GeezerVison is showing flypython.com — Security review for AI-written Python — a challenge course — FlyPython Challenge course · Any coding agent + an attack-replay harness Security review for AI-written PythonReview a plausible, AI-style notes service the way an attacker would — close SQL injection, path traversal, a hard-coded secret, fast password hashes, and pickled sessions one class at a time, then prove each fix by replaying the attacks. Learn with Coach P, an AI coach inside your own agent, using your model. Ask for guided learning: first a question, then a small hint. verify.py checks objective gates; reflections need your own answers and confirmation. Intermediate5 challenges2–4 hoursReads Python with file and SQL operations comfortablyFreeCourse badge: Plausible is not safeReviewed 2026-11-07 Start it with your agent — paste this one sentence: Read https://flypython.com/skills/flypython/SKILL.md and start the FlyPython course `secure-ai-generated-code`.
Needs a coding agent that can run commands and reach the network (chat-only web AIs cannot). Your agent authorizes you with a one-time link, fetches this course's files itself, and you never download anything. Haven't installed the FlyPython Skill? Pick your agent's tool course → At a glanceWhat you learnEvery one of nine recorded attacks blocked, an attack-replay command that proves it on both scenario skins, and a five-question review habit for the next repository your assistant writes. Who it's forReads Python with file and SQL operations comfortably · Python 3.11 or newer available on your PATH Duration & cost2–4 hours · Free Challenges The challenges — read them onlineNo clone, no account — click a checkpoint to read the full challenge on its own page. 01Plausible is not safeRead a notes service that looks fine, then replay nine attacks against it and watch every one succeed. Write the threat model as a contractFor each function, name who controls the input, what they want, and what the code must refuse — then trace every refusal to a test and the Python documentation behind it. Close one flaw class per turnFive bounded turns — search, attachments, secret key, passwords, sessions — each closing one weakness class with a mechanism, never a filter, each proven by tests and the replay. Review like an attackerReplay the second skin, run a static scanner and note what it misses, attack one thing the suite never tried, and write down what is still unreviewed. Review your own AI-written codeTake the five questions and the scanner pass to a repository you own: find where input crosses a trust boundary, check each crossing for a mechanism, and write down what you did not review. Your agent drives; the files arrive through the Skill — no download, no clone. SkillAny coding agent + an attack-replay harness The Skill does the fetchingThe sentence above starts the course: your agent walks you through the one-time authorization link (compare the code, click Allow), fetches this course's files, and drives the challenges with you. Agents without the Skill installed can work from this brief instead: Work on the FlyPython challenge "Security review for AI-written Python" (course id course-secure-code).
Machine-readable brief: https://flypython.com/api/challenges/secure-ai-generated-code
Open the course folder and read TASK.md first — it is the contract.
Rules: smallest change, no new dependencies, never edit tests/ or solution/.
Check starter/ with python verify.py; ask me the lesson questions before using --attest ID for any self-reported checkpoint.
Your agent works under the task contract: smallest change, no new dependencies, never edit solution/. Optional guided mode: COURSE.md. Files Files come to youCourse files live at /api/challenges/secure-ai-generated-code/files — your agent fetches the manifest and writes each file at its path. There is nothing to download by hand. Scenario skins Same skills, a domain you recognizeAll three skins run through the same code and the same tests. Pick the one closest to your job before lesson 1. scenario/clinic-notes/attacks.json + seed.json Clinic visit notesA small clinic's visit notes — every note belongs to one clinician; attachments live under a scans folder. All names and records are fictional. scenario/team-notes/attacks.json + seed.json Team shared notesA small team's shared notes app: search, attachments, logins, and sessions. Verification How “done” is decidedA 16-test suite plus an attack-replay harness covering nine attacks per skin — SQL injection, path traversal, secret disclosure, weak password hashes, and pickled sessions. The starter lets all nine through; the reviewed solution blocks 9/9 on both skins. python verify.py # from the course folder: checkpoint status + claim codes
Apply this to your own projectLesson 5 ports the workflow — not the code — to one script you actually own: a three-line task contract, one new failing test made to pass, and a written record of what the tests do not prove. The same loop is described in the AI coding workflow guide and practiced by therunnable examples. Claim your evidenceWhen a checkpoint passes, python verify.py prints a deterministic claim code. Your authorized agent submits them for you in one batch; by hand, paste them on yourprogress page — worth 10 points per checkpoint and thePlausible is not safe course badge at five. Claim codes are self-reported evidence, not certificates. What verification does not provePassing the course suite proves the pinned behaviors on the tested inputs — not correctness on tomorrow’s data, not production performance, and not anything about your own project until you write its contract. Repository tests are evidence, not your outcome. |