What the Experiment Tests
This is a cleverly designed security experiment. AI for source-code auditing is nothing new, but binary analysis (looking directly at compiled machine code, with no readable source) is far harder—even human experts need specialized training and tools. Quesma hid a known backdoor in a 40MB binary and had AI look for the needle in a haystack, essentially measuring AI's real capability in this high-difficulty, high-value domain. Whether it can find it, how accurately, and how much guidance it needs are all hard metrics the industry cares about.
The Offense-Defense Significance of Binary Auditing
The weight of this matter is in touching a core pain point of supply-chain security: in reality we run vast amounts of software with no source, only binaries—commercial components, firmware, obfuscated dependencies. These are precisely the best hiding places for backdoors and malicious code, and manual binary auditing is so expensive that only a tiny few scenarios can afford it. If AI can bring down the cost of binary auditing, defenders will gain a powerful weapon to screen at scale the binaries they were previously unable to inspect. But offense and defense are the same coin—the same capability can also help attackers find exploitable vulnerabilities faster. Whatever the result, experiments like this are preparing for an arriving reality: AI entering the security contest at the binary level will redefine the cost and boundaries of supply-chain security. Worth the attention of everyone who cares about security.
via: Hacker News