
Crucible — Agent Security
AI security agent that detects & stops threats in real time
Crucible — Agent Security launched on April 25, 2026.
What it does
Crucible — Open-source AI agent security framework. Stress-test AI agents against prompt injection, goal hijacking, and tool misuse before production.
Crucible — the open-source security framework that tests what AI agents do, not just what they say. 153 attack vectors across 11 modules, 8/10 OWASP Agentic risks covered, CI/CD-native. Free and Apache 2.0.
Crucible stress-tests AI agents against every known attack vector — prompt injection, goal hijacking, tool misuse — before your system reaches production. 83% of organizations are deploying AI agents in 2026. Only 29% feel ready to do it securely. The gap between deployment speed and security maturity is where breaches happen. Every AI agent exposes a new attack surface. OWASP published the Agentic Top 10 in December 2025 — the first formal taxonomy of autonomous AI risks. Crucible covers 8 of the 10, with the remaining two in active development. Crucible runs 90 attack payloads against your agent in under 60 seconds — 153 across all 11 modules. Automated, continuous, and integrated…from crucible-security.github.io
Does a similar job
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Gambit, an open-source agent harness for building reliable AI agentsJan 2026 · github.com · ▲91Hey HN! Wanted to show our open source agent harness called Gambit. If you’re not familiar, agent harnesses are sort of like an operating system for an agent... they handle tool calling, planning, context window management, and don’t require as much developer orchestration. Normally you might see an agent orchestration framework pipeline like: compute -> compute -> compute -> LLM -> compute -> compute -> LLM we invert this so with an agent harness, it’s more like: LLM -> LLM -> LLM -> compute -> LLM -> LLM -> compute -> LLM Essentially you describe each agent in either a self contained…
Crucible — AI Trading Strategy ResearchAug 2026 · crucible-trading.com · ▲2Find, test, and evaluate trading strategies with AI.
Open-source playground to red-team AI agents with exploits publishedMar 2026 · github.com · ▲30We build runtime security for AI agents. The playground started as an internal tool that we used to test our own guardrails. But we kept finding the same types of vulnerabilities because we think about attacks a certain way. At some point you need people who don't think like you. So we open-sourced it. Each challenge is a live agent with real tools and a published system prompt. Whenever a challenge is over, the full winning conversation transcript and guardrail logs get documented publicly. Building the general-purpose agent itself was probably the most fun part. Getting it to reliably use…

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