CASB and DLP get compared as if you have to pick one. You don't. They answer different questions, and most mature security programs run both. A CASB governs which cloud apps people use and what they can do inside them. DLP enforces rules about content: this string looks like a credit card number, this document is tagged confidential, so block the upload.
The comparison that actually matters is not CASB versus DLP. It is what both of them check versus what neither of them watches. Both evaluate a move at the moment it happens, against a rule written in advance. Your most valuable data leaves on access you granted on purpose, through channels both tools were configured to allow. Every move is permitted. The pattern across moves is the breach.
What a CASB does, and does well
A Cloud Access Security Broker sits between your users and your SaaS estate. It discovers shadow IT, the apps employees signed up for without telling anyone. It enforces access policy: who can reach Salesforce, whether downloads are allowed from an unmanaged device, which sharing settings are permitted in Google Drive. It applies conditional access tied to identity, device posture, and location.
This is real coverage. A CASB is the right tool for SaaS governance. If you need to know which cloud apps hold company data and to control how people reach them, a CASB does that better than anything else in the stack. Hilt does not replace it.
Where a CASB stops is the SaaS boundary. It governs access to and activity inside cloud apps. It has limited visibility into what happens on the host once data lands there, and it reasons about access events, not the shape of data movement over time. An account with granted, appropriate access that moves data in an unusual pattern is, to a CASB, an account using access it was given.
What DLP does, and does well
Data Loss Prevention enforces content rules. It inspects files, emails, and uploads for patterns: regular expressions for account numbers, classification labels, fingerprinted documents. When content matches a rule, DLP acts, usually by blocking the transfer or quarantining the file.
This catches a real class of mistake. Someone pastes a customer list into a personal webmail draft. Someone attaches a labeled document to an outbound email. DLP is good at the known-bad-content case, and it is the right tool for enforcing content policy. Hilt does not replace it either.
DLP's structural limit is that it reasons about content, not behavior. It answers "does this payload match a rule." It does not answer "is this movement normal for this identity." A file with no triggering content, moved through an approved channel, in a pattern that does not fit the user behind it, is invisible to a content engine. And DLP carries a well-known operational cost: tuned tight, it generates false positives that bury teams; tuned loose, it misses. Either way it is reading your data to make the call.
Where they overlap, and where the gap is
The two categories overlap on the egress points everyone watches. Both have a view of SaaS uploads. Both can be configured around email and web channels. Vendors increasingly bundle them, so the line blurs in the product sheet.
Neither closes the same gap. A CASB knows the access was granted. DLP knows the content did not match a rule. So a permitted user, with appropriate access, moving data that carries no rule-triggering content, through a sanctioned channel, in a pattern that is wrong, passes both. Not because either tool failed. Because neither was built to evaluate the pattern of movement across permitted actions.
Consider a researcher who copies proprietary code in small chunks, off-hours, through an FTP connection approved for legitimate transfers. The access is real, so the CASB sees an authorized session. The payload is source code with no PII pattern, so DLP finds nothing to match. Each action is permitted. The danger is the sequence: this identity, this volume, this hour, this destination, against months of how that identity normally moves data. That is the signal, and it lives between the two tools.
What runtime data movement governance adds
The only place to see the dangerous pattern is at runtime, while the data moves. Not before, where predictive tools guess and are wrong a lot. Not after, in the forensics that arrive with the disclosure letter. On the movement itself, as it forms.
Hilt watches data movement at the kernel, metadata only by default, off the path. It does not inspect content to do this, and it does not have to read your data to see that a pattern is wrong. Each move resolves to a probabilistic, source-dependent identity: which user, which job, which destination, and whether this fits what that identity normally does. The signal is not one bad event. It is the deviation across layers at once: the job is unusual for this identity, the read is a bulk pull of high-value paths in a short window, the destination volume is off despite the approved channel. Any one alone is noise. Together they are a pattern, and a pattern is a case, not an alert.
This is additive. A CASB governs SaaS access. DLP enforces content policy. Hilt watches the runtime pattern of movement underneath both, on cloud workloads and user endpoints, and resolves it to the job behind the move. It does not block content inline, and it does not broker SaaS sessions. When the pattern is dangerous, it responds with host-level network isolation, quarantine from the control plane, never by sitting inline or filtering packets. The collector never stands between your data and where it is going. It does not block, drop, or alter traffic.
It also keeps your data where it belongs. The path from kernel event to written case runs single-tenant inside your own cloud, AWS, GCP, Azure, or Ali Cloud. Events never leave your account. The overhead is negligible, on the order of 0.1% of one core and 4 to 8 MB of memory per host, because the collector observes the move rather than standing in its way.
How to think about all three
A useful way to place the three layers:
A CASB answers: which cloud apps, and what can users do inside them. Run it for SaaS discovery and access governance. It is the right tool for that, and Hilt does not do it.
DLP answers: does this content match a rule. Run it for content policy on the channels you can enumerate. It is the right tool for that, and Hilt does not do it.
Runtime data movement governance answers: is this movement normal for the identity behind it. It scores the pattern across permitted moves, at the kernel, metadata only, off the path, and writes the dangerous one up as a case. It is the layer that catches the move both other tools correctly let through.
None of these replaces the others. The mistake is assuming that because the CASB allowed the session and DLP found no matching content, the movement was safe. Permission and content are two checks. The pattern is a third, and it is the one that fits the threat that uses your own access against you.
The bottom line
CASB versus DLP is the wrong frame for the threat that matters most. One governs access, one enforces content, and a permitted user moving rule-clean data through a sanctioned channel passes both while the pattern of movement is the actual breach. That pattern is only visible at runtime, on the movement itself, resolved to the identity and the job behind it.
If your CASB confirms the access was granted and your DLP confirms the content matched no rule, you still have not answered the question that catches the insider and the compromised account: did this data move the way this identity normally moves it. If you want to see how that resolves at the kernel without reading your data or sitting in the path, we are happy to walk an engineer through it on a 30-minute technical call.