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  "sourcesContent": ["import{jsx as e,jsxs as t}from\"react/jsx-runtime\";import*as i from\"react\";export const richText=/*#__PURE__*/t(i.Fragment,{children:[/*#__PURE__*/e(\"h3\",{children:\"Streamlining Security Operations with Advanced Log Management\"}),/*#__PURE__*/e(\"p\",{children:\"For a company like Snyk, committed to developing fast and staying secure, achieving comprehensive visibility across its infrastructure is paramount. One of Snyk's primary challenges was maintaining complete coverage across its expanding security stack. Panther's flexible ingestion capabilities allowed the team to quickly onboard new log sources.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})}),/*#__PURE__*/t(\"blockquote\",{children:[/*#__PURE__*/e(\"p\",{children:\"\\\"My favorite part about Panther is how fast you can onboard any log source. Even if there's no native integration, I can throw the logs in an S3 bucket, and it will create a schema or parser for them, which is amazing. It takes a few hours, and you have a log source onboarded, in the traditional SIEM world, it would take weeks or months.\u201D \"}),/*#__PURE__*/e(\"p\",{children:\"Filip Stojkovski, Staff Security Engineer\"})]}),/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})}),/*#__PURE__*/e(\"p\",{children:\"The Panther team helped to successfully implement custom integrations, including CircleCI logs, a common platform in security stacks that doesn\u2019t enable easy audit log exports. This capability proved essential for maintaining comprehensive security coverage as their infrastructure evolves.\"}),/*#__PURE__*/e(\"h3\",{children:\"Intelligent Alerting and Noise Reduction\"}),/*#__PURE__*/e(\"p\",{children:\"The Snyk team identified alert fatigue as a critical challenge for their security operations. They needed a strategic approach to separate signal from noise without compromising detection coverage. Using Panther's advanced filtering and detection engineering capabilities, Snykembarked on a comprehensive alert optimization project to transform their operations.\"}),/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})}),/*#__PURE__*/t(\"blockquote\",{children:[/*#__PURE__*/e(\"p\",{children:'\"Managing all the detections and alert triage was one of the first projects I did with Panther. We had too many detections and too many alerts. We needed to figure out which alerts were actionable, so we went through them, applying the correct filters to trigger only on specific patterns. By figuring out the baseline of what\\'s normal versus abnormal behavior, we reduced our alert volume by around 70%.\" '}),/*#__PURE__*/e(\"p\",{children:\"Filip Stojkovski, Staff Security Engineer\"})]}),/*#__PURE__*/e(\"p\",{children:/*#__PURE__*/e(\"br\",{className:\"trailing-break\"})}),/*#__PURE__*/e(\"p\",{children:\"The team leveraged Panther's correlation capabilities to chain multiple events, creating more sophisticated detection mechanisms that reduced false positives while maintaining high-fidelity threat detection. This approach proved particularly effective for identifying potentially malicious activities across their cloud infrastructure.\"}),/*#__PURE__*/e(\"h3\",{children:\"Enhanced Protection Through Custom Detection Engineering\"}),/*#__PURE__*/e(\"p\",{children:\"Snyk's security team established a comprehensive framework for detection engineering, ensuring thorough protection of their crown jewels and critical assets. Their approach includes:\"}),/*#__PURE__*/t(\"ul\",{children:[/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Verification of sufficient logging coverage for critical assets\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Development of meaningful, actionable detections\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Creation of detailed runbooks for investigation procedures\"})}),/*#__PURE__*/e(\"li\",{\"data-preset-tag\":\"p\",children:/*#__PURE__*/e(\"p\",{children:\"Implementation of automation for enrichment and response\"})})]}),/*#__PURE__*/e(\"p\",{children:\"The security team's technical expertise and Panther's Python-based detection capabilities enabled them to build sophisticated detection mechanisms tailored to their specific needs. 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Migrating to AWS necessitated a flexible security tool that matched their scale and budget needs and integrated quickly with AWS. Panther, a cloud-native solution built entirely on AWS, allowed them to centralize security operations in one platform and manage their production environment with complete visibility. Panther\u2019s scalable and flexible Lambda-based architecture simplified data onboarding with OOTB integrations for AWS services.\"}),/*#__PURE__*/e(\"p\",{children:\"Migrating hosting to AWS and deploying Panther empowered Spring Health to take ownership of its security posture without overextending their budget. 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We had to hunt down somebody from engineering who knew how to write a schema because their support team would not even help us.\u201D Cory Roop, Senior Manager of Security\\xa0\"]})}),/*#__PURE__*/e(\"h3\",{children:\"Accelerating Investigations\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Spring Health, the leading global mental health solution for employers and health plans, needed to find a new security solution. Their prior tool lacked extended data retention, which meant the security team depended on native logs outside their tools for investigations. This created investigation inefficiencies, often requiring hours of manual effort to piece together data from multiple log sources. The engineering team frequently flagged potential security issues, letting the security team know rather than vice versa.\"}),/*#__PURE__*/e(\"blockquote\",{children:/*#__PURE__*/e(\"p\",{children:\"\u201CThere are certain event types that require us to query three or four services to investigate, and it was very cumbersome. It used to take a couple of hours to verify an activity, but now it only takes a few minutes in Panther.\u201D Cory Roop, Senior Manager of Security\\xa0\"})}),/*#__PURE__*/e(\"p\",{children:\"With Panther, Spring Health adopted a data-lake-backed SIEM with 12 months of included hot storage. This extended retention eliminated blind spots and sped up investigations. 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These delayed detections created a \u201Crearview\u201D approach to security, making the security team reactive rather than proactive. This could have left Tealium potentially exposed to undetected, time-sensitive incidents.\"}),/*#__PURE__*/e(\"p\",{children:\"Panther\u2019s real-time detection capabilities enable Tealium to implement dynamic, immediate alerting. With rules and logic running in real-time, they can detect potential threats as they occur rather than after the fact. This change allows the team to apply real-time detection rules to analyze incoming data for potential security threats like breaches, failed logins, or anomalous user behavior.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"The shift to real-time detection reduced false positive alerts by up to 70%. This reduction allows the team to focus on meaningful alerts without spending hours filtering out noise, decreasing alert fatigue and enabling them to prioritize and address critical security concerns faster and more effectively.\"}),/*#__PURE__*/e(\"p\",{children:\"Unlocking the Ability to Identify Targeted \u201CNeedle in a Haystack\u201D Events\"}),/*#__PURE__*/t(\"blockquote\",{children:[/*#__PURE__*/e(\"p\",{children:\"As soon as we were on the platform and able to start writing in code that we were familiar with, it was easy to start customizing detections. There are a lot of great examples already written in the documentation, and that jumpstarted us. With the included detections, we were 80% of the way there. Then all we needed to do was apply what we knew about what we are looking for.\"}),/*#__PURE__*/e(\"p\",{children:\"Jason, Security Engineer\"})]}),/*#__PURE__*/e(\"p\",{children:\"Tealium\u2019s previous security tool lacked the precision and customization capabilities to identify particular \u201Cneedle-in-the-haystack\u201D events\u2014rare yet critical security signals hidden within a high volume of other data. For example, Tealium wanted to identify unusual login attempts on their IDP system that originated from unfamiliar IPs. Advanced detections like this were difficult or impossible to run on the previous platform, limiting the team\u2019s ability to detect specific targeted threats.\"}),/*#__PURE__*/e(\"p\",{children:\"Panther provides Tealium with correlation capabilities, allowing the team to create custom detections tailored to their unique needs. This flexibility empowers Tealium to design detection logic specific to their security environment, including monitoring unique events like failed logins from unusual locations and role-switching behaviors across cloud accounts. The correlation capabilities allow them to build complex, multi-layered detections to pinpoint risky activities otherwise lost within the more extensive data set. With Panther, Tealium\u2019s security team can deploy highly tuned detections to pick up on targeted events that their previous solution would have missed.\"}),/*#__PURE__*/e(\"h3\",{children:\"Moving Forward with Panther\"}),/*#__PURE__*/e(\"p\",{children:\"By migrating away from an inflexible and high-cost solution, Tealium\u2019s security team can now confidently and proactively protect its environment. With real-time detection and advanced correlation capabilities, the team has transformed its approach, monitoring more of its security data, gaining invaluable insights into potential threats, and addressing them before they escalate.\"})]});export const richText21=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"The previous solution\u2019s high costs capped data ingestion and limited visibility into security logs, creating blind spots to undetected threats\"})});export const richText22=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Only having access to scheduled queries put everything in their rearview and slowed down MTTD\"})});export const richText23=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"A lack of flexible detection logic and correlations in their prior solution made finding their targeted \u201Cneedles in the haystack\u201D difficult\"})});export const richText24=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Auto-scaling, cost-effective data ingestion\"})});export const richText25=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Real-time detection rules\"})});export const richText26=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Python-based detections with built-in correlation capabilities\"})});export const richText27=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Increased data ingested by 9X, expanding visibility into the environment\"})});export const richText28=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Reduced false positive alert volume in some severity classifications by as much as 70%\"})});export const richText29=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Deployed highly targeted, customized detections that monitor for niche but significant events, like a failed login on an IDP system that is also from an unknown IP vs. a prolific IP\"})});export const richText30=/*#__PURE__*/t(i.Fragment,{children:[/*#__PURE__*/t(\"blockquote\",{children:[/*#__PURE__*/e(\"p\",{children:\"Panther hits that sweet spot of being a tool and having all these useful features, but it\u2019s also a framework. It\u2019s the framework piece that gets underserved by every other tool I have tried, and that\u2019s what makes it genuinely different.\"}),/*#__PURE__*/e(\"p\",{children:\"Jeremy Mill, Varo\u2019s Senior Manager of Security Engineering\"})]}),/*#__PURE__*/e(\"h3\",{children:\"Outdated Existing Tech Stack Couldn\u2019t Deliver\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"The Varo security team needed help with their existing security tech: an ELK stack that took up too much time from the team without high-quality alert output. It demanded considerable overhead maintenance, and as an outdated solution, it lacked the comprehensive functionality of a proper SIEM platform, leading to a lot of manual effort. This led to their hunt for a modern SIEM to deploy that could reduce the burden of ongoing maintenance and liberate valuable security engineering time to focus on threat detection and response.\\xa0\"}),/*#__PURE__*/t(\"blockquote\",{children:[/*#__PURE__*/e(\"p\",{children:\"I want to focus on what we do, and we secure the bank. We don\u2019t run or manage the SIEM, so if we can have somebody else run the SIEM and focus on that for us, then that is the right decision every time.\"}),/*#__PURE__*/e(\"p\",{children:\"Jeremy Mill, Varo\u2019s Senior Manager of Security Engineering\"})]}),/*#__PURE__*/e(\"p\",{children:\"During a comprehensive SIEM search, Varo reviewed their existing tech stack against offerings like Panther and Datadog. The Varo team found that Datadog couldn\u2019t meet their needs for flexible data ingestion or their budget, and lacked core SIEM functionality. They ultimately opted to purchase and deploy Panther as their modern SIEM solution.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"With Panther\u2019s SaaS deployment requiring no overhead maintenance, Varo's security team could redirect their focus towards more critical tasks, particularly detection and response activities. By opting for a managed SIEM and freeing up engineering resources, Varo could better allocate their talents and expertise toward safeguarding their systems and data.\\xa0\"}),/*#__PURE__*/e(\"h3\",{children:\"Evolving to Everything-as-Code\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Jeremy Mill, Varo\u2019s Director of Security Engineering, wanted to transition as much as possible towards an infrastructure-as-code approach. In his search for a new security solution, he knew that everything-as-code was a priority and found alignment between his vision for his team and Panther\u2019s Detection-as-Code based solution.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Their existing solution didn\u2019t deliver the level of flexibility they needed in a SIEM. The built-in alerting functionality was limited and lacked key features like dynamic alert severities, detection enrichment, and alert management. By choosing to adopt a Detection-as-Code approach with their SIEM solution, the Varo team has been able to drastically improve their security operations.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"The team leverages many out-of-the-box Panther detections tuned with Python code edits or rule filters to customize their detection engine to their security environment\u2019s needs. They also heavily use Panther\u2019s enrichment features, delivering key context to alerts for speedier response times. Through detection tuning and enrichment, they\u2019ve improved their false-positive alert rate and enabled security team members to focus their efforts on high-value signals and avoid burnout.\\xa0\"}),/*#__PURE__*/t(\"blockquote\",{children:[/*#__PURE__*/e(\"p\",{children:\"Work-life balance and avoiding burnout is really, really important to me. That way when something real does happen, our team can prioritize it. Every alert should have an action, and if that action is a false-positive assessment, then we can tune it immediately. Otherwise, we would have a lot of fatigue.\"}),/*#__PURE__*/e(\"p\",{children:\"Jeremy Mill, Varo\u2019s Senior Manager of Security Engineering\"})]}),/*#__PURE__*/e(\"h3\",{children:\"Centralizing Data and Alert Management\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"One of the driving forces for finding a new security solution was to improve the visibility and consolidation of Varo\u2019s security data into one platform. It was important for the team to find a solution that delivered easy data ingestion and centralized alerting into one platform. Panther\u2019s native capabilities to ingest high-priority log sources like Okta, GSuite, and AWS enabled Varo to quickly onboard their critical data and leverage out-of-the-box detections for immediate value.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"In addition to using Panther\u2019s native integrations for log ingestion, Varo also uses Panther\u2019s flexible capabilities for ingesting custom data sources.\\xa0\"}),/*#__PURE__*/t(\"blockquote\",{children:[/*#__PURE__*/e(\"p\",{children:\"We have one job that takes in a very legacy data source and we can fire that off to our Panther webhook within the JSON schema we have defined and now it\u2019s in Panther and it\u2019s searchable. Doing that in other security tools would be a nightmare and in Panther, it isn\u2019t.\"}),/*#__PURE__*/e(\"p\",{children:\"Jeremy Mill, Varo\u2019s Senior Manager of Security Engineering\"})]}),/*#__PURE__*/e(\"p\",{children:\"By consolidating their key log sources, Varo gained comprehensive insight into their security landscape, allowing for more effective monitoring and threat detection across their cloud-native operations. This centralized approach streamlined their security operations and gave the security team a holistic view of potential threats and vulnerabilities. As a result, Varo bolstered its security posture, enhancing its ability to identify and respond to possible security incidents proactively. 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There is this fuzziness when it comes to many, many security tools, and when it comes to Panther I have been happy to find none of that.\"}),/*#__PURE__*/e(\"p\",{children:\"Anssi Matti HeliN, Wolt Security Operations Lead\"})]}),/*#__PURE__*/e(\"h3\",{children:\"Wolt\u2019s Preference for Everything-as-Code\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"The primary motivation to adopt detection-as-code was the team\u2019s desire to integrate security operations seamlessly into their existing development workflows. By shifting to detection-as-code, Wolt could leverage the same development practices and tools their engineering teams were already familiar with. This approach enables consistent version control, automated testing, and streamlined collaboration among security and development teams.\"}),/*#__PURE__*/t(\"blockquote\",{children:[/*#__PURE__*/e(\"p\",{children:\"Making changes with the integrated testing in Panther Analysis Tool makes it possible to be much more fearless with the changes. I don\u2019t need to wonder if this will break something, because I know if it will break something before I even deploy it.\"}),/*#__PURE__*/e(\"p\",{children:\"Anssi Matti HeliN, Wolt Security Operations Lead\"})]}),/*#__PURE__*/e(\"p\",{children:\"Wolt implemented detection-as-code using Panther\u2019s integration with version control systems like Git, allowing security engineers to write, test, and review detection rules like any other piece of code. Code reviews and pull requests ensured security rules were thoroughly vetted, improving their quality and accuracy. The Wolt security team uses continuous integration and continuous deployment (CI/CD) pipelines to automatically test and deploy their detections. This automation reduces the manual effort required for managing detections and ensures that changes are deployed rapidly and reliably.\"}),/*#__PURE__*/e(\"p\",{children:\"Python-based detection-as-code has enabled the Wolt team to both tune out-of-the-box detections and create their own. They created one global filter function and an import function to easily tune their Okta detections and customize the existing rule set to better suit their needs, an experience Anssi Matti described as \u201Cdead simple and very straightforward.\u201D\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Integrating security directly into the development lifecycle, coupled with the automation and collaboration benefits, resulted in an overall more robust and agile security posture, positioning Wolt to better protect its customers and assets.\"}),/*#__PURE__*/e(\"h3\",{children:\"Flexible, Managed Data Pipelines\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Wolt\u2019s security team faced the common challenge of effectively managing and analyzing vast amounts of data generated by their growing infrastructure. Legacy SIEMs, like the one they were using, task the end users with managing their data pipelines and integrations themselves. When the integrations broke, and they sometimes did, their team had to spend engineering hours resolving those issues. Recognizing these limitations, Wolt sought a solution that could scale their growth and would not require engineering hours to manage.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Panther\u2019s flexible and scalable cloud-based architecture lets Wolt easily ingest its critical data sources. With native out-of-the-box integrations and support for data transports like S3, Wolt\u2019s engineers no longer need to dedicate time to managing their data pipelines. They could easily start ingesting crucial security logs, like GitHub, AWS, and MongoDB Atlas. For especially high-volume log sources, they employ Panther\u2019s out-of-the-box filtering capabilities to ensure they only ingest their security-relevant data.\\xa0\"}),/*#__PURE__*/t(\"blockquote\",{children:[/*#__PURE__*/e(\"p\",{children:\"We really value the ease of onboarding our very diverse set of services that we use. External services, hosted services, managed services, all of them. And having all of those logs in the same place with the unified detection model and the unified fields.\"}),/*#__PURE__*/e(\"p\",{children:\"Anssi Matti Helin, Wolt Security Operations Lead\"})]}),/*#__PURE__*/e(\"p\",{children:\"With a unified view of all their security logs, Wolt\u2019s security team could detect and respond to threats more quickly and accurately. The real-time ingestion and analysis capabilities allow for the immediate identification of suspicious activities. 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Using the Slack bot means that the security team doesn\u2019t need to open the Panther console to resolve an alert, and supports quick remediation even when collaborating with less technical team members.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"While a technical team like Wolt could build their own Slack bot, Anssi Matti, the Security Operations Lead, is glad that they don\u2019t have to spend their dedicated security resources creating and maintaining something themselves.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Because Panther normalizes data upon ingestion and employs a unified data model, queries in Panther\u2019s data lake backend are fast. During an investigation for an example like a potential insider threat, the unified data model makes it simple to search for a user\u2019s identifier, like an email address across all of their logs at once.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"The data lake\u2019s support for complex searches and correlations across their ingested data enables Wolt to uncover hidden threats and anomalies that might have been missed with less sophisticated tools. 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This approach made it challenging to effectively manage the growing number of security alerts.\\xa0 By implementing Panther, the team\u2019s alert workflows became more streamlined, enabling them to easily assign, track, and resolve incidents. The platform's alert queue and assignment features improved accountability and ensured that security incidents were addressed promptly.\"}),/*#__PURE__*/e(\"p\",{children:\"Leveraging Panther\u2019s comprehensive search features like the summary views delivered faster investigations when responding to alerts. Having all of their security events in a normalized data lake now means that they can more easily find the data they\u2019re looking for.\\xa0\\xa0\"}),/*#__PURE__*/t(\"blockquote\",{children:[/*#__PURE__*/e(\"p\",{children:\"Search has been really useful for generating a set of data. When I have something in mind, I can build it easily and get something back pretty quickly when I\u2019m investigating an alert.\"}),/*#__PURE__*/e(\"p\",{children:\"Eric Jolly, Security Operations Lead\"})]}),/*#__PURE__*/e(\"p\",{children:\"GoFundMe's new, streamlined alert and incident response workflows improved the security team\u2019s operational efficiency and productivity. The platform's automated alert assignment and tracking features reduced manual effort and enabled the security team to prioritize and resolve incidents more efficiently.\"}),/*#__PURE__*/e(\"h3\",{children:\"Leveraging Advanced Detection Capabilities to Reduce False Positives\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"One of the main challenges GoFundMe was facing before deploying Panther was the limited detection capabilities of their existing tools. Their previous solution required them to build everything from scratch, resulting in a significant time investment. Panther's advanced detection capabilities, including both Python-based custom detections and out-of-the-box Detection Packs, helped GoFundMe to quickly improve their threat detection accuracy and reduce false positive alerts. For critical data sources, the Detection Packs were especially valuable in providing immediate threat coverage. Features like rule filters in Panther enable the team to easily tune and iterate on out-of-the-box detections, creating a cycle of continuous improvement.\\xa0\"}),/*#__PURE__*/t(\"blockquote\",{children:[/*#__PURE__*/e(\"p\",{children:\"One of the big advantages with Panther is having a library of built in rules, and the fact that new ones are coming out pretty frequently. It takes that burden off of us to create our own. Whereas in our previous tools, that's entirely up to us to create those rules and those alerts, and that is a significant time requirement.\"}),/*#__PURE__*/e(\"p\",{children:\"Eric Jolly, Security Operations Lead\\xa0\"})]}),/*#__PURE__*/e(\"p\",{children:\"Using Panther's advanced detection capabilities and customization options, GoFundMe successfully reduced the number of false positive alerts in their queues. Leveraging the ability to apply no-code rule filters the security team can easily customize Panther\u2019s pre-written detections to meet their environment\u2019s unique needs and keep false positive alerts low. The GoFundMe team also makes heavy use of Enrichment, utilizing custom Lookup Tables to add key context to their detections, cutting down investigation times and false positive alerts even further.\\xa0\"}),/*#__PURE__*/t(\"blockquote\",{children:[/*#__PURE__*/e(\"p\",{children:\"Panther has matured our workflows in a lot of ways. In terms of threat detection and alerting it\u2019s allowed us to standardize, and it\u2019s even helped with SOC2 in some ways. Panther has helped us in investigations that became incidents; it\u2019s a great tool for investigating those vulnerabilities. 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Their leadership team knew that it was time to take their security to the next level and find a solution that consolidated their security events into one system for centralized visibility and delivered flexibility to easily create custom detections to monitor for potential threats in their environment. Michael\u2019s search for a modern SIEM led him to Panther, where he found a solution that matched his team\u2019s needs. If Panther didn\u2019t exist, Michael admits that they likely would have needed to build something similar themselves since they couldn\u2019t find another solution offering the same level of customization at a scalable cost.\\xa0\"}),/*#__PURE__*/t(\"blockquote\",{children:[/*#__PURE__*/e(\"p\",{children:\"Given that the security team in general was pretty small, there were a couple of key things that we needed that were non-negotiable. One was a hosted modern, scalable solution that didn't take somebody's full-time job administering. 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As a result, Zapier recognized the need for a solution that could streamline event management and provide a unified platform for monitoring and responding to security incidents.\"}),/*#__PURE__*/e(\"p\",{children:\"With Panther, Zapier was able to easily centralize security event management and correlation. Panther\u2019s out of the box data ingestion integrations with commonly used SaaS products especially made onboarding their data simple for Zapier. Their first six critical data sources were onboarded on day two- in about half the time they estimate it would have taken on a legacy SIEM product.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"Panther's scalability and budget-friendly pricing ensure that Zapier can adapt to evolving security needs without experiencing performance bottlenecks. As the company expands its infrastructure and adds new services, Panther can seamlessly accommodate the increased workload and data volume without overhead maintenance or skyrocketing costs like legacy SIEMs often require. With Panther\u2019s ease of data ingestion and pricing model, they\u2019ve increased their visibility from 20% of their security logs to 70% with plans to achieve 100% in the near future.\\xa0\"}),/*#__PURE__*/e(\"h3\",{children:\"Engineering First Detection & Response\"}),/*#__PURE__*/e(\"p\",{children:\"Zapier\u2019s existing security program was making use of a legacy infrastructure tool that wasn\u2019t suited to their security-specific use cases. They were limited to basic event threshold detections but knew that they needed a tool that supported advanced detection use cases to achieve comprehensive threat coverage across all of their log sources. Their prior tool didn\u2019t provide pre-written detection or enable effective custom detections, meaning they couldn\u2019t get alerts for known security concerns in their environment.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"While there are a number of SIEMs on the market that deliver advanced detection capabilities, Panther stood out for its use of Python-based detections. With Panther, Michael didn\u2019t need to limit his Detection & Response hiring to engineers with tool-specific knowledge already in place or invest heavily in education and onboarding with tool-specific training. Adopting Python-based detections allowed the security team to leverage their existing engineering skills to develop sophisticated detection rules.\"}),/*#__PURE__*/e(\"p\",{children:\"The Zapier security team creates new detection rules based on gap analyses across their environment. Utilizing a combination of Panther\u2019s out-of-the-box rules and their own custom detections, Zapier has achieved comprehensive threat coverage, improved response times, and reduced false positive alerts. The platform's advanced analysis capabilities allowed the security team to identify genuine security threats more accurately, minimizing the occurrence of false alarms.\"}),/*#__PURE__*/e(\"h3\",{children:\"Establishing a Detection & Response Team\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"To establish an effective Detection & Response team, Michael needed to find the right solution to centralize their security workflows. When Michael started his search for the right tool for their team, Panther stood out due to its modern, cloud-native architecture, ease of use, and its support for Python-based detection logic, aligning perfectly with the team's existing engineering skills.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"The urgency to find a solution was driven especially by the lack of visibility and aggregation of security-related events, especially from critical sources like Okta, Google, Slack, and Zoom. The team was limited by this lack of employee data for their internal security. With the shift away from traditional in-office working environments and on-prem services, employee data like this is critical for security teams to monitor.\\xa0\"}),/*#__PURE__*/t(\"blockquote\",{children:[/*#__PURE__*/e(\"p\",{children:\"Your identities and what your people do are how you interface with the world. And so you need to have your security perimeter at the identity level. 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The company has experienced rapid growth in the last several years. Given the critical nature of their industry, security is a top focus. During their search for a Detection Platform they needed to remain compliant and meet their customers' high security standards in addition to finding a tool that enables them to apply standard software engineering practices to their detection writing processes.\"}),/*#__PURE__*/e(\"p\",{children:\"Given their tech stack and customer requirements, Benchling was looking for a Detection Platform that would grant them total ownership of their data in their own environment and keep costs linear and predictable despite rapidly growing cloud infrastructure log volumes.\"}),/*#__PURE__*/e(\"h3\",{children:\"Embracing Code-Driven SecOps\"}),/*#__PURE__*/t(\"blockquote\",{children:[/*#__PURE__*/e(\"p\",{children:\"Our detection and response team cannot be responding to hundreds of alerts a day, there\u2019s just no possible way. 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Using CI/CD to deploy detections, the Benchling team is confident in both the efficacy of their rules to catch true positives while tuning out noisy false positives.\"}),/*#__PURE__*/e(\"h3\",{children:\"Crafting Complex Detection Logic in Python\"}),/*#__PURE__*/e(\"p\",{children:\"Benchling takes advantage of Panther to write powerful, environment-specific detections. Detections in Panther are written in Python - a highly expressable and widely adopted language. The combination of Python and the security data lake makes it easy to craft robust detections that call on efficiently stored and organized data. At Benchling, there was nuanced malicious behavior the team wanted to detect. The behavior had multiple indicators and required calculation and correlation across disparate variables to alert correctly. Using a combination of batch-styled SQL queries to build dynamic baselines for certain behaviors and Python to process results, Benchling was able to correlate data from multiple heterogeneous datasets to create a custom detection tailored for Benchling's specific use case.\"}),/*#__PURE__*/e(\"h3\",{children:\"Meeting Unique Data Needs\"}),/*#__PURE__*/t(\"blockquote\",{children:[/*#__PURE__*/e(\"p\",{children:\"With Panther Cloud Connected, not only do we run Panther on our own AWS infrastructure, but we also run it on our own Snowflake, which allows us to continue to uphold the highest standards for our customers.\"}),/*#__PURE__*/e(\"p\",{children:\"Brian Maloney, Engineering Manager\"})]}),/*#__PURE__*/e(\"p\",{children:\"Given their industry, it is important to Benchling that they own all of their data on their own infrastructure. Built with serverless architecture, Panther\u2019s Cloud Connected deployment option fits both Benchling\u2019s budget and infrastructure needs perfectly. Leveraging Panther Cloud Connected, Benchling was able to double their data ingest without breaking their budget, ensuring every single security-relevant event can be monitored. Benchling needed a SIEM that would work with their custom data processing workflows and support their unique processes. Panther seamlessly integrated with Benchling's data workflow. Their Panther deployment and data workflows ensure they maintain ownership of their data at all times, strengthening Benchling\u2019s security posture while making use of Panther\u2019s powerful detection engine.\"}),/*#__PURE__*/e(\"p\",{children:\"Additionally, using a world-class data warehouse like Snowflake unlocks analytics capabilities that are simply not present in other SIEM software.\\xa0 Benchling\u2019s highly-skilled detection engineers can easily use Snowflake in conjunction with other data analysis tools using the same tools for querying and analysis that data scientists use.\\xa0 By bringing extensibility to both detection logic and analysis capabilities, Panther provides a truly open platform for deriving actionable Security intelligence from raw log data.\"}),/*#__PURE__*/e(\"p\",{children:\"At the end of the day, Panther is enabling a highly technical team to maximize their time spent on writing and optimizing detections for their unique environment.\\xa0\"}),/*#__PURE__*/t(\"blockquote\",{children:[/*#__PURE__*/e(\"p\",{children:\"Panther is freeing up our engineers' time to do what they do well, which is writing detections and responding to novel threats. Without the ease of use combined with scalability we get from Panther, the Benchling Security Operations program would not be as mature as we are today.\"}),/*#__PURE__*/e(\"p\",{children:\"William Phillips, Head of Security Operations\"})]})]});export const richText71=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Integrating with Benchling\u2019s tech stack and existing data processing and infrastructure needs\"})});export const richText72=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Scalable programmatic approach to Security Detection development that allows detections to be change-managed via GitOps\"})});export const richText73=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Delivering extensible detections (using external APIs and data sources) is a challenge with many products on the market\"})});export const richText74=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Leveraging a code-driven detection engine enabled the security team to write reliable, tested detections\"})});export const richText75=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Using a general programming language like Python allows detection logic to access anything with an API, such as their own cloud infrastructure and partner SaaS\"})});export const richText76=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Deploying Panther Cloud Connected - Built with serverless architecture, Panther\u2019s Cloud Connected deployment option fit Benchling\u2019s unique infrastructure and data needs perfectly\"})});export const richText77=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Timely and effective detection deployment with true CI/CD resulted in high fidelity detections\"})});export const richText78=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Simple Detection maintainability as program grew to meet the needs of the business\"})});export const richText79=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Quickly iterated and deployed critical detections as part of response actions\"})});export const richText80=/*#__PURE__*/t(i.Fragment,{children:[/*#__PURE__*/e(\"p\",{children:\"JupiterOne, a cloud-native security company, is a leader in security asset management. Their tool focuses on providing added context on the relationships between assets. Its ability to dynamically enrich data and provide focused details to security events enhances security team incident response capabilities.\"}),/*#__PURE__*/e(\"p\",{children:\"As JupiterOne grew their security operations, they recognized the importance of having a SIEM to gain insights into high-risk, critical actions within their systems. With events occurring across their tech stack, it was critical to centralize visibility into their logs in one place for monitoring. The decision to adopt Panther stemmed from JupiterOne\u2019s alignment with Panther\u2019s cloud-native and engineering first approach to detections-as-code.\"}),/*#__PURE__*/t(\"blockquote\",{children:[/*#__PURE__*/e(\"p\",{children:\"We worked with one of Panther\u2019s amazing engineers, Nate, and he helped us configure the Terraform to fit our needs. Ever since then it has just simply worked. We haven\u2019t had to tweak it. We haven\u2019t had to modify it. Haven\u2019t had bug fixes or anything like that. It just works.\"}),/*#__PURE__*/e(\"p\",{children:\"Kenneth Kaye, Security Automation Architect\"})]}),/*#__PURE__*/e(\"h3\",{children:\"Deploying Code Driven SecOps\"}),/*#__PURE__*/e(\"p\",{children:\"The team knew they would face frustration with generic out-of-the-box detections provided by traditional SIEMs. These detections often result in false positives, flooding the system with unactionable alerts. These poor alerts not only consume valuable time but also hinder the ability to promptly identify genuine security incidents.\"}),/*#__PURE__*/e(\"p\",{children:\"Adopting the detections as code approach allowed the security team to customize, test, and fine-tune detections according to their specific environment. By leveraging Python, they gained the flexibility to update and fine tune detections rapidly, reducing the noise generated by traditional SIEMs and ensuring that alerts were tailored to their unique use cases.\\xa0\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"When JupiterOne found the disconnect of cloned detections from upstream updates in the Panther Analysis Tool burdensome, Panther responded to this feedback by adding a feature that allows users to customize Panther-provided detections while retaining customer-applied customizations. This has resulted in better uptime, less maintenance, and specialized detections for JupiterOne\u2019s specific needs.\"}),/*#__PURE__*/e(\"p\",{children:\"The team experienced a noted lack of false positives, enabling them to focus their attention on high fidelity alerts and legitimate security concerns. The ability to code detections provided a level of precision and customization that traditional SIEMs lack, resulting in a more efficient and accurate security monitoring process.\"}),/*#__PURE__*/e(\"h3\",{children:\"Building for the Cloud\"}),/*#__PURE__*/e(\"p\",{children:\"JupiterOne, being a cloud-native company, didn\u2019t want to consider SIEM solutions that lacked necessary cloud-native features. Legacy SIEMs are not designed to effectively monitor and secure dynamic cloud environments, posing a significant challenge for modern security teams like JupiterOne.\"}),/*#__PURE__*/e(\"p\",{children:\"Panther's cloud-native architecture addressed this challenge head-on. Specifically tailored for cloud environments, Panther provided the scalability, flexibility, and agility required to effectively monitor assets and events in their dynamic infrastructure.\"}),/*#__PURE__*/e(\"p\",{children:\"Panther seamlessly integrated with their systems, ensuring that their security monitoring was aligned with the broader organization's cloud-first approach.\"}),/*#__PURE__*/e(\"h3\",{children:\"Growing SecOps Coverage with a Small Team\"}),/*#__PURE__*/e(\"p\",{children:\"Being a small security team, JupiterOne wanted to avoid difficulties with constantly tuning their SIEM . With traditional SIEMs, the rule tuning process is time-consuming, and the team may have struggled to keep up with the demands of an ever-evolving threat landscape.\"}),/*#__PURE__*/e(\"p\",{children:\"Embracing detections as code not only addressed the challenge of generic detections, but also allowed engineering to get more deeply involved in the tuning process. This collaborative approach empowered the team to leverage Python for honing and managing detections efficiently across team members.\"}),/*#__PURE__*/e(\"p\",{children:\"The collaborative effort across the JupiterOne team paired with the adoption of detections as code ensured that the SIEM was finely tuned to their environment, enhancing its overall effectiveness.\"}),/*#__PURE__*/t(\"blockquote\",{children:[/*#__PURE__*/e(\"p\",{children:\"More teams are going to have to go towards engineering first, they\u2019re going to have to. The environment is changing and the nature of security engineering and security operations are changing. It\u2019s scaling to the point where you can\u2019t hire enough people anymore to do all the work, you have to get smarter about it and engineer for security.\"}),/*#__PURE__*/e(\"p\",{children:\"Kenneth Kaye, Security Automation Architect\"})]})]});export const richText81=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"False Positives from Generic Detections: Many SIEMs provided generic detections that result in false positives and are often not tuned to a specific environment\"})});export const richText82=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Lack of Cloud-Native Features: Legacy SIEMs lacked the cloud-native capabilities required to address the challenges specific to a cloud-centric infrastructure\"})});export const richText83=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Limited Team Resources: With a lean team, the tech stack needs to support effortless scalability without requiring additional headcount\"})});export const richText84=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Detections as Code: The ability to code and configure detections in Python allowed the security team to easily tailor alerts to their environment\"})});export const richText85=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Cloud-Native Architecture: Panther's cloud-native approach aligned seamlessly with their infrastructure, providing the flexibility and scalability needed for monitoring a dynamic environment\"})});export const richText86=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Accessible Features like Rule Filters: The addition of rule filters and code-free features in Panther allowed for more fine-tuned control over detections across the team\u2019s skill levels, enhancing the full team's ability to prioritize and act on security alerts\"})});export const richText87=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Reduced False Positives: Detections as Code empowered the team to refine alerts, reducing false positives and delivering actionable insights\"})});export const richText88=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Improved Cloud-Native Monitoring: Panther's cloud-native architecture addressed the specific challenges posed by their infrastructure, ensuring effective monitoring without unnecessary noise\"})});export const richText89=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Enhanced Collaboration: The ability to involve the broader team in tuning and managing detections enhanced collaboration for the security team\"})});export const richText90=/*#__PURE__*/t(i.Fragment,{children:[/*#__PURE__*/e(\"p\",{children:\"Since 2008, Asana, a leading work management platform for organizations, has embraced a mission of enabling teams to work together effortlessly. With millions of users across industries collaborating on its platform, Asana must protect a large, diverse collection of data for its customers, including those within highly regulated sectors such as healthcare. To meet these challenges as quickly and cost-effectively as possible, Asana chose to embrace scalability and automation through engineering-based approaches.\"}),/*#__PURE__*/e(\"p\",{children:\"Jackie Bow, Head of Detection and Response at Asana, recognized that traditional detection workflows using a traditional SIEM wouldn't scale for Asana's complex needs. \\\"I have been in security analysis roles before, and I knew that trying to solve detection and response challenges in the traditional ways of black-box SIEM detection and heavy use of manual analyst labor would not match Asana's engineering-first culture or lead to a scalable, sustainable team,\\\" Bow said. \\\"We're an engineering-driven company, and I wanted to solve the challenges we were facing in an automated way using code and engineering principles.\\\" This approach led Bow and Asana to explore Panther.\"}),/*#__PURE__*/e(\"h3\",{children:\"Building a Team Focused on Detection-as-Code\\xa0\"}),/*#__PURE__*/e(\"p\",{children:'For most detection and response teams using legacy SIEMs, security analysts get a barrage of alerts without the context needed to investigate threats effectively. The root cause of this stems from tools that have preset detections that aren\u2019t tailored to the environments they\u2019re used in, and alerts that lack context necessary for those triaging them. \"The reality in many SOCs is that there are just too many alerts to work through, and it results in poor return on investment on actual threats being detected,\" Bow said.\\xa0'}),/*#__PURE__*/e(\"p\",{children:'Bow\\'s team sought a solution that would facilitate engineering-centric detection workflows that aligned with her team\\'s philosophy. \"We used to have a lot of siloes that made detection and response workflows challenging. It was hard to collaborate. With a dedicated Detection and Response function and the tooling that supports it, we\\'ve improved our ability to detect and respond to incidents faster,\" Jackie said. \"Panther allows us to offer detection-as-a-service to other stakeholder teams. We can work with them to create custom detections that suit their specific needs, and we have the ability to manage 100% of them as code.\"\\xa0'}),/*#__PURE__*/e(\"h3\",{children:\"Accelerating Detection and Response at Scale with Panther\"}),/*#__PURE__*/e(\"p\",{children:'Asana had been using the open-source log analysis project, StreamAlert, for several years, and Bow\\'s team found it increasingly difficult to maintain the software as they scaled. \"Despite the fact that we love open source, we were using StreamAlert for detections, and as we grew, and the StreamAlert open source project became unmaintained, it was harder to manage,\" said Bow. \"We liked how StreamAlert fit into our CI/CD pipelines and overall architecture, but the maintenance costs and the operational overhead became untenable. We were hitting a performance ceiling and needed a more powerful system that could handle the scale of our infrastructure.\"'}),/*#__PURE__*/e(\"p\",{children:\"With the adoption of Panther, Asana no longer needed to worry about performance or scale. Panther's cloud-native SaaS architecture allowed Asana to leverage the full power of the cloud to seamlessly scale up and down as needed, ensuring that their detection infrastructure could handle the demands of its growing platform. \\\"Our customers expect the best from us, and that's what we built our team and system to deliver. Our cloud surface is large, so Panther's ability to process and analyze all of that data seamlessly has cut down the time it takes us to detect suspicious activity.\\\"\\xa0\"}),/*#__PURE__*/e(\"h3\",{children:\"Asana Looks Forward to 100% Threat Map Coverage\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"The Asana Detection and Response team set its compass towards the ambitious goal of 100% threat map coverage. To achieve this, the team must rely on automation and dynamic systems to deal with constantly changing and growing log sources and data volumes.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:'With other SIEMs, Asana would be forced to choose between incurring exorbitant costs or not analyzing its most critical data. Fortunately, Panther solves both challenges through its ability to manage detection-as-code and limit cost at scale. \"Our entire approach was based on avoiding hiring an army of analysts and contractors because we believe we can do better less expensively with well-designed systems,\" Bow said. \"For this to make sense, we also needed a SIEM that we could scale up to our level of demand in a more cost-effective way than the legacy players. We could see a world of getting to our 100% threat surface coverage goal with Panther that would have cost considerably more with a collection of off-the-shelf tools from other vendors.\"'}),/*#__PURE__*/e(\"p\",{children:\"As the Asana Detection and Response team continues to grow, Bow is excited for the future of building even more automation across the organization and using detections to deliver additional workflow value to teams. \\\"As other security teams, including product security and internal tooling, understand our capabilities better, we're starting to see them ask for things outside of what you'd expect detections to be limited to,\\\" Bow said. \\\"It's really cool to see the applications of what we're doing help to make people's jobs easier. It makes it exciting to keep building together.\\\"\"})]});export const richText91=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Scaling a detection and response program that has full visibility and control over detections and tooling\"})});export const richText92=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Maintaining the ability to process large amounts of security data\"})});export const richText93=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Onboarding a variety of stakeholders and use cases\"})});export const richText94=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Automating detection and response workflows to support industry compliance\"})});export const richText95=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Delivering detection infrastructure-as-a-service to product engineering teams\"})});export const richText96=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Dynamically scaling with rapidly growing log volume for cloud workloads\"})});export const richText97=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Eliminated introduction of manual tasks through use of intelligent log analysis\"})});export const richText98=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Increased threat map coverage using detection-as-code\"})});export const richText99=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Reduced projected SIEM total cost of ownership (TCO)\"})});export const richText100=/*#__PURE__*/t(i.Fragment,{children:[/*#__PURE__*/e(\"h3\",{children:\"Jumio: A Leader in Identity Verification\"}),/*#__PURE__*/t(\"p\",{children:[\"Jumio is an identity verification company that validates customers for mobile and web transactions. Leveraging advanced technology including automation, biometrics, AI/machine learning, liveness detection and no-code orchestration with hundreds of data sources, Jumio helps organizations fight fraud and financial crime, onboard good customers faster and meet regulatory compliance including KYC and AML. Jumio has secured more than one billion transactions across a range of industries, including financial services, gaming, travel, and healthcare.\",/*#__PURE__*/e(\"br\",{}),/*#__PURE__*/e(\"br\",{}),\"Prior to looking for a SIEM solution, Jumio paid a managed service provider. The team was disappointed in the opaque nature of the service and wanted to bring control over their security monitoring in-house. To do so, \",/*#__PURE__*/e(\"strong\",{children:\"Mo Imran, Jumio\u2019s Head of Threat Detection and Response\"}),\" wanted a security analytics platform that could handle their diverse and voluminous data sources, enable them to write flexible and powerful detection logic, and store their data in a structured way to enable fast queries. Jumio chose Panther as their cloud-native SIEM solution to meet these needs and improve their security operations.\"]}),/*#__PURE__*/e(\"h3\",{children:\"Easy Data Onboarding with Native Integrations & Infer Schema Functionality\"}),/*#__PURE__*/t(\"p\",{children:[\"One of the main challenges that Imran faced with traditional SIEM tools was getting data into the platform, especially from custom or non-standard log sources. Typically, they had to work with the vendor, which took weeks, if not months, to figure out all the schemas and formats. With Panther, Jumio was able to onboard all of their data sources in less than a week, thanks to native integrations with common cloud and SaaS applications. For their Windows logs and other custom data sources, Jumio leveraged Panther's infer schema functionality, which can \u201Cread\u201D sample logs from any source and create a custom schema for it. This \",/*#__PURE__*/e(\"strong\",{children:\"enabled Jumio to ingest log sources into Panther without waiting for vendor support or manual configuration\"}),\".\"]}),/*#__PURE__*/e(\"h3\",{children:\"Flexible Detection Logic in Python\"}),/*#__PURE__*/e(\"p\",{children:\"Another challenge that Jumio faced with traditional SIEM tools was writing and tuning detection logic that was meaningful and relevant for their environment. Out-of-the-box logic was often basic and noisy, generating too many false positives and wasting time and resources. It was also difficult to write new or customize existing logic in most SIEMs, which used vendor-specific or proprietary languages that were hard to learn and maintain.\\xa0\"}),/*#__PURE__*/e(\"p\",{children:\"With Panther, Jumio was able to write highly customizable detections using Python, a widely adopted and versatile language that enabled them to write lean and efficient code. Python also gave them the ability to enrich detections with external data sources, query other log sources, cache and timestamp events, and perform simple baselining and trend analysis. This enabled Jumio to optimize how meaningful each alert they generated was, reducing noise and improving accuracy.\"}),/*#__PURE__*/e(\"p\",{children:\"One example of a detection that Jumio was particularly proud of was a rule for spear phishing attacks. The multi-part rule cached an IP address for baselining, checked for activity from the same account from two different IPs, while also applying some of the out-of-the-box brute force logic. This rule helped Jumio detect and prevent more sophisticated phishing attempts.\"}),/*#__PURE__*/e(\"h3\",{children:\"Structured Data Stored in Security Data Lake\"}),/*#__PURE__*/e(\"p\",{children:\"A third challenge that Jumio faced with traditional SIEM tools was querying unstructured data across large volumes of logs. In other tools, correlating data over terabytes for a query could take 15 minutes or more, making investigations slow and cumbersome. With Panther, Jumio was able to bring in verbose data streams and store them in a structured security data lake powered by Snowflake, a cloud data platform that enables fast and scalable queries over massive data sets. Panther also normalized indicators of compromise (IOCs) across all log sources as data was ingested, making it easier to query across structured data based on attributes like usernames, emails, IPs, and more. This helped Jumio tell the full story during an incident and perform thorough investigations in minutes.\"}),/*#__PURE__*/e(\"h3\",{children:\"Top-Notch Support from Panther Team\"}),/*#__PURE__*/e(\"p\",{children:'In addition to the technical capabilities of Panther, Jumio also appreciated the support they received from the Panther team throughout their deployment and usage of the platform. \"The support has been a breath of fresh air,\" Imran noted. \"When there is an issue, I have complete confidence you all are on it.\" Jumio also valued the feedback loop with Panther, which allowed them to share their suggestions and requests for new features or improvements.\\xa0'}),/*#__PURE__*/e(\"h3\",{children:\"Conclusion\"}),/*#__PURE__*/e(\"p\",{children:\"By choosing Panther as their cloud-native SIEM solution, Jumio was able to streamline their data onboarding process, write flexible and powerful detection logic in Python, store their data in a structured security data lake powered by Snowflake, and receive top-notch support from the Panther team. Panther helped Jumio improve their security operations and achieve their security goals with speed, scale, and flexibility.\"}),/*#__PURE__*/t(\"blockquote\",{children:[/*#__PURE__*/e(\"p\",{children:\"Panther is a great choice for security teams that want to take control of their data and detections,\"}),/*#__PURE__*/e(\"p\",{children:\"Mo Imran, Head of Threat Detection and Response, Jumio\"})]})]});export const richText101=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Many tools make it difficult to ingest diverse or custom data sources\"})});export const richText102=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Out-of-the-box detection logic is traditionally noisy and hard to edit\"})});export const richText103=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Vast amounts of unstructured data leads to extremely slow query times\"})});export const richText104=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Easy data onboarding with native integrations & infer schema functionality\"})});export const richText105=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Flexible, powerful detection logic in Python enables granular detections\"})});export const richText106=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Structured data stored in Security Data Lake efficiently increases retention and accelerates queries\"})});export const richText107=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"Panther\u2019s cloud-native architecture enables the security team to focus on security, not tool maintenance\"})});export const richText108=/*#__PURE__*/e(i.Fragment,{children:/*#__PURE__*/e(\"p\",{children:\"By leveraging environment-specific logic, Jumio has drastically increased alert fidelity\"})});export const richText109=/*#__PURE__*/t(i.Fragment,{children:[/*#__PURE__*/e(\"h3\",{children:\"The Most Trusted Crypto Exchange\"}),/*#__PURE__*/e(\"p\",{children:\"Bitstamp is the world\u2019s longest-standing cryptocurrency exchange, having provided safe, secure, and reliable access to crypto since 2011. With a proven track record and mature approach to the industry, Bitstamp provides a secure and transparent trading venue to over five million individuals and is the preferred choice for a range of institutional clients seeking a trusted partner to participate in crypto markets. Bitstamp is a sector leader in both security and compliance, with 51 licenses and registrations secured with financial regulators across the globe.\"}),/*#__PURE__*/e(\"p\",{children:\"As the world\u2019s most trusted cryptocurrency exchange, security is paramount for Bitstamp. The permanence of transactions in the crypto space leaves no room for error. Due to the decentralized nature of cryptocurrencies, a hack of assets will likely remain anonymous and final. Moreover, financial institutions are held to a strict regulatory standard and organizations must maintain proper security measures. Audits require extensive visibility across infrastructure and application data. Structuring a security program within such stringent requirements is already a challenge, but the difficulty is exacerbated when trying to secure a dynamic cloud environment.\"}),/*#__PURE__*/e(\"h3\",{children:\"Trying To Secure a Dynamic Cloud Environment\"}),/*#__PURE__*/e(\"p\",{children:\"When he joined Bitstamp, Jan Urbanc, Head of Security Operations, already had scars from trying to implement SIEM solutions in previous roles. Traditional tools were often incapable of handling voluminous and diverse log sets, detection logic was written in a complicated vendor-specific language, and testing and updating detection logic was a pain. Frustrated by the engineering hours required for set-up, overhead, and maintenance with many solutions on the market, he wanted to bring something new to Bitstamp.\"}),/*#__PURE__*/t(\"blockquote\",{children:[/*#__PURE__*/e(\"p\",{children:\"With traditional tooling, getting a new detection to production took hours of engineering time. With Panther, it's seconds or minutes,\"}),/*#__PURE__*/e(\"p\",{children:\"Jan Urbanc, Head of Security Operations, Bitstamp\"})]}),/*#__PURE__*/e(\"h3\",{children:\"Flexible Ingestion and Customizable Out-Of-The-Box Detections with Panther\"}),/*#__PURE__*/e(\"p\",{children:\"When faced with purchasing a SIEM solution at Bitstamp, the security team had several key reasons for choosing Panther.\"}),/*#__PURE__*/e(\"h3\",{children:\"Flexible & Cost-Effective Log Ingestion\"}),/*#__PURE__*/e(\"p\",{children:\"The pricing of many SIEM tools forces security teams to pick and choose logs they\u2019ll ingest - leading to a lack of visibility. With Panther, Bitstamp is able to efficiently ingest all the logs they need, including nontraditional or custom log sources \u2013 it removes the need to prioritize which data is important. \u201CYou cannot possibly find a product that could take 1TB of data a day at a similar price point,\u201D Jan said. \u201CThat alone sidelines the majority of vendors.\u201D\"}),/*#__PURE__*/e(\"p\",{children:\"Moreover, having faced serious security incidents, Jan knows the importance of context. \u201CWhen an incident occurs, it\u2019s often one random log source that\u2019s going to provide the information you need,\u201D Jan noted. He\u2019s been in active incidents where he needed to bolster the limited information that was placed in the SIEM. He\u2019s tracked down random logs, and tried to organize and make sense of them in real time - a very stressful exercise when the clock is ticking.\"}),/*#__PURE__*/e(\"p\",{children:\"With Panther\u2019s flexible custom schemas and architecture built on a security data lake, it\u2019s much simpler to ingest, structure, and query a wide variety of logs so they\u2019re ready for urgent situations. Bitstamp has some standard logs like AWS CloudTrail and M365, but they also have organization-specific application and audit log types aka \u2018skeleton in the closet\u2019 logs. \u201CWe\u2019re so thankful for the infer schema functionality.\u201D Jan said, \u201CThe flexibility to throw any log source into Panther was a critical reason we chose the tool.\u201D\"}),/*#__PURE__*/e(\"h3\",{children:\"Detections in Python, Querying in SQL\"}),/*#__PURE__*/e(\"p\",{children:\"For Bitstamp, a SIEM tool should use widely-adopted languages for detection and query logic. \u201CA big issue I have with a number of SIEMs is their insistence on using some confusing vendor-specific language for detections,\u201D Jan noted. In Panther, detections are written in Python - enabling engineers of all types to work in the tool.\"}),/*#__PURE__*/e(\"p\",{children:\"Panther does provide a variety of out-of-the-box detections. \u201CThe AWS detections and policies that come with Panther are hyper-valuable,\u201D Jan said. However, the Python language enables interesting use cases for customization and enrichment. \u201CPython gives us flexibility to do a lot of things in a detection: data manipulation, quick queries, quick GET requests to APIs of interest - all of which enrich the detection.\u201D\"}),/*#__PURE__*/e(\"p\",{children:\"Moreover, Panther uses SQL for investigations. 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First, where an action by a user looks suspicious but lacks context; and second, where an actor taking an action is unknown and more data is needed to pinpoint the user. 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