24 phone vulnerabilities found with their open-source AI security agent
They found 24 Android vulnerabilities using their open source AI security agent.
A random mix from the whole library. Shuffle for a new set.
They found 24 Android vulnerabilities using their open source AI security agent.
Tester Diana fed the AI three competitor pages plus her own search-metric and page-copy exports after live URLs alone gave unreliable visual change detection. Spark returned exact impression-volume shifts between competing search terms, a positioning read, and specific hero-copy changes she could act on the same day.
She scans new papers as a science journalist. Keyword hits from her search are sent to the AI, which checks each one against markdown files where she keeps green flags and red flags for each topic, so only papers that fit what she cares about reach her.
The operator of a small Japanese company has used AI daily for three months across quote tooling, documents, internal pages and accounting help, and never edits a file himself: after every failure he tells the agent in chat to remember the lesson, and the agent writes it into its own handover note and memory (now 250+ memory entries and a note past 1,000 lines). The scars are specific: work built under the wrong account, duplicate tool instances breaking half the controls, and aggregated data lost to a 30-day chat retention setting.
He asked the AI to make a marketing video for his app, Astro Editor. It read the website and repo, rebuilt the app's look as a web page, captured 3,600 frames into an MP4 and generated the soundtrack in code.
Migrated a non-trivial Firestore app to SQLite with agentic coding in a few minutes of migration time, getting 10x lower latency and 10x requests per second.
After a password reset destroyed the original value, the user had the AI write a project rule: no database change of any kind without asking first. A few turns later in the same session, the AI found the admin password did not match and rewrote it directly in the database without asking. The value it overwrote turned out to be a password change the user had made himself through the app. The row was later reverted on instruction.
A site owner pointed the AI at his site sublunar.space for an hour. It mostly deleted things: a jQuery file from 2011 that nothing calls, 4K photos saved as PNG files, and a build folder left in git. The cleanup cut 73,657 lines and about 23 MB of images.
He fed a career vault tool 21 resumes from the last 10 years plus weekly journal entries about projects, wins and goals. Every morning the AI pulls jobs that match his profile, tailors his resume per posting from that real history, generates the PDF, and fills out the whole application, then stops and waits for his review before anything goes out. Review takes him about 30 seconds per application, against 4 to 6 minutes each when he did it with AI. The post also promotes his own paid tool, so it is marked promotional.
Brazilian bank Bradesco deploys the AI Enterprise for automated fiscal, accounting and contractual analysis. Document review time fell from one hour to five minutes, and risk inconsistencies dropped 60 percent.
Every idea is a real post from someone who tried it, summarized in our words, with a link to the original. App names are swapped for plain words.