Benchmarks, comparison pages, GitHub Actions hardening guides, and AI code review workflows for Python teams that want lower-noise static analysis.
11 articles
We ran Skylos on popular open source Python projects, submitted pull requests to remove dead code, and all three were merged by maintainers. Here's what we found, how the LLM verification agent worked, and what the maintainers said.
FastAPI's async-first design and Pydantic validation prevent some bugs but introduce others. Here are 8 real vulnerability patterns in FastAPI applications — from SSRF in background tasks to Pydantic validation bypass — and how to detect them with static analysis.
Django's ORM prevents SQL injection — until your code uses raw(), .extra(), or cursor.execute(). Here are 7 real vulnerability patterns in Django applications, which tools detect each one, and how to test them yourself.
A side-by-side comparison of the three main Python static analysis tools. We ran all three on the same codebase and compared detection rates, false positives, speed, and CI/CD integration — with real output examples.
We ran static analysis on FastAPI, Flask, Pydantic, Rich, Requests, httpx, Click, Starlette, and tqdm. The results: 1,800+ security findings, 4,195 quality issues, and 730 pieces of dead code across 9 of the most popular Python packages.
We ran Skylos and Vulture on the Flask repository. Skylos found all 7 dead items with 12 false positives. Vulture found 6 but produced 260 false positives. Here's the full breakdown with real output.
Every unused function in your Python codebase is attack surface you don't need. Here's how dead code creates real security risks, why it gets worse with AI-generated code, and how to detect and remove it systematically.
AI generates code instantly but humans still review at 10 lines per minute. Here's why the AI PR flood is breaking code review, what the data says about review quality in 2026, and how to automate security and quality gates.
LLMs write code fast but introduce security flaws. Here's why AI-generated Python code fails security checks, the most common vulnerability patterns from Copilot, Claude, and Cursor, and how to detect them with static analysis.
Static Application Security Testing is supposed to catch vulnerabilities before they ship. In practice, most teams ignore SAST results because 70%+ are false positives. Here's why, and how taint analysis and framework awareness fix it.