This was quickly resolved and announced as ‘CVE-2026-34219’, courtesy of the team. The broader concern, however, was separating the real bugs from the agents from the bugs that confidently presented themselves as such.
“The surprise was how little work went into finding them, and how much work went into distinguishing the real bugs from the ones that just looked real,” wrote Nikos Baxevanis, author of the post.
The difficulty started with what an agent produces. A fuzzer, the standard tool that hurls malformed data at software until something breaks, returning a crash and a record of where it happened, which an engineer can confirm in minutes.
However, an agent returns a created story. It traces how the flaw could be achieved, argues why it matters, proposes a severity rating, and provides working code that demonstrates the attack. It all arrives in flowing prose, and it’s the same whether the bug is real or made up.
According to the Foundation, three types of false positives continued to occur.
The first was a crash that only occurs on a test build, where the compiler enables security checks that the shipped software doesn’t provide, so that nothing breaks for real users.
The second was an attack that only works if the dangerous value is manually placed in the program, because any route an outsider might take to deliver it first rejects the value. The third came from formal verification, the practice of mathematically proving that code behaves correctly, which assumed a proof by proving something trivially true and told the reviewers nothing about the software.
Credit : cryptonews.net
