Two of the most respected names in enterprise cybersecurity have gone on record: Anthropic’s Claude is writing less secure code than it was six months ago, and they can prove it.

The alarm was first raised publicly by Dave Kennedy, CEO of TrustedSec and a former NSA analyst, in a Forbes investigation published April 22. Kennedy’s team had been using Claude Opus to generate attack simulations and accelerate development — until code quality fell off a cliff.

“Right now, from five weeks ago to today, the code quality is over 47.3% worse than when it was first released,” Kennedy told Forbes. “It’s really bad, I mean unusably bad.”

The Numbers Are Hard to Dismiss

Kennedy built an internal tool to benchmark Claude’s output across four dimensions: code quality, bugs introduced, security issues, and task completion. The 47.3% degradation figure comes from that tool, measured from Claude Opus 4.6’s release in early February through late April 2026.

But Kennedy isn’t the only one with data. Jens Wessling, CIO at security testing company Veracode, shared findings from a year-long benchmark study. Veracode tested AI coding models across 80 standardized coding tasks, measuring how often each model introduced security vulnerabilities.

The results for Claude Opus 4.7 — the current flagship model — are concerning:

  • 52% of coding tasks contained at least one security vulnerability
  • That’s up from 51% for Opus 4.1 and 50% for Claude Sonnet 4.5
  • Comparable OpenAI models introduced vulnerabilities in approximately 30% of tasks

A 52% vulnerability rate means that if you’re using Claude Opus 4.7 to help write production code without rigorous review, the statistical odds are that more than half of what it produces has a flaw.

Root Cause: Thinking on the Cheap

Forbes’ investigation surfaced a named Anthropic source: Boris Cherny, head of Claude Code, who confirmed that Anthropic reduced Claude’s pre-editing “thinking effort” from high to medium to cut token costs.

This is significant. The thinking phase — the model’s internal reasoning before generating output — is where Claude evaluates the correctness, security implications, and edge cases of code it’s about to write. Cutting that phase to save compute means less time spent considering whether the code it’s about to produce could be exploited.

Anthropic has not issued a formal public response or patch as of publication. The Forbes piece notes that Anthropic is “investigating.”

The Real Risk: Novice Developers

Kennedy and Wessling both emphasized the same concern: the developers most at risk from this degradation are the least experienced ones.

Senior engineers who use Claude for acceleration typically review everything before merging. They’ll notice a suspicious function, an unescaped input, a missing auth check.

Novice developers — who represent a large and growing share of Claude Code’s user base — are using the tool to write code they couldn’t write themselves. They’re not reviewing it with the same eye. If Claude introduces a SQL injection vulnerability or an insecure deserialization pattern into code a junior developer is treating as a trusted output, that vulnerability often ships.

An AI executive at chipmaker AMD also weighed in on GitHub, describing Claude’s thinking as so “shallow” that it “cannot be trusted to perform complex engineering tasks.” The comment has since spread widely across the security and developer communities.

What Categories of Vulnerabilities Are Appearing?

While the Forbes piece doesn’t enumerate specific CVE classes, based on Veracode’s methodology and the types of coding tasks tested, the most common AI-generated vulnerability categories in recent industry research include:

  • Injection flaws (SQL injection, command injection, prompt injection in LLM-integrated code)
  • Broken authentication (insecure session handling, hardcoded credentials)
  • Insecure deserialization
  • Missing input validation
  • Exposed secrets in generated config or environment snippets

If you’re using Claude for code generation today, these are the categories to prioritize in your review process.

What You Should Do Right Now

  1. Don’t treat AI-generated code as production-ready without review. This was always best practice; current data makes it urgent.
  2. Run static analysis on every Claude-generated code block. Tools like Semgrep, Snyk, and CodeQL can catch many vulnerability classes automatically.
  3. Consider reverting to Claude Opus 4.6 or switching models for security-sensitive workloads. Kennedy’s firm has already made this decision internally. Opus 4.7 was described as “marginally better” than 4.6’s degraded state, but still below 4.6’s original quality.
  4. File feedback with Anthropic directly. The Claude feedback portal and GitHub issue tracker for Claude Code are both live. Enough signal from enterprise users accelerates the investigation.

Anthropic built its reputation on safety-first AI development. This is a moment where that reputation is under pressure from the market, and the technical debt on the thinking-effort decision is now visible. The expectation is that Anthropic will address this — but until they do, the burden is on developers to compensate.

Sources

  1. Forbes (The Wiretap): Anthropic’s Claude Is Pumping Out Vulnerable Code, Cyber Experts Warn
  2. The Register: AMD AI director calls Claude too ‘shallow’ for complex engineering tasks
  3. Veracode: AI Code Security Research

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