![Practical AppSec, Part II: The Limitations of “Shift Left” (and Why Runtime Is the Right Time)](https://cdn.prod.website-files.com/63e8dd453f71270c6845992b/65e6ee112e7a589579e6fcba_Practical%20AppSec%20blog%20(2).webp)
Practical AppSec, Part II: The Limitations of “Shift Left” (and Why Runtime Is the Right Time)
In the first part of our Practical AppSec series, we talked about the reasons developers don’t trust AppSec – and how that distrust is rooted in tools that focus on theoretical vulnerabilities rather than real, provably exploitable ones.
Even when security alerts frustrate engineering and security teams, they’re still plugging away at those dashboards full of CVEs, trying to make them all turn green. Why? Well…because of shift left, of course.
We all know it’s the right way to do application security, because it saves money. If you read security blogs, you’ll have seen a specific number over and over: Fixing vulnerabilities earlier in the development life cycle saves you up to 100x versus fixing them later, according to pretty much every security vendor out there. Except…does it?
“Shift Left” Rests on Shaky Foundations
OWASP founder Mark Curphey earlier this year produced compelling evidence that the much-vaunted 100x statistic was just an “urban myth,” sourced from an internal IBM training manual based on data gathered, at absolute latest, in 1981. A lot of things have changed in software development in that time (I can certainly think of a few), but the statistic lingers on stubbornly – probably because it made sense for a lot of vendors selling shift-left products to use it in their ROI calculators.
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According to recent research, shifting left may not really save any money or effort at all. In a paper from 2016, three researchers tried to find evidence for the “delayed issue effect,” in which an issue requires more effort to resolve when it is found later in the development cycle.
The team “found no evidence for the delayed issue effect,” and concluded that it was a “historical relic that occurs intermittently only in certain kinds of projects.”
What if we rethought application security without the truisms and urban myths? What if we thought about what would actually work best for the problems and situations today’s organizations find themselves in?
Let’s take a moment for a thought experiment that takes us outside the realm of development – and into the kitchen.
The Peanut Butter Jar: A Thought Experiment
You’re cooking for a friend, and you know he has a peanut allergy. You’re a considerate friend (and certainly don’t want to end the night with anaphylaxis), so you don’t use any peanuts in the food. You even check the labels of everything you use, just to be sure.
When your friend comes over, he says he’s got something new – a detector that can determine if it’s safe for him to eat the meal you’ve cooked. He turns on the detector, and it flashes red. “It’s ok,” he says. “I’ll grab something on my way back.”
“Hold on a minute,” you tell him. “I was so careful to make sure there were no peanuts anywhere in our meals. You can search my whole kitchen.”
So the two of you do just that, and after an hour of searching, you find it: a small, unopened jar of peanut butter on the back of a shelf. “I didn’t use this! It’s still sealed!” you say.
Your friend says: “It’s built to detect the presence of peanut-containing products in the building, rather than whether they’re being used. It won’t stop flashing until you take the peanut butter out of the house.”
When you return from disposing of the jar outside, you can barely hide your annoyance. Your friend confesses that he’s not so sure about the scanner. “I haven’t actually found a house where it says I’m safe to eat yet,” he says, miserably. “And apartments? Forget it.”
And it gets worse: everywhere he goes, he’s spending time looking through the cupboards and trying to figure out when he should really avoid the food, and when it’s fine. There’s no chance of eating a hot meal, and he says some of his friends seem to be avoiding his visits altogether, because it’s a big pain every time.
It’s obvious what doesn’t make sense about the peanut scanner, isn’t it?
There’s no need to scan the entire building when what really matters is what actually makes its way to the plate to be eaten. We’d be better off just analyzing the plates when they’re ready to be served, and limiting our scan to real risks, not theoretical ones.
When we move from the kitchen to the scrum, the lesson holds. If you scan for every hypothetical vulnerability from your manifest file – with little regard for whether the vulnerable library is actually loaded or running, or whether a vulnerable function is called – you’re going to cause a lot of wasted time and frustration.
Real Risks Come from Running Applications
The truth of the matter is: scanning based on manifest files was always going to be like the peanut scanner. But if “shift left” isn’t saving money or effort, and over-broad scanning tools are sowing distrust between teams, what’s the alternative?
In the kitchen, what matters is what’s served. In software, what matters is what’s loaded, running, and accessed when the application runs.
Application security vendors have been selling “shift left” with the 100x statistic for decades. In that time, open source use (and CVE numbers) exploded, and just about every organization adopted some kind of tooling to detect vulnerabilities early in the development process.
But as Valery Legasov said in the TV miniseries Chernobyl: “Every lie we tell incurs a debt to the truth. Sooner or later, that debt is paid.”
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What’s true about lies is also true of an industry’s foundational myths.
Even if no one intentionally lied about the benefits of pushing security earlier into the SDLC, the frustrations, wasted effort, and wasted time of today’s AppSec programs are all a debt being paid to the foundational myth of “shift left.”
But a new era is coming – as organizations search for lean, practical AppSec solutions, they’re learning that the only way to really see what’s exploitable is to check on an application while it’s running.
If scanning a running application is more focused and efficient than scanning the content of a manifest file, why isn’t everyone already doing it – and what else could a solution with that kind of visibility do for an AppSec program?
Stay tuned: we’ll talk about the answers to these questions in the final part of this blog series – Practical AppSec, Part III: How Oligo Keeps Focused on Real Risks.
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