How I advertise malicious software on Google Ads
summary
Google Ads' automated security systems can mistakenly flag legitimate software as malicious, leaving developers in a frustrating loop of unexplained suspensions and rejected appeals. This lack of transparency prevents developers from fixing the specific issues triggering the flags, making the process feel arbitrary. The author's experience shows that even when software is notarized and passes all security scans, it can still be banned without a clear reason. Ultimately, this highlights a systemic failure in how large platforms handle security appeals for independent developers.
key points
- The author's terminal multiplexer, RACE, was flagged for malicious software despite being signed, notarized, and passing multiple independent security audits.
- Google's appeal process is a 'Catch-22' where the developer is asked for more information but never told exactly what part of the site or app is considered compromised.
- Legitimate software functionality, such as managing background shell processes, can be misinterpreted by automated scanners as malicious behavior.
who should read it
Software developers and independent creators who use advertising platforms to promote their tools and may face automated moderation issues.
discussion skeptical
consensus
Commenters generally agree that Google Maps has become unreliable and frustrating, particularly regarding the submission of new location data and the handling of reviews. Many attribute this decline to a shift from engineer-led quality to profit-driven corporate management and an over-reliance on automated moderation. Consequently, several users advocate for switching to OpenStreetMap as a transparent, community-driven alternative.
top insight
The difficulty in maintaining data quality at Google's scale creates a fundamental tension where human review is impossible for every request, yet automated systems are easily gamed or overly restrictive. This suggests that the current centralized model of massive platforms is inherently incapable of sustaining high-quality, user-generated data without enabling systemic abuse or alienating legitimate contributors.
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