AI tool comparison
QSAG-Core vs qsag-core
Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.
Security
QSAG-Core
Open-source security scanner purpose-built for AI agent systems and MCP deployments
75%
Panel ship
—
Community
Paid
Entry
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.
Security
qsag-core
Open-source security scanner for AI agents — catches MCP poisoning and prompt injection
50%
Panel ship
—
Community
Free
Entry
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.
Reviewer scorecard
“I've been manually reviewing MCP tool schemas before deploying them — QSAG-Core automates that. 26 MCP poisoning patterns and 28 prompt injection patterns in a single pip install is a no-brainer to add to any agent pipeline's security layer.”
“I've been looking for exactly this since MCP started proliferating. Pattern-based detection over ML is the right call for security tooling — I can audit what it's flagging and why. Dropping this into my agent pipeline CI was a 30-minute job. The MCP tool poisoning scanner alone is worth it.”
“Pattern matching is a starting point, not a solution. Sophisticated prompt injection and MCP poisoning attacks are designed specifically to evade signature-based detection. QSAG-Core will catch known-bad patterns, but a determined attacker will trivially bypass it. This is necessary but not sufficient security.”
“Zero stars, no known production deployments, no security audit of the security tool itself — that's an uncomfortable situation. Pattern-based detection will generate false positives as MCP tool definitions grow more complex, and attackers who know about this scanner can trivially evade it. Treat as research, not production security.”
“Every major software ecosystem eventually got linters, scanners, and static analysis tools. QSAG-Core is the beginning of that toolchain for AI agents. The OWASP Agentic AI threat model it implements will become the industry baseline. Early adopters of agent-specific security tooling will be ahead of the curve when regulations arrive.”
“MCP security is going to matter enormously as AI agents gain real-world tool access. The OWASP Top 10 for Agentic Applications is brand new and most teams haven't even read it. Getting familiar with these attack patterns now, before an incident forces the conversation, is table-stakes security hygiene.”
“Non-technical teams building AI-powered tools with MCP have no idea what tool poisoning even is. QSAG-Core gives developers a way to add a meaningful security layer that they can explain to stakeholders without a security engineering background.”
“Unless you're running AI agents in production that use MCP tools, this is highly specialized developer/security tooling. Relevant context for understanding AI agent risks, but not something most creatives will interact with directly.”
Weekly AI Tool Verdicts
Get the next comparison in your inbox
New AI tools ship daily. We compare them before you waste an afternoon.