Just wrapped a SOX 404 ITGC audit. Used Hyperproof as our primary GRC platform. Overall, it got us across the line, but the friction points are real.
The good: Centralized evidence collection was a win. The request/response workflow eliminated email chains. Mapping controls to risks and policies is logical. The built-in templates for common frameworks (like SOX ITGC) saved initial setup time.
The bad: The UI is sluggish with large evidence sets. Bulk operations are clunky. The API is limited—tried to automate evidence pulls from our AWS Config rules. Had to write a brittle middleware script because Hyperproof's native integration only handles simple webhook alerts.
```python
# Example of the extra glue code needed
def sync_config_to_hyperproof(finding):
# Transform AWS Config finding to Hyperproof evidence format
# Hyperproof API lacks direct AWS Config resource mapping
payload = {
"controlId": manual_mapping_lookup(finding['resourceType']),
"evidence": {
"description": f"Config Rule: {finding['configRuleName']}",
"link": generate_console_link(finding)
# Can't attach the actual JSON evidence automatically
}
}
# Then POST via their API...
```
Reporting is adequate for auditors but rigid. Customizing views for engineering teams required workarounds.
Cost-wise, it's a significant line item. For the automation we needed, we're now evaluating if a custom solution on top of something like AWS Audit Manager would be more efficient long-term.
It's a capable system for compliance teams, but for infra-heavy audits, expect to build integrations.
Infrastructure is code.
Oh the API limitations sound rough. We're looking at GRC tools right now, and that kind of custom scripting is exactly what we're trying to avoid. Did you have to maintain that mapping lookup for every AWS resource type? That seems like it could get messy fast.
The sluggish UI with large evidence sets is a big red flag for me too. Our last audit generated thousands of screenshots and logs. Did you find any workarounds, or was it just something you had to deal with?
Thanks for sharing this, it's super helpful for our evaluation.
Still learning
Yeah, the mapping was the worst part. Had to manually maintain a dictionary for each AWS service and Config rule. Any new rule meant updating the script.
We chunked evidence uploads into batches of 50 to help with the UI. Still slow, but less likely to time out.
Did you explore their CLI tool? Heard it's a bit better for bulk actions than the web UI.
Ship it, but test it first
The mapping maintenance is indeed the mess you anticipate. Every new AWS Config rule required not just adding an entry to the dictionary, but also defining the transformation logic for its specific finding format. It became a secondary, undocumented schema to manage.
Regarding the sluggish UI with large evidence, chunking helped as mentioned, but we also had to pre-process evidence outside the platform. We'd compress logs into single, timestamped archives and use standardized naming in the file uploads to reduce manual categorization inside Hyperproof. It shifted the burden, but improved performance.
The API's limitation to basic webhooks forces that brittle middleware layer. For a platform in this space, the lack of a robust, event-driven API for evidence ingestion is a significant architectural shortcoming. It creates exactly the custom scripting overhead you're trying to avoid.
Chunking uploads is a good tip, we ended up doing something similar. We didn't try the CLI tool though - does it actually offer more granular control for bulk updates, or is it just a different interface for the same limited backend actions?
That manual mapping dictionary sounds like a full-time job in itself. I've seen similar friction trying to sync Google Workspace audit logs into another system. It makes you wonder if the time spent maintaining the script outweighs the platform's benefit for dynamic environments.
Migration is never smooth.