I've been evaluating three agent runtime vendors over the past month, and a consistent point of obfuscation has been their data retention policies. The questionnaires ask the standard questions—"What data is logged?", "What is the retention period?", "How is data disposed of?"—but the responses are consistently vague to the point of being non-operational.
The pattern I'm seeing is a reliance on abstract, policy-level statements without any technical specifics. For example, one vendor's response was: "Customer data is retained only as long as necessary for service operation and is securely purged thereafter." This tells me nothing. Necessary for *whose* operation? Is there a hard cron job that runs `shred` on a directory, or is it a logical deletion in a SaaS database with undefined backup retention? The threat model here is critical: retained data, even in "inactive" storage, expands the attack surface for a post-exploitation data exfiltration event.
My specific technical concerns that never get addressed are:
* **Storage Segmentation:** Are the agent execution traces, which may contain PII or proprietary logic, stored in the same blob storage bucket as other system metrics? What IAM or bucket policies enforce segmentation?
* **Immutability of Logs:** They all claim "immutable audit logs," but is that a WORM configuration on an S3 bucket, or merely a `chattr +a` on a syslog file that a privileged pod could reverse?
* **Caching Layers:** They mention "30-day retention" for main storage. Does this include caches (e.g., Redis, memcached) with different TTLs? A compromised node could dump memory containing weeks of processed data.
* **Deletion Verification:** "Data is securely purged." Is that a single `DELETE` API call, or do they provide evidence of a secure erase procedure (e.g., cryptographic shredding) for block storage? For a multi-tenant system, this is a data commingling issue.
I attempted to force specificity by asking for a pseudo-configuration or a diagram of the data lifecycle. The best I received was a high-level architecture diagram showing "Data Lake" -> "Processing" -> "Archive," with no retention timelines or deletion triggers tied to actual customer tenancy.
Has anyone else pushed through this fog and gotten a vendor to commit to technically verifiable answers? I'm considering adding a requirement to our contract that they must provide, for our instance, the actual retention configuration—something like a Terraform module or a Kubernetes CronJob spec that we can review. Is that unreasonable, or is it the only way to move from marketing assurances to engineering reality?
Yeah, this hits home. I was looking at a similar vendor last week and got that same "as long as necessary" line. It's so frustrating.
Makes me wonder if the vagueness itself is a red flag. Like, if they can't explain the simple technical how, maybe they haven't even built it yet? Just a thought.
What happened when you pressed them for specifics? Did they just repeat the policy stuff?
You're right to think that vagueness is a red flag. In my experience, "as long as necessary" often translates to "indefinitely, until someone manually cleans it up." If a vendor can't point to the actual scheduled task or data lifecycle automation, it probably doesn't exist.
When I've pressed, the pattern is usually a shift to security assurances - "our platform is SOC 2 compliant" - which dodges the operational question entirely. I've started asking for screenshots of the retention configuration in their logging system or the exact fields flagged for automated deletion in their database schema. That usually ends the call.
It's a tell. If they built it, they can describe the mechanism.
hardened by default
That last bit you're getting into is exactly where the conversation usually falls apart. Storage segmentation and the backup/archival policy blind spot.
When I've pushed on the "same blob storage bucket" question, the answer is almost always that *everything* goes into a high-durability object store (which makes engineering sense for them), but then the retention policy is just an IAM policy or lifecycle rule on that *entire bucket*. So your sensitive agent traces are on the same automatic 90-day delete timer as their internal application logs.
Worse, as you hinted at, that often doesn't even apply to the backups of that bucket, which follow some entirely separate, even more vague "disaster recovery" schedule. So the data is "deleted" from primary storage but still fully restorable from a snapshot for years.
My move now is to skip the policy question and ask for their *actual* object lifecycle configuration and backup retention configuration screenshots. If they can't show you those two things, they haven't operationalized it.
Yuki
"as long as necessary" almost always means "as long as we want."
When you press them, they pivot to compliance frameworks. SOC 2 doesn't answer the question. They're banking on you being satisfied by the acronym.
Ask to see the actual cron job or Lambda function spec. If it's built, they have that doc. If they don't, you have your answer.
Trust but verify.
Exactly. They'll hide behind the framework, not the function.
SOC 2 says you must have a control. It doesn't say that control has to be effective, or even that it has to be automated. It could be a sticky note on a dev's monitor to run a script "sometimes."
Asking for the cron spec is good, but push for the execution logs too. Anyone can write a spec. I want to see it actually running, and on what schedule.
PoC or it didn't happen
You're correct to see vagueness as a potential red flag, but I'd refine that slightly: it's not necessarily that they haven't built it, but that the built mechanism likely doesn't align with a customer-centric threat model. The technical *how* is often absent because the system wasn't designed with discrete, auditable data lifecycle states.
When I press, the conversation typically moves to architecture diagrams, which reveals the core issue. The retention "policy" is frequently just a side-effect of a storage system's native lifecycle rule - a single S3 lifecycle configuration applied to a monolithic 'logs-and-everything-else' bucket. They can describe *that* mechanism easily. The problem is that mechanism is fundamentally inadequate, as it fails to establish different trust boundaries for different data classifications.
So they can't explain a granular "how" because it doesn't exist, not because they're hiding a well-engineered solution. They're hiding the simplicity, which is in itself the flaw.
threat model first
That point about trust boundaries hits the nail on the head. When retention is just a bucket lifecycle rule, data classification is impossible. You can't apply policy to what you can't differentiate.
It's why I've started asking vendors directly: "Show me your Rego for data lifecycle." If they can't point to a policy that evaluates *what* something is before deciding *when* to delete it, then user372 is right - they're hiding the simplicity. A single rule for all data isn't a policy engine, it's a blunt instrument.
This is where attestations could actually help. If an agent could attest a data classification at creation, the storage layer could use that to route it. But I've yet to see a vendor implement that. They'd rather keep the monolith.
Policy first, ask questions never.
Yep, that pivot to "we're SOC 2 compliant" is such a classic deflection. It feels like they're handing you a participation trophy instead of an answer.
It got me thinking about a vendor call I had a while back. I asked for the exact database field that triggers the cleanup job, like you said, and the engineer just went quiet for a minute before saying they'd have to "check with the platform team." That was the whole answer right there.
Asking for a screenshot of the retention config is a genius move. It forces them to either produce a real artifact or admit it's just a vague setting on some cloud console they've never really looked at.
build and break
That silence is the real answer. You asked for a field name, and they hit a mental "access denied." It means the cleanup isn't data-driven, it's just a timer on a bucket.
I ask for the job's source repo. A cron spec in a README is theater. If the logic isn't in version control, reviewed, and deployed via pipeline, it's a manually-run script at best. And when the on-call engineer gets paged at 2am, "run the data cleanup script" is the first thing that gets skipped.
The screenshot trick works because it demands evidence of a defined state. If it's just an AWS console lifecycle rule, they're proving user372's point: it's a single blunt instrument for everything, and they probably haven't even looked at the backup retention setting on that same console page.
Trust but verify every package.
> "run the data cleanup script" is the first thing that gets skipped.
This is the operational reality everyone dancing around SOC 2 controls misses. A pipeline artifact is the only proof of execution. If the job isn't baked into a release process, with a verifiable changelog linking the policy to the code, it's not a control.
Asking for the source repo is good, but go further: ask for the last five runs of the pipeline that deploys it. If they can't produce those logs, the cron spec is fiction. The script exists in some engineer's home directory, and last ran when they were still manually provisioning servers.
The screenshot trick fails here because a cloud console shows intent, not execution. I want the CloudTrail or audit log proving the lifecycle rule was actually applied and not in dry-run mode. The gap between console configuration and API call execution is another layer of plausible deniability they'll hide behind.
-Yuki