Recently I noticed an interesting new announcement from Google Deepmind called: “Introducing CodeMender: an AI agent for code security“. Since I am into security this article caught my attention.
A growing trend in the security tooling space is the emergence of AI-powered code auditors — tools that don’t just find vulnerabilities, but claim to fix them automatically.
Google has joined this AI secure programming race with a new product from DeepMind:Google CodeMender — an “AI agent for code security.”
At first glance, the announcement sounds impressive. But for all its confident language, the details are thin. The only concrete number Google offers is that CodeMender, during beta testing, “upstreamed 72 security fixes to open source projects.” That’s it.
No information on what kinds of vulnerabilities were fixed, how those fixes were reviewed, or what the false positive rate looked like.
The Problem with “AI Fixes” for FOSS
Anyone who’s ever run a static security analysis tool—like Bandit or Python Code Audit—across a few large codebases knows: you’ll find hundreds of potential issues in no time. Issues are always context-dependent. The value isn’t in simply finding security issues; the real value is in finding those with a high potential risk for your specific context.
When researchers or vendors highlight findings from open source projects, it feeds a misleading narrative: that FOSS software is insecure. In reality, open source projects are simply visible and transparent. So easy targets for scanning and academic papers.
Meanwhile, the majority of truly critical systems run on proprietary software that never sees the light of day. Those code bases are scanned too, sometimes, but the results stay buried under NDAs and compliance reports.
Context Matters — and So Does Caution
Security fixes in complex systems are never plug-and-play. Changing “unsafe” code without full context can break business logic, disrupt continuity, or introduce subtle errors. Since regression testing is expensive and always risk-based, you never know in advance what new risks are introduced.
From a security standpoint, fixing potential weaknesses is always desirable. But from a business standpoint, touching code that “isn’t broken” carries risk and cost. That’s why many security recommendations end up parked on backlogs, awaiting time, budget, or consensus.
The Boring Truth: Security by Design Still Wins
The best security defence isn’t a new hype AI product — it’s good engineering.
- Bake security by design into every layer of your stack.
- Review your architecture and designs
- Run SAST scans and security audits often
- Use only security tools that are 100% open, transparent, and you can trust!
Real security isn’t about buzzwords — it’s about visibility, verification, and trust.
These practices are unsexy, slow, and human-intensive. But they have proven to work.
Tools like Google CodeMender could become helpful companions for such processes, but not replacements. And for now, there’s another catch: CodeMender isn’t available to anyone. It’s a closed DeepMind research product, not a tool the community can audit, test, or even benchmark.
If history is any indication, many DeepMind “announcements” quietly fade before reaching real users. Let’s hope this one doesn’t — and if it does, maybe someone will build an open FOSS alternative that values both security and transparency.