Many high-stakes collective problems, e.g., climate mitigation and pandemic response, share a structure in which risk materializes unless a group threshold is met. This threshold is often uncertain, but uncertainty can be reduced at a cost. We study this information cost tradeoff in an evolutionary game theoretic model of social learning in the collective-risk dilemma, where individuals must cooperate to reach a possibly uncertain threshold to prevent collective loss. Individuals may pay a fixed cost to observe the threshold's true value and condition their cooperation on it. Across four threshold priors, we characterize risk levels at which cooperative equilibria emerge and show that low cost information increases group success. However, this effect is reversed at higher costs. We define a private \emph{value of information} and show that information is worth buying only when it is considerably cheaper than contributing. When purchased information is shared with the group, the cooperative tipping point shifts to lower risk levels. Despite bearing a private cost, above this tipping point buyers earn more in expectation than information free-riders. We then study these dynamics when information diffuses through a network, allowing nodes to relay it. Although fewer individuals pay for information, relaying increases group success, and noisy relaying does not reduce it. By contrast, false information does, especially when it originates at the hubs of heterogeneous networks, and large attacks can bring collective action close to collapse. Buyers act as a firewall against disinformation, confining it to source neighbourhoods, and once disinformation sources are removed, the population recovers. The value of costly information thus depends on its price, the level of risk, and how it is shared, and, in our setting, the effort of acquiring it also protects the population against disinformation.

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