Does a Checkup Report Saying 'Fine' Mean You're Really Fine?
You get a checkup and the report says "nothing abnormal." But you know in your heart: that only means this time, these items, this machine found no problem—it doesn't mean you're absolutely healthy. Some issues weren't tested this time; some are too early to catch. The report "passing" and "actually healthy" are two different things.
It's the same when AI runs a security scan for you. When it says "no vulnerabilities found," what it really means is "in its judgment this time, by the patterns it has seen, it didn't recognize a problem"—not "this code is absolutely safe."
False Negatives: The Most Dangerous Kind of Error
A check can make two kinds of error. False positive: there's no illness but it reports one—at worst a needless scare and one extra check. False negative: there is an illness but it reports none—that's the deadly one, because it makes you mistakenly feel safe and let your guard down.
A false negative in an AI security scan is a real vulnerability the AI calls "no problem." It may miss the issue because it hasn't seen this attack pattern, lacks context, or is fooled by cleverly disguised code. The moment you treat "it didn't report a problem" as "there's no problem," the vulnerability ships openly.
The Right Stance: Treat It as a 'Lead,' Not a 'Verdict'
So is the AI scan useful? Yes—it can sweep through quickly and flag a batch of suspicious spots, saving you effort. But its output is a lead, not a verdict.
The right move is cross-verification: when the AI reports a problem, a human confirms whether it's real; when the AI says no problem, don't call it done either—critical paths still need human review, dedicated security tools, and tests working together. Each independent check lowers your chance of being burned by a false negative.
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"There's a real vulnerability, but the check reports no problem"—this miss-type error is called a "false ____."
答案：negative
A real problem judged as no problem is a "false negative" (a miss); in security it's more dangerous than a "false positive" (a false alarm).
Which case is a "false negative"?
答案：The code really has a vulnerability, but the scan says "no problem found"
A false negative = a real problem judged as no problem (a miss); the first option "no illness reported as illness" is a false positive.
Judge: the AI scanned the code and said "no security issues found," which means the code is now absolutely safe and can be shipped with confidence.
答案：No
"Not found" only means it didn't recognize a problem this time, by the patterns it has seen; a false negative (miss) may exist, so it isn't absolute safety.
What's the most accurate meaning of "AI scan passed"?
答案：In the AI's limited judgment this time, it didn't recognize a problem—a lead, not a verdict
An AI scan passing is the result of a limited-scope check; treat it as a lead, not a verdict of "absolutely safe."
An AI security scan reports "no problems found" for a critical piece of payment-handling code—what's the safest follow-up?
答案：Treat the conclusion as a lead and add human review, dedicated security tools, and tests for cross-verification
Critical code needs cross-verification by multiple independent means; a single AI "no problem" can't rule out a false negative.
Judge: in security, a false negative (missing a real vulnerability) is usually more dangerous than a false positive (a false alarm), because it makes people feel safe and let their guard down.
答案：Yes
A false positive at worst wastes a recheck, while a false negative lets a real vulnerability through and lulls people into lowering their guard—far worse.