scanning, making it fast enough for inline deployment in API gateways or agent middleware. You feed it prompt-response pairs (or full conversation logs) and it returns matched technique IDs, severity ratings, and structured evidence. Think of it as a Snort/Suricata ruleset, but for the semantic attack surface of LLMs. With only 4 stars as of today, atlas-detect is an extremely early project — but it's filling a gap that no major security vendor has meaningfully addressed. As enterprises deploy AI agents with real tool access and real consequences, ATLAS-aligned detection will become a compliance requirement. This is the seed of that tooling.

qsag-core is a fresh open-source Python toolkit from Neoxyber that addresses the OWASP Top 10 for Agentic Applications 2026 — specifically the two fastest-growing attack vectors: MCP tool poisoning and prompt injection in AI agents. The library uses pattern-based detection (not ML-based, to minimize false positives) to scan 26 MCP tool poisoning patterns across 7 categories and detect 28+ prompt injection patterns across 9 threat categories. It also catches ghost agent attempts, credential harvesting, and memory poisoning in real time. The toolkit is available on PyPI, ships with cryptographic attestations, and is licensed under Apache 2.0. It was created in early April 2026, making it genuinely new-to-the-scene. The timing is significant: a recent Dark Reading poll found 48% of cybersecurity professionals now identify agentic AI as the #1 attack vector, up from a niche concern in 2025. Microsoft released a similar (but much larger-scope) Agent Governance Toolkit in early April, which validates the problem space but leaves room for nimble open-source tooling. qsag-core is early-stage — zero stars on GitHub as of today, minimal community traction, and no documented production deployments. But it addresses a problem that's going to become critical as MCP adoption accelerates. First-mover advantage in a niche that's about to explode.