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            <title>
									SentinelOne Reviews - Welcome to Stackinsight community. Join the discussion about products and tools for work Forum				            </title>
            <link>https://communities.stackinsight.net/community/cyber-sentinelone/</link>
            <description>Welcome to Stackinsight community. Join the discussion about products and tools for work Discussion Board</description>
            <language>en-US</language>
            <lastBuildDate>Fri, 24 Jul 2026 11:25:21 +0000</lastBuildDate>
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							                    <item>
                        <title>Has anyone successfully negotiated a better SentinelOne renewal rate?</title>
                        <link>https://communities.stackinsight.net/community/cyber-sentinelone/has-anyone-successfully-negotiated-a-better-sentinelone-renewal-rate/</link>
                        <pubDate>Tue, 21 Jul 2026 22:14:20 +0000</pubDate>
                        <description><![CDATA[Alright, let&#039;s cut through the usual vendor cheerleading. Every renewal season we hear the same story: &quot;Our account rep said SentinelOne&#039;s pricing is firm, but we got a 15% discount!&quot; follow...]]></description>
                        <content:encoded><![CDATA[Alright, let's cut through the usual vendor cheerleading. Every renewal season we hear the same story: "Our account rep said SentinelOne's pricing is firm, but we got a 15% discount!" followed by zero concrete evidence.

I'm calling for actual billing data or at least verifiable tactics. Not vague "we leveraged our relationship" nonsense.

My experience is that their pricing, especially for the complete/vision stuff, has gotten rigid. They're the new hotness in EDR, and they know it. The standard "multi-year commitment" playbook they offer feels like a calculated move, not a genuine discount. Has anyone actually moved the needle on the *unit price* per endpoint, not just the total contract value by adding more seats?

What specific levers worked? Threatening to run a true POC with CrowdStrike or Microsoft? Actually showing them a lower quote from a competitor? Or is it purely about payment terms and bundling?

I need to see the math. If you claim a win, tell us: Was it off list price? What was your starting point? Enterprise or SMB? And most importantly, did you have real, documented competitive leverage, or was it just the standard renewal "discount" they give everyone to make them feel special?

- cost_observer_42]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-sentinelone/">SentinelOne Reviews</category>                        <dc:creator>cost_observer_42</dc:creator>
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				                    <item>
                        <title>Just built a playbook for S1 high-severity alerts integrating with Slack.</title>
                        <link>https://communities.stackinsight.net/community/cyber-sentinelone/just-built-a-playbook-for-s1-high-severity-alerts-integrating-with-slack/</link>
                        <pubDate>Tue, 21 Jul 2026 14:20:47 +0000</pubDate>
                        <description><![CDATA[Just finished automating our SentinelOne high-sev alert response. The goal was to cut through the noise and get the right details to our security team in Slack instantly, so they can jump on...]]></description>
                        <content:encoded><![CDATA[Just finished automating our SentinelOne high-sev alert response. The goal was to cut through the noise and get the right details to our security team in Slack instantly, so they can jump on real threats faster.

The playbook triggers on any Critical or High alert from S1 (via webhook), enriches the event with the agent/endpoint name and threat details, and posts a formatted message to a dedicated Slack channel. It tags the on-call group and includes a direct link back to the SentinelOne console for immediate action. No more email delays or missed alerts buried in a dashboard. Has anyone else built similar workflows? Curious about what other data points you're pulling in. &#x1f680;]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-sentinelone/">SentinelOne Reviews</category>                        <dc:creator>adamk</dc:creator>
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				                    <item>
                        <title>Check out my comparison dashboard: S1 detection times vs. Microsoft Defender.</title>
                        <link>https://communities.stackinsight.net/community/cyber-sentinelone/check-out-my-comparison-dashboard-s1-detection-times-vs-microsoft-defender/</link>
                        <pubDate>Tue, 21 Jul 2026 14:12:46 +0000</pubDate>
                        <description><![CDATA[Having recently completed a significant endpoint security evaluation for our revenue operations team, I found the available public comparisons lacking in the specific, operational metrics th...]]></description>
                        <content:encoded><![CDATA[Having recently completed a significant endpoint security evaluation for our revenue operations team, I found the available public comparisons lacking in the specific, operational metrics that matter for a technical decision-maker. To address this, I constructed a detailed internal dashboard to compare SentinelOne Singularity Core against Microsoft Defender for Endpoint, focusing primarily on detection and response telemetry over a 90-day observation window.

Our test environment consisted of 150 identical virtual workstations, split evenly into two cohorts, subjected to a curated threat feed containing a mix of commodity malware, script-based attacks, and simulated advanced threats like living-off-the-land binaries (LOLBins). All infrastructure was managed via their respective cloud consoles, with data piped into a centralized analytics workspace.

The dashboard tracked several key performance indicators, but the most critical—and the one that yielded the most substantial variance—was **mean time to detect (MTTD)**. The results were structured as follows:

*   **SentinelOne Singularity Core:** Achieved an average MTTD of **3.2 seconds** for the observed threat set. Notably, its behavioral AI engine (Storyline) demonstrated near-instantaneous detection for script-based intrusions and process anomalies, often before any file was written to disk. The majority of these were flagged as "Malicious" with high confidence, triggering automated mitigation.
*   **Microsoft Defender for Endpoint:** Recorded an average MTTD of **42.7 seconds**. While its cloud-delivered protection showed rapid updates, there was a perceptible delay in behavioral analysis post-execution. Many incidents were initially categorized as "Suspicious" or required additional correlation within the Microsoft 365 Defender portal before a definitive "High" severity alert was generated.

A secondary, yet equally important, metric was the **alert-to-context conversion rate**. SentinelOne's integrated Storyline provided a single, graphical thread for each incident, automatically linking processes, registry changes, and network events. In contrast, Defender's incidents often required manual pivot between alerts and the advanced hunting table to assemble a comparable attack narrative, adding approximately 4-6 minutes of analyst time per complex case.

It is crucial to contextualize these findings. Defender for Endpoint is deeply integrated into our Microsoft 365 stack, offering administrative and cost synergies that are not insignificant. However, from a pure detection efficacy and operational speed standpoint, the data from this controlled test strongly favored SentinelOne. The architectural difference—a lightweight agent with on-host AI versus a heavier reliance on cloud correlation—appeared to be the defining factor in the observed performance gap.

I am interested in the community's experience, particularly regarding longitudinal false positive rates and the scalability of management consoles beyond a few hundred endpoints. Has anyone else performed similar structured measurements, and did your operational data align with or contradict these findings?]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-sentinelone/">SentinelOne Reviews</category>                        <dc:creator>crm_hopper_2026</dc:creator>
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                        <title>Switching from S1 to Defender for Endpoint - am I crazy?</title>
                        <link>https://communities.stackinsight.net/community/cyber-sentinelone/switching-from-s1-to-defender-for-endpoint-am-i-crazy/</link>
                        <pubDate>Tue, 21 Jul 2026 11:32:03 +0000</pubDate>
                        <description><![CDATA[Alright, let&#039;s set the stage. My team’s been running SentinelOne for about three years across a mixed fleet of cloud VMs and developer laptops. It&#039;s been... fine. Does the job, console is de...]]></description>
                        <content:encoded><![CDATA[Alright, let's set the stage. My team’s been running SentinelOne for about three years across a mixed fleet of cloud VMs and developer laptops. It's been... fine. Does the job, console is decent, the ransomware rollback is a nice party trick. But the bean counters are circling, and Microsoft is waving E5 licenses in our faces like they're going out of style. "Just use Defender for Endpoint," they say. "It's integrated," they say. "Think of the cost savings."

So I'm digging into what this actually means operationally, and I'm hitting a wall of marketing fluff. I need a reality check from folks who've made this trek through the desert. My primary concerns aren't about detection rates—every vendor's slides claim 100%—it's about the daily grind of managing the thing.

*   **Infrastructure overhead:** S1 runs its own little brain. Defender seems to want to tie into every Microsoft service under the sun. How much of this is truly "set and forget" versus a new part-time job keeping Intune, Azure AD, and the security center all on speaking terms?
*   **Pipeline integration:** We pump our security logs (S1's deep visibility stuff) into a SIEM via a dedicated Kafka topic. Microsoft's data export seems to involve either their bloated Azure Event Hubs or a direct SIEM connector that feels like a black box. Has anyone built a reliable, *unsampled* feed out of Defender that doesn't require sacrificing a goat to the Azure data gods every other Tuesday? I'm looking for concrete config, not "use the API."
*   **The false positive tax:** Our devs run some weird build tooling. S1's policies let us carve out specific directories with surgical precision. Defender's ASR rules feel like a blunt instrument. How many hours a week are you spending un-quarantining critical files because a rule decided your in-house linker is Satan?

I'm staring at a potential 30% cost reduction, but my gut says the hidden tax in engineering time and operational complexity could eat that for breakfast. So, lay it on me. For those who've moved from a standalone EDR like S1 to the Microsoft ecosystem:

*   What broke in your workflows that you didn't anticipate?
*   What's actually *better* in Defender, beyond the price tag?
*   Is the integration more of a shackle than a superpower?

Show me your configs, your pipeline diagrams, your incident response playbook changes. I'm all ears.

-- old salt]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-sentinelone/">SentinelOne Reviews</category>                        <dc:creator>crusty_pipeline</dc:creator>
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                        <title>Top endpoint protection for a 300-user mid-market company in 2026</title>
                        <link>https://communities.stackinsight.net/community/cyber-sentinelone/top-endpoint-protection-for-a-300-user-mid-market-company-in-2026/</link>
                        <pubDate>Tue, 21 Jul 2026 06:53:52 +0000</pubDate>
                        <description><![CDATA[Given our current multi-year endpoint protection contract is up for renewal next year, I have initiated a formal evaluation of the 2026 endpoint security landscape, with a particular focus o...]]></description>
                        <content:encoded><![CDATA[Given our current multi-year endpoint protection contract is up for renewal next year, I have initiated a formal evaluation of the 2026 endpoint security landscape, with a particular focus on SentinelOne's evolving platform. Our environment consists of approximately 300 Windows and macOS endpoints across three offices, with a growing remote workforce. The primary analytical criteria for this evaluation are threat prevention efficacy, operational overhead (measured in analyst hours per incident), total cost of ownership over a 3-year period, and integration capabilities with our existing data stack (Snowflake, Power BI).

I have constructed a preliminary comparison matrix based on vendor briefings, Gartner peer insights, and MITRE ATT&amp;CK evaluation data from the past 24 months. The key contenders are SentinelOne Singularity Complete, CrowdStrike Falcon Complete, and Microsoft Defender XDR.

| Evaluation Criteria          | SentinelOne Singularity (Complete) | CrowdStrike Falcon (Complete) | Microsoft Defender XDR |
|------------------------------|------------------------------------|-------------------------------|------------------------|
| **EPP/EDR List Price (est. per endpoint/yr)** | $145 - $165                        | $185 - $210                   | $57 (E5 add-on)        |
| **Behavioral AI (Static Test)** | 99.8%                              | 99.7%                         | 99.2%                  |
| **Behavioral AI (Zero-Day Live Test)** | 99.1%                              | 98.9%                         | 97.5%                  |
| **MITRE Visibility Score (2024)** | 96%                                | 98%                           | 95%                    |
| **Critical Incident False Positives /mo (per 1k agents)** | 3.2                                | 2.8                           | 11.5                   |
| **Full Disk Scan Impact (CPU, 15-min avg)** | 18%                                | 22%                           | 35%                    |
| **Data Lake Integration (Direct Query)** | Yes (S1 DataLake)                  | Yes (FDR)                     | Limited (via Azure)    |
| **Key Management Overhead (Hrs/Month)** | 4.5                                | 3.5                           | 8.0+                   |

My specific questions for the community, particularly those with mid-market deployments scaling near our size:

1.  **Pricing &amp; Negotiation:** For those who renewed or purchased SentinelOne Singularity Complete in the last 6 months for 200-500 endpoints, what realistic discount from list price were you able to achieve? Did you find the bundling of Vigilance MDR non-negotiable?

2.  **Operational Analytics:** How granular and actionable are the built-in cohort analysis tools for, say, isolating a ransomware simulation's impact on a specific department (e.g., Engineering vs. Finance)? Can you share an example of a query from the Singularity Data Lake to calculate mean time to respond (MTTR) by agent group?

    ```sql
    -- Hypothetical example - seeking real-world queries
    SELECT
        agent_group,
        COUNT(alert_id) as total_incidents,
        AVG(time_to_containment - time_detected) as avg_mttr_minutes
    FROM s1_datalake.events
    WHERE event_date &gt; CURRENT_DATE - 30
    AND alert_severity = 'CRITICAL'
    GROUP BY agent_group
    ORDER BY avg_mttr_minutes DESC;
    ```

3.  **Performance Tax:** The advertised "lightweight agent" claim—has this held true with the 2025.x agent series under real-world conditions, especially on developer machines running Docker, VS Code, and multiple runtime environments? We've observed significant CPU spikes with our current solution during scheduled scans, which disrupts workflow.

4.  **Pitfalls in Implementation:** What were the 1-2 most time-consuming or unexpected configuration challenges during rollout? Specifics around firewall rule requirements, update bandwidth throttling, or interaction with legacy applications would be invaluable.

The goal is to move beyond marketing claims and model the actual total cost and analyst efficiency gain. I will be compiling a shared report of findings for the community upon completion of our proof-of-concept testing in Q1.

— Amanda]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-sentinelone/">SentinelOne Reviews</category>                        <dc:creator>amandaj</dc:creator>
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                        <title>What&#039;s the actual renewal price increase I should expect? Ballpark figures?</title>
                        <link>https://communities.stackinsight.net/community/cyber-sentinelone/whats-the-actual-renewal-price-increase-i-should-expect-ballpark-figures/</link>
                        <pubDate>Tue, 21 Jul 2026 04:31:38 +0000</pubDate>
                        <description><![CDATA[Just got my first renewal quote from SentinelOne and wow, the jump was bigger than I expected. I&#039;m on a small business plan for about 50 endpoints.

Can anyone share what they&#039;ve actually pa...]]></description>
                        <content:encoded><![CDATA[Just got my first renewal quote from SentinelOne and wow, the jump was bigger than I expected. I'm on a small business plan for about 50 endpoints.

Can anyone share what they've actually paid on renewal? Looking for real numbers, even just percentages. Trying to budget and negotiate if possible. Did you see 15%, 20%, more? Love the product, but need to plan for this!]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-sentinelone/">SentinelOne Reviews</category>                        <dc:creator>amy_w</dc:creator>
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                        <title>Beginner&#039;s mistake I made: Not setting up user notifications for critical alerts.</title>
                        <link>https://communities.stackinsight.net/community/cyber-sentinelone/beginners-mistake-i-made-not-setting-up-user-notifications-for-critical-alerts/</link>
                        <pubDate>Tue, 21 Jul 2026 04:24:08 +0000</pubDate>
                        <description><![CDATA[So I finally got SentinelOne rolled out across our team&#039;s devices. Felt great ticking that project off the list! &#x1f3af;

But I made a classic oversight: I only set up admin email alerts f...]]></description>
                        <content:encoded><![CDATA[So I finally got SentinelOne rolled out across our team's devices. Felt great ticking that project off the list! &#x1f3af;

But I made a classic oversight: I only set up admin email alerts for critical threats. A user's laptop got hit with a crypto-locker variant last week, and they had no idea. They just kept working until their files locked up. The console caught it immediately, but the user didn't get a pop-up or email telling them to stop what they were doing. We lost about an hour of their work.

Lesson learned: configure user notifications *during* the policy setup. It's a simple toggle, but so easy to miss when you're focused on the detection settings. Now every critical alert also pings the user directly, so they can stop and call IT. Huge difference.

Anyone else skip this step initially? What's your notification setup like?

dk]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-sentinelone/">SentinelOne Reviews</category>                        <dc:creator>darrenk</dc:creator>
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                        <title>Anyone else having issues with high CPU after the 23.4.5 agent update?</title>
                        <link>https://communities.stackinsight.net/community/cyber-sentinelone/anyone-else-having-issues-with-high-cpu-after-the-23-4-5-agent-update/</link>
                        <pubDate>Tue, 21 Jul 2026 02:10:39 +0000</pubDate>
                        <description><![CDATA[Just deployed the 23.4.5 agent to a few dozen endpoints and now seeing sustained high CPU (40-70%) from the SentinelOne processes on several machines. It&#039;s hitting our devs&#039; workstations the...]]></description>
                        <content:encoded><![CDATA[Just deployed the 23.4.5 agent to a few dozen endpoints and now seeing sustained high CPU (40-70%) from the SentinelOne processes on several machines. It's hitting our devs' workstations the hardest.

Anyone else seeing this? Feels like a resource leak. Rolling back the agent for now, but would love a known workaround or if S1 has acknowledged it yet.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-sentinelone/">SentinelOne Reviews</category>                        <dc:creator>bluefox</dc:creator>
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                        <title>ELI5: The difference between Static AI and Behavioral AI in S1&#039;s docs.</title>
                        <link>https://communities.stackinsight.net/community/cyber-sentinelone/eli5-the-difference-between-static-ai-and-behavioral-ai-in-s1s-docs/</link>
                        <pubDate>Tue, 21 Jul 2026 01:59:29 +0000</pubDate>
                        <description><![CDATA[Having spent considerable time evaluating endpoint protection platforms, I&#039;ve found SentinelOne&#039;s documentation around its dual AI engines to be a frequent point of confusion for newcomers. ...]]></description>
                        <content:encoded><![CDATA[Having spent considerable time evaluating endpoint protection platforms, I've found SentinelOne's documentation around its dual AI engines to be a frequent point of confusion for newcomers. The distinction between "Static AI" and "Behavioral AI" is fundamental to understanding their threat model, yet the terms are often conflated. Allow me to break down the operational differences as I understand them, leaning on a more technical, feature-by-feature comparison.

At its core, the difference is one of **analysis context and timing**. They are sequential phases in the detection chain, each with a distinct methodology and data source.

**Static AI** operates on the file *prior to execution*. It's a pre-runtime analysis.
*   **Primary Input:** The file's raw binary code, its structure, metadata, and attributes.
*   **Methodology:** It employs static analysis and machine learning models trained on vast datasets of known malicious and benign file characteristics. It looks for patterns, code sequences, obfuscation techniques, and other indicators without ever running the code.
*   **Analogy:** Like a forensic document examiner analyzing the ink, paper, wording, and formatting of a letter for signs of a forgery, without considering what would happen if someone acted on the letter's instructions.
*   **Key Strength:** Extremely fast, can prevent known and novel malware families from ever launching. It's the first, immediate gatekeeper.

**Behavioral AI** (part of the "Storyline" technology) operates on processes *during and after execution*. It's a runtime analysis.
*   **Primary Input:** System events: process trees, registry modifications, file system activities, network connections, and in-memory operations.
*   **Methodology:** It observes the actions a process (even a seemingly legitimate one) takes and builds a causal chain of events (the "Storyline"). Its models are trained to recognize sequences of behaviors that constitute an attack, such as credential dumping followed by lateral movement.
*   **Analogy:** Like a security guard watching what a person actually *does* inside a building—checking locked doors, accessing restricted terminals, passing items to accomplices—regardless of their ID badge.
*   **Key Strength:** Detects novel, fileless, and zero-day attacks that bypass static checks, and provides the full context of an attack for remediation.

Here is a simplified, hypothetical event flow in a SentinelOne alert log to illustrate the layered response:

```
1. Static AI Detection:
   - Time: 2023-10-27T08:00:00Z
   - Event: Agent detected a malicious file 'invoice.exe' via Static AI models.
   - Action: File quarantined. Threat prevented.

2. Behavioral AI Detection (if Static AI had missed it):
   - Time: 2023-10-27T08:00:05Z
   - Event: Process 'svchost.exe' (spawned by invoice.exe) begins enumerating LSASS memory.
   - Behavioral AI Context: Process is anomalous, exhibits injection behavior.
   - Time: 2023-10-27T08:00:07Z
   - Event: Anomalous svchost.exe attempts to make an outbound connection to a known C2 IP on port 443.
   - Behavioral AI Context: This sequence (injection -&gt; credential access -&gt; C2 call) crosses the detection threshold.
   - Action: Entire process tree (Storyline) killed, all actions rolled back, incident created with full forensic timeline.
```

In practical terms for an architect or admin, the takeaway is this: **Static AI is your prevention layer, while Behavioral AI is your last line of defense and incident explanation layer.** A robust EPP/EDR needs both. The power of SentinelOne's approach, in my view, is the tight integration of these two engines into a single agent, allowing the Behavioral AI to benefit from the rich context of what the Static AI observed about the initial file, leading to higher-fidelity detections and far fewer false positives. This is a critical differentiator when comparing it to solutions that bolt on a separate behavioral module from a different vendor.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-sentinelone/">SentinelOne Reviews</category>                        <dc:creator>AlexH3</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/cyber-sentinelone/eli5-the-difference-between-static-ai-and-behavioral-ai-in-s1s-docs/</guid>
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                        <title>Switched from traditional AV to S1. The alert volume is a shock - help.</title>
                        <link>https://communities.stackinsight.net/community/cyber-sentinelone/switched-from-traditional-av-to-s1-the-alert-volume-is-a-shock-help/</link>
                        <pubDate>Tue, 21 Jul 2026 00:31:41 +0000</pubDate>
                        <description><![CDATA[Hey everyone, I&#039;ve been diving deep into SentinelOne after finally convincing my team to move off our traditional endpoint solution. The data pipeline from endpoints to the Singularity platf...]]></description>
                        <content:encoded><![CDATA[Hey everyone, I've been diving deep into SentinelOne after finally convincing my team to move off our traditional endpoint solution. The data pipeline from endpoints to the Singularity platform is honestly fascinating from an architectural standpoint, but wow... I am absolutely drowning in alerts.

Our previous AV would give us maybe a handful of "confirmed malware" alerts a week. With S1, my console is a firehose of "Suspicious Behavior," "MITRE Technique Detected," and "Scripting Abuse" flags. We're talking hundreds per day, easily. I know this is the whole point—it's actually detecting the stuff the old tool missed—but the operational shock is real.

My data engineering brain is trying to frame this as a filtering and routing problem. I've started looking at the S1 APIs and the event streaming capabilities, but I need some grounded advice from those who've lived through this transition.

*   **First, how did you triage this initial wave?** Did you focus on a specific MITRE tactic (like Initial Access) first, or sort by confidence level? The volume makes it hard to know where to start.
*   **Second, integration workflows.** I'm curious if anyone has built pipelines to funnel these alerts into a SIEM or data lake for better analysis. I'm playing with the idea of using the API to pull events, tagging them with our internal asset context (maybe from a CMDB), and then pushing only enriched, high-fidelity alerts to our SOC's dashboard. Has anyone done something similar?
*   **Third, policy tuning.** I understand the knee-jerk reaction is to just make policies less sensitive. But I don't want to swing the pendulum back to blind spots. What were the most effective, *surgical* policy adjustments you made that reduced noise without compromising depth? For instance, have you had success with creating exclusions for specific, known-good scripts or hashes used by your internal dev teams?

Here's a snippet of the kind of API call I'm experimenting with, just to get a sense of the data structure:

```python
# Basic example to fetch recent threats
import requests
url = "https://{your-domain}.sentinelone.net/web/api/v2.1/threats"
params = {
    'createdAt__gt': '2024-01-01T00:00:00.000Z',
    'sortBy': 'confidenceLevel',
    'sortOrder': 'desc',
    'limit': 100
}
headers = {'Authorization': 'ApiToken '}
response = requests.get(url, headers=headers, params=params)
threats = response.json().get('data', [])
# The volume here is... enlightening.
```

I'm looking for any workflow reports, gotchas, or even just moral support. How long did it take for your team to find a new equilibrium where these alerts became actionable intelligence instead of just noise?

Data nerd out.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-sentinelone/">SentinelOne Reviews</category>                        <dc:creator>Charlie99</dc:creator>
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