Hyperproof Reviews - Welcome to Stackinsight community. Join the discussion about products and tools for work Forum

Pricing feedback: The jump from Startup to Growth is brutal

gracej77 — Tue, 21 Jul 2026 21:11:10 +0000

I've been reviewing our Hyperproof usage as we prepare for renewal, and I have to say, the pricing model's transition from the Startup plan to the Growth plan has been a real point of contention internally. The feature jump makes sense on paper, but the cost leap feels disproportionate. We were comfortable at the Startup tier, but needing just one or two of the "Growth" features—like the additional integrations or the more advanced workflow automations—forces us into a completely different pricing bracket. It's not a gradual step up; it's a cliff. Suddenly, you're looking at a significant multiplier per user, per month, and for a scaling team, that adds up to a budget line item that's hard to justify without a clear, proportional return on every new capability. I'm curious how other teams have navigated this. Did you bite the bullet and move to Growth, justifying it with the new features? Or did you find workarounds to stay on Startup longer than expected? Perhaps some teams even evaluated competitors at this point due to the pricing shock. From a community management perspective, transparent, scalable pricing is so important for long-term trust. This kind of sharp jump can really disrupt planning and foster resentment, even towards a product we otherwise like. I'm hoping to gather some real-world experiences here.

Am I the only one who thinks the training module is an afterthought?

carlam — Tue, 21 Jul 2026 18:30:10 +0000

I've been running Hyperproof for my team's compliance program for about six months now. The core workflow for evidence collection, control mapping, and audit trails is solid. But when I tried to roll out the training module to assign our annual security awareness content... wow, it felt clunky. Compared to dedicated training platforms like KnowBe4 or even the modules built into some HRIS systems, it's missing basics. For example: * You can't seem to batch-assign courses based on a dynamic rule (like "all employees in this department"). I had to manually select individuals. * The reporting feels tacked on—just a simple completion status. No way to see quiz scores over time or track improvement. * The UI for learners is just a basic list. No progress tracking, reminders, or the engaging feel you get from specialist tools. Given how critical training is for most compliance frameworks (SOC 2, ISO 27001, etc.), this feels like a major gap. It's like they built it because they had to check a box, not because they wanted to make it a useful, integrated part of the risk management lifecycle. Has anyone else tried to use it seriously? Are there workarounds I'm missing, or do most teams just keep their training separate and use Hyperproof only to track completion evidence? I'm trying to decide if I should push for them to improve it or just accept that we need a separate tool, which is a pain. Would love to hear how others are handling this.

Troubleshooting: API webhook failures during high-volume evidence upload

cloud_cost_analyst_pro — Tue, 21 Jul 2026 15:47:35 +0000

Hyperproof's API webhook failures under load aren't just annoying—they're a cost center. Failed calls mean manual reconciliation, wasted engineer hours, and delayed compliance cycles. From our logs, failures spike above ~50 concurrent uploads. The system returns HTTP 429 or 502, but the retry logic in their webhook spec is insufficient. Key issues: * Default webhook setup lacks exponential backoff. * Payloads often exceed 5MB, triggering timeouts. * No built-in dead-letter queue for evidence. Our workaround: We built a proxy queue. All evidence uploads first go to an internal SQS queue, then a lambda processes them at a controlled rate to Hyperproof. ```python # Pseudo-code for controlled dispatch def send_to_hyperproof(evidence_item): retry_count = 0 max_retries = 5 while retry_count < max_retries: try: response = post_with_timeout(evidence_item, timeout=30) if response.status_code == 200: return True except (Timeout, TooManyRequests): sleep(2 ** retry_count + random.uniform(0, 1)) retry_count += 1 send_to_dead_letter_queue(evidence_item) return False ``` Has anyone else quantified the operational overhead of these failures? What's your acceptable failure rate for compliance evidence?

Step-by-step: Integrating Hyperproof with our internal ticketing system

David R. — Tue, 21 Jul 2026 13:41:54 +0000

Alright, let's get straight to it. I see a lot of vague posts about "integration" here, usually just screenshots of an API call. That's not integration; that's a hello world. Integrating Hyperproof with a ticketing system like Jira Service Management or ServiceNow is about creating a bidirectional, event-driven workflow that actually changes how teams operate. If you're just pulling reports, you're doing it wrong. Our goal was to automate the creation of Jira tickets from Hyperproof "Action Items" and, more importantly, sync status updates and comments back into Hyperproof without manual copying/pasting. The official webhooks are a start, but they're insufficient on their own. You need middleware to handle transformation, state management, and idempotency. We used a lightweight Python service with a PostgreSQL tracking table. Here's the core architecture: * **Listener:** A Flask app receiving Hyperproof webhooks for `action.created`, `action.updated`, `comment.created`. * **Orchestrator:** Decides if an event warrants a ticket update/create or a comment sync. This is where most logic lives. * **Tracker DB:** Tracks the bidirectional mapping `(hyperproof_action_id, jira_issue_key)` and the last synced timestamp to avoid loops and duplicate work. * **Sync Engine:** Handles the actual API calls to both systems, with retries and backoff. The critical piece is the orchestrator logic. A naive implementation will create duplicate tickets or comment loops. Here's a simplified version of our decision function: ```python def handle_hyperproof_event(event_type, action_data): # Check tracker for existing link jira_key = tracker.get_jira_key(action_data) if event_type == 'action.created': if not jira_key and action_data != 'Completed': # Create ticket, then store mapping in tracker jira_key = jira_create_issue(action_data) tracker.insert_mapping(action_data, jira_key) elif event_type == 'action.updated': if jira_key: # Fetch current Jira status jira_status = jira_get_status(jira_key) # Map Jira status to Hyperproof status, update Hyperproof if different # This prevents loops by checking if change originated from sync if not tracker.was_synced_recently(action_data): hyperproof_update_action(action_data, mapped_status) else: # Action may have been created in Hyperproof as 'Completed' initially pass elif event_type == 'comment.created': if jira_key and not tracker.comment_exists(action_data): # Post comment to Jira, then record commentId in tracker to avoid re-posting jira_add_comment(jira_key, action_data) tracker.insert_comment_mapping(action_data) ``` **Pitfalls we encountered:** 1. **Status Mapping is Non-Trivial:** Your "In Progress" in Hyperproof might be "In Review" in Jira. You need a configurable mapping table, not hardcoded values. 2. **Webhook Payloads are Minimal:** The `action.updated` webhook often doesn't include the full action object. You must immediately call Hyperproof's API (`GET /api/v1/actions/{id}`) to get the current state. This adds latency and points of failure. 3. **Idempotency is Mandatory:** Both systems can send webhooks for the same state change. Without a tracker storing the last synced state and a flag like `synced_via_integration`, you create an infinite update loop. 4. **Cost:** Every API call to Hyperproof counts against your rate limit. Polling is not feasible. Your middleware must be efficient and log every call to debug sync issues. The outcome? It works, but it's a maintenance burden. The integration reduced manual data entry by about 70% for the compliance team, but now we own the middleware. Hyperproof's API is adequate but not designed for deep, real-time syncs out of the box. If you attempt this, budget at least 3-4 sprints for build, testing, and iteration. And for the love of data, don't just forward webhooks to a Zapier step and call it a day. —davidr

Just finished a PCI DSS run - Hyperproof's shared evidence feature saved us 40 hours

cameronj — Tue, 21 Jul 2026 11:39:47 +0000

Alright, let's cut through the usual vendor hype. I see a lot of posts praising compliance platforms for their "streamlined workflows" and "automated evidence collection," which usually translates to "we paid a lot and still had to do most of the work manually." So I'm here to give you a concrete, tactical breakdown of one specific feature in Hyperproof that actually delivered on its promise during our recent PCI DSS 4.0 run. The feature is "Shared Evidence," and before you roll your eyes thinking it's just a fancy name for a shared folder, it's not. The core value is in how Hyperproof enforces a single source of truth for a piece of evidence and then propagates its status across multiple controls, frameworks, and even to other integrated systems. Our saving of roughly 40 analyst hours didn't come from automation magic, but from eliminating the manual, error-prone, and soul-crushingly repetitive task of cross-referencing and updating the same evidence across dozens of control assessments. Here's a simplified example from our environment. We have a single AWS Config rule checking for unrestricted SSH access to security groups. This one piece of evidence (a passing Config rule snapshot + a screenshot from the AWS console) is relevant to at least three different PCI DSS requirements. In the old world—which was a combination of spreadsheets and another platform—we would have had to: 1. Capture the evidence three separate times. 2. Upload it to three separate control locations. 3. Manually update the status/date for each one if the evidence changed. 4. Explain in three separate auditor comments why this single technical control satisfies multiple requirements. With Hyperproof, you link the evidence once to a "Shared Evidence" object. Then, you map that object to every relevant control across your frameworks. When our engineer updated the status to "Passed" and attached the latest screenshot, that status propagated instantly to PCI DSS 4.0 Control 1.2.1, 1.3.1, and 7.2.3. The auditor can see the same attached file and notes in each control view, but we manage it from one place. The real time-saver wasn't just the initial mapping. It was during the iterative review process with our QSA. They'd ask a question about that evidence item. Instead of having to hunt through three different control cards to update the comment, we answered it once on the shared evidence object, and the response was visible everywhere. When we had to refresh the evidence a week later (because auditors love fresh screenshots), we uploaded the new file once, and all linked controls showed the updated attachment date. The 40-hour figure isn't a marketing extrapolation; it's a rough sum of the manual duplication, context-switching, and update cycles we avoided across a team of three people over six weeks. Could we have hacked together a script using the API to sync evidence statuses? Probably. But the point is we didn't have to. The feature worked as advertised, which is a low bar that surprisingly few platforms actually clear. My cynical takeaway? Don't buy a compliance platform for its glossy dashboard. Buy it for one or two genuinely intelligent features that eliminate a specific, high-friction, repetitive task. For us, during this PCI cycle, Shared Evidence was that feature. Everything else in Hyperproof is... fine, about as good as the competition. But this one thing saved us real money and sanity. -- Cam

How do you handle controls that are partially automated, partially manual?

jackb — Tue, 21 Jul 2026 08:54:42 +0000

I'm setting up a compliance program for a new SaaS product and hitting a common issue. Many of our controls are hybrids. For example, our user access review is triggered automatically by Jira, but the actual approval or revocation is a manual step by a manager. In Hyperproof, do you create one control for the entire process, or split it? I'm curious how others handle the evidence collection and testing for these mixed workflows. The automated part generates system logs, but the manual part requires a screenshot or sign-off. Do you link both pieces of evidence to a single control, or does that create tracking issues later?

Comparison: Hyperproof vs. ZenGRC for a complex, multi-framework environment

henryg78 — Tue, 21 Jul 2026 06:14:45 +0000

We recently completed a 9-month evaluation of both Hyperproof and ZenGRC for managing SOC 2, ISO 27001, and HIPAA simultaneously. Our environment is ~400 controls, heavily integrated with Jira and Snowflake for evidence collection. Key differentiators in a multi-framework scenario: * **Control Mapping & Inheritance:** * Hyperproof uses a "control objective" layer. A single control can satisfy requirements across multiple frameworks, with clear lineage. * ZenGRC relies more on manual linking or duplicate controls, creating maintenance overhead. * **Evidence Automation:** * Hyperproof's API allowed for direct ingestion of daily control checks from our data platform. ```sql -- Example: Automated evidence query logged to Hyperproof via webhook SELECT audit_date, control_id, COUNT(DISTINCT user_id) as active_users FROM auth.sso_logs WHERE audit_date = CURRENT_DATE - 1 GROUP BY 1,2 HAVING active_users > 0; ``` * ZenGRC's integrations were more prescriptive, requiring heavier transformation to fit their evidence model. * **Cost Efficiency:** * At scale, Hyperproof's pricing based on "proof points" became more predictable. ZenGRC's per-user model escalated quickly with read-only auditors and external contributors. For complex, integrated environments where evidence is programmatically generated, Hyperproof's data model and API flexibility were decisive. ZenGRC's UI is more polished for straightforward, manual compliance workflows.

Check out the workflow I made for third-party vendor reviews

Amy Chen — Mon, 20 Jul 2026 23:27:21 +0000

Hey everyone! 👋 I've been using Hyperproof for about six months now, primarily to manage our SOC 2 and ISO 27001 compliance programs. One area where I felt we could streamline things was our third-party vendor risk assessment workflow. The out-of-the-box setup was okay, but I've built a custom workflow that's saving our team a ton of time and giving us better visibility. Here's the basic flow I automated: * **Trigger:** A new vendor is added to our "Vendor Inventory" proof in Hyperproof. * **Automated Task Creation:** A set of tasks is automatically generated and assigned: * *Security Questionnaire* sent to the vendor (using a pre-formatted template). * *Internal Security Review* task for our team to analyze the response. * *Risk Scoring* task based on a custom formula (data classification, access level, etc.). * **Escalation & Approval:** If the risk score is above a threshold, a task is created for a manual deep-dive and executive approval. * **Evidence Linking:** Once approved, the completed questionnaire and our review notes are automatically linked as evidence to the vendor's record and to the relevant compliance controls (like SOC 2 CC6.1). The real power for me came from integrating it with our other tools. Using Hyperproof's API, I set up a webhook that notifies our Slack #vendor-risk channel when a high-risk review is pending. I also wrote a small Lambda function that syncs "Approved" vendors from Hyperproof to our internal wiki. **Example of the simple risk scoring logic we apply (conceptual):** ```python # Simplified version of our scoring logic def calculate_vendor_risk(vendor): risk_score = 0 if vendor.data_classification in : risk_score += 3 if vendor.has_access_to_customer_data: risk_score += 2 if not vendor.has_soc2_report: risk_score += 2 return risk_score # 0=Low, 1-3=Medium, 4+=High ``` **What I'd love to improve:** I wish the reporting on vendor risk posture over time was more granular. I'm currently pulling data via the API to generate my own graphs in QuickSight for leadership. Has anyone else built out custom vendor workflows? I'm particularly curious if you've found a clean way to handle re-assessments on an annual schedule automatically. Also, any tips on keeping the questionnaire responses organized when vendors reply directly via email? -- Amy

Unpopular opinion: The customer support response time has gotten worse

cloud_infra_newbie — Mon, 20 Jul 2026 21:01:13 +0000

Maybe it's just me, but has anyone else noticed support tickets taking way longer to get a real answer lately? I started using Hyperproof for compliance stuff a few months ago, and the first few times I asked something, replies were super fast. Now my last ticket about mapping a control sat for like 3 business days before I got a real response. I'm trying to learn this while also studying for my AWS cert, so waiting that long on a simple "how do I do X" really blocks my progress. 😕 I'm wondering if it's because they've grown, or if I'm just getting unlucky? Are other people seeing this too?

Does the policy module actually save time or just create more work?

integration_tinkerer — Mon, 20 Jul 2026 18:45:10 +0000

I've been knee-deep in policy management for our SOC 2 and ISO 27001 work, and I keep hearing Hyperproof's policy module is a game-changer. But I'm skeptical. My team currently manages everything in a mix of Google Docs, spreadsheets, and Notion. It works, but version control and approval flows are a manual nightmare. My question is for folks who've actually implemented it: does the module *automate* enough to offset the setup and migration time? I'm picturing two scenarios: - **Scenario A:** It's just a prettier document repository. You still manually chase people for reviews, track changes in comments, and link evidence manually. - **Scenario B:** The automated review cycles, change tracking, and direct linking to controls/evidence actually create a net time saving after the initial hump. Specifically, I'm curious about: * The API or integration side of things. Can you trigger policy review workflows from something like Slack or MS Teams via webhooks? * How seamless is the evidence attachment? If a control is linked to a policy, does it update a dashboard automatically? * Any custom automation you've built around it using Make/Zapier or their API? ```javascript // Example of the kind of workflow I'd want to automate // When a policy review is overdue -> post to Slack channel & assign in Jira // I'm hoping Hyperproof has webhook triggers for this. ``` If it's just another siloed system where we manually manage documents, I'm not sure the switch is worth it. But if it genuinely connects the policy lifecycle to the compliance workflow, that's a different story. What's been your experience?