StakeBench/SBC: Web agents driven by large language models (LLMs) are increasingly deployed in real-world environments, where they operate over untrusted web content and execute actions with direct consequences. This makes them vulnerable to prompt-injection attacks, in which seemingly benign...
Pillar = mean of 2 scaled values = 2.5.
Awaiting first reading — these signals apply to this agent and will be ingested on the next tier tick: SO questions (7d), Product Hunt upvotes, Docker Hub pulls, Crates.io downloads (90d), Tech-news mentions (30d)
Not applicable — this agent doesn't have the prerequisite (no GitHub repo, no HF mirror, etc.) for these signals to ever apply: HF downloads (30d), npm weekly installs, PyPI monthly installs
[](https://agenttape.com/agents/stakebench-sbc)
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