This paper introduces the Open-Audience Pseudo-Psychology Risk Model (OAPRM), a framework for analyzing the risks created when clinical, forensic, and therapeutic concepts are converted into viral public content. Mental-health content about narcissism, gaslighting, love bombing, coercive control, DARVO, red flags, and abuse detection is typically framed as victim education. This paper argues that such framing ignores the open-audience structure of algorithmic platforms. In public feeds, victims are not the only viewers. Confused observers, false accusers, reputation managers, manipulators, and abusive actors can all receive the same detection rules.The paper identifies detection-rule leakage as the central failure: when content teaches victims what to recognize, it can simultaneously teach adversarial viewers what to hide. This creates asymmetric benefit. Victims may gain language for harm, while harmful actors may gain operational knowledge about which behaviors trigger suspicion. The paper formalizes this process through the concepts of Trust Camouflage, Weak Disclosure, Resilient Disclosure, and MIPU/MAP formation. Trust Camouflage describes the use of therapeutic language, such as boundaries, healing, accountability, and emotional safety, to appear trustworthy while maintaining harmful control dynamics underneath.OAPRM proposes that viral pseudo-psychology content should be evaluated not only by accuracy, intent, or creator credentialing, but by audience composition, adversarial uptake, disclosure resilience, and downstream behavioral adaptation. The paper argues that public abuse-awareness content can unintentionally degrade its own detection value when the people being described learn the signs and adapt around them. It concludes by proposing resilient disclosure principles for mental-health education that can support victims without broadcasting evasion manuals to adversarial audiences.