The Monoculture Problem: Why AI-Generated Code Fails in the Same Places
AI-generated code creates a dangerous security monoculture, making shared bugs easier to find, exploit, and scale across thousands of apps.
Tag: software security assurance
Does “Move Fast and Break Things” Still Work in the AI Era? A Practical Review for IT Teams
Why “move fast and break things” no longer fits AI: learn where speed still helps, where risk grows, and how teams can innovate with guardrails.
AI Can Find the Bugs. Who Decides What Secure Means?
Can AI really secure code? Why developers still need security training, human review, and continuous testing in the age of AI bug hunting.
Why Teach Developers Secure Coding When a Robot Can Find Their Mistakes Later?
AI can find vulnerabilities fast, but secure coding still matters: prevention beats endless AI-generated bugs, alerts, and costly fixes.
Why Bother Teaching Developers Security When AI Can Just Mop Up the Mess Later?
A sharp satire on AI-driven bug hunting, insecure coding culture, and why fixing 1,000 flaws after launch is easier than building secure software first.
Shipping the Unspecifiable: Are Frontier AI Models Released to Engineering Standards?
Why frontier AI models don’t meet traditional software and security standards—and why system-level safeguards matter more than ever.
The Lord of COBOL on Galactica Speaks: AI Is Scary, Please Don’t Fire the Security People
A witty take on AI security, trust, and risk—why giving autonomous systems access to code, money, and sensitive data should alarm everyone.
Systems Over Models: Why Aisle’s cURL Findings Matter (And Where AI Bug Hunting Goes Next)
How Aisle found 6 new cURL CVEs where top AI scanners missed everything—and why system design, not bigger models, is reshaping AI vulnerability detection.
How Organizations Can Secure Agentic AI Use
Agentic AI needs guardrails before it touches your network.
The Older I get, the More the Hype Cycles Rhyme
AI security echoes open source’s old promises: without real control, isolation, and trust, prompt injection remains a built-in risk.
Why Generative AI Produces Insecure Code: Insights from the 2026 Veracode Generative AI Code Security Report
Veracode’s 2026 GenAI Code Security Report reveals AI-generated code still lags on security, with 44% of outputs introducing vulnerabilities.
David’s Review of the AI Secure Coding Experiment (SANS CWE Top 25)
A critical review of the Skynet vs HAL9000 experiment, highlighting AI collaboration strengths, key flaws, and why human validation still matters.
Encouraging Responsible Bug Reporting: A Comprehensive Guide for Users and Maintainers
Learn how to reduce false positives in AI-generated vulnerability reports with verification, prioritization, and better bug reporting practices.
HAL 9000’s Assessment of the SANS Top 25 Security Experiment
HAL9000 compares ChatGPT and Claude on SANS Top 25 security writing, exposing strengths, blind spots, and what the experiment really proves.
Skynet (ChatGPT) on the SANS Top 25 Security Experiment
We asked Skynet (ChatGPT, acknowledging its Skynet contribution to the series) to assess the SANS Top25 experiment