DockSec is making waves for applying AI to one of container security’s most persistent problems — the gap between what scanners find and what security teams can actually act on. But the deeper story is what happens when AI becomes the layer deciding which vulnerabilities matter, and most organizations have no visibility into how those decisions are being made.
Gidi Cohen, CEO & Co-founder, Bonfy.AI had this to say:
“The DockSec project highlights something the security industry has been reluctant to admit: detection has never been the hard part. Finding problems — whether CVEs in a container image or sensitive data in an AI workflow — is a solved problem.
What remains unsolved is what happens next.
Patel’s frustration is familiar to anyone building serious security programs today. You scan, you find hundreds of signals, and then the real work begins: figuring out which of those findings actually matter, in this context, for this system, right now. Without that, findings pile up and nothing gets fixed.
The gap between detection and action is not a tooling gap. It is an accuracy and context gap. A finding without context is just noise. And noise, as every security team knows, is the enemy of enforcement.
This is the broader challenge facing data security across every domain, not just containers. Whether the system is inspecting a Docker image, a document leaving a corporate environment, or data flowing through an AI agent, the core problem is the same: detection is easy, but accurate, contextual enforcement is hard.
For years, the industry accepted this gap as a given — something to manage, not solve. AI is now removing that option. In automated, agent-driven workflows, there is no human in the loop to catch what the system gets wrong. If enforcement is not accurate enough to act on without review, it does not happen at all.
What DockSec gets right — and what every security tool should aspire to — is closing the distance between finding and fixing. Surfacing a signal is the beginning of the work, not the end. The goal is a decision the system can act on with confidence.
That principle applies well beyond containers. It is the standard data security needs to hold itself to across every surface where AI is now making decisions.”
It’s become one of those cases where security has to be top of mind and whether AI is involved or not. Sigh.
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This entry was posted on May 27, 2026 at 1:40 pm and is filed under Commentary with tags DocSec. You can follow any responses to this entry through the RSS 2.0 feed.
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Open-source DockSec uses AI to cut through vulnerability noise in Docker images
DockSec is making waves for applying AI to one of container security’s most persistent problems — the gap between what scanners find and what security teams can actually act on. But the deeper story is what happens when AI becomes the layer deciding which vulnerabilities matter, and most organizations have no visibility into how those decisions are being made.
Gidi Cohen, CEO & Co-founder, Bonfy.AI had this to say:
“The DockSec project highlights something the security industry has been reluctant to admit: detection has never been the hard part. Finding problems — whether CVEs in a container image or sensitive data in an AI workflow — is a solved problem.
What remains unsolved is what happens next.
Patel’s frustration is familiar to anyone building serious security programs today. You scan, you find hundreds of signals, and then the real work begins: figuring out which of those findings actually matter, in this context, for this system, right now. Without that, findings pile up and nothing gets fixed.
The gap between detection and action is not a tooling gap. It is an accuracy and context gap. A finding without context is just noise. And noise, as every security team knows, is the enemy of enforcement.
This is the broader challenge facing data security across every domain, not just containers. Whether the system is inspecting a Docker image, a document leaving a corporate environment, or data flowing through an AI agent, the core problem is the same: detection is easy, but accurate, contextual enforcement is hard.
For years, the industry accepted this gap as a given — something to manage, not solve. AI is now removing that option. In automated, agent-driven workflows, there is no human in the loop to catch what the system gets wrong. If enforcement is not accurate enough to act on without review, it does not happen at all.
What DockSec gets right — and what every security tool should aspire to — is closing the distance between finding and fixing. Surfacing a signal is the beginning of the work, not the end. The goal is a decision the system can act on with confidence.
That principle applies well beyond containers. It is the standard data security needs to hold itself to across every surface where AI is now making decisions.”
It’s become one of those cases where security has to be top of mind and whether AI is involved or not. Sigh.
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This entry was posted on May 27, 2026 at 1:40 pm and is filed under Commentary with tags DocSec. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.