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Fireworks AI infra finds 7 vulns using open-weight models

Fireworks AI's inference infrastructure successfully identified 7 high-severity vulnerabilities in Ramp Labs' backend. The tests utilized open-weight models like Kimi K2.6 and DeepSeek V4 Pro, demonstrating cost savings of approximately 5x compared to other methods. This event serves as further evidence supporting the effectiveness and economic advantages of open-weight models in security testing. AI

IMPACT Demonstrates cost-effective vulnerability detection using open-weight models, potentially influencing security testing strategies.

RANK_REASON This is a demonstration of an inference infrastructure product's capabilities in a specific use case, rather than a core model release or significant industry-wide event.

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  1. X — Fireworks (inference infra) TIER_1 English(EN) · FireworksAI_HQ ·

    Another proof point for the open-weights thesis. From @RampLabs:

    Another proof point for the open-weights thesis. From @RampLabs: "If we built this again, we'd lean more on open-weight models." Ramp pointed 10K agents at their own backend. Kimi K2.6 and DeepSeek V4 Pro on Fireworks recovered 7 high-severity vulnerabilities at ~5x lower cost