SecOps Platform

Modernize security operations and investigate threats at cloud-scale speed with Panther.

“Panther’s architecture is perfect for modern technology organizations: easy to roll out, scalable, and with an interface that helps us centralize and expand several of our core security & compliance operations.”

Aaron Zollman, CISO, Cedar

Why Panther for Security Operations?

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Accelerate Threat Detection

When facing a breach, the stakes are high. Having to rely on a slow SecOps platform raises the stakes even higher. With Panther, security operations teams can detect threats immediately by analyzing logs as soon as they are ingested, dramatically expediting the possible time to detection.

Panther’s platform delivers well-honed processes, tracking, and a single pane of glass visibility in a centralized hub for proactive and responsive threat management.

Improve Detection Fidelity

Detection engineering teams are often forced to learn proprietary programming languages and complex workflows associated with traditional SIEM solutions.

Leveraging universal toolsets like Python, Panther’s platform empowers teams to easily create, test, and harden detections directly in the UI or with a CLI-based workflow. With limited false positives and without alert fatigue, you can level up your incident response and get better quality detections.

Expedite Incident Response

Traditional SIEM solutions often force security teams to wait hours or even days to access historical data and even longer for queries to complete. When every minute is critical, investigation and response activities can’t afford to be impeded.

By adding dynamic context to alerts, Panther boosts incident response times with more efficient routing, triage and automation downstream. When alerts contain the right context and get to the right person at the right time, your incident response team is empowered to succeed.

Query Terabytes of Data for Incident Investigations

For critical incident investigation and response, executing large queries shouldn’t take hours or even days to complete. Panther’s log normalization turns disparate logs into usable data that focuses on indicators of compromise (IoCs) to speed up ingestion and optimize future queries.

IoCs are parsed into standardized fields, so you can easily (and quickly) conduct searches across all log types in a single query or detection rule. With Panther, you can query numerous data sources at massive log sizes all at once, without missing a beat.

FAQs About SecOps

Cloud-native application architecture takes full advantage of cloud-based computing features to boost management, scalability, and on-demand output. Typically, best-of-breed cloud-native SOC platforms transform terabytes of raw logs per day into a structured security data lake to power real-time detection, swift incident response, and thorough investigations. Best of all, Cloud Native SOC platforms provide total visibility across silos.

With Panther’s integration of GreyNoise, a leader in threat intelligence, security practitioners can better focus on the most important alerts, without taking on additional overhead to add enrichment in external or downstream platforms. All Panther threat detection platform customers now have access to GreyNoise enrichment data, which enables security teams to craft detections using contextual data from GreyNoise to evaluate network behavior and categorize or suppress alerts accordingly.  Context from GreyNoise can also be appended to alerts for actionable details that accelerate incident response.

Absolutely. Panther, can ingest data from common data transports such as S3, SQS, SNS, Cloudwatch, and Google Cloud Storage. Along with out-of-the-box integrations for critical log sources like 1 Password, Okta, Crowdstrike , G Workspaces, Zoom, and more.

Scaling Security and Gaining Better Visibility

Learn how Cedar is securing health records for more than 10 million patients using detection-as-code and security automation with Panther.

Read the Story

Detect any threat, anywhere with Panther

  • Effortless data ingestion and IoC normalizations
  • Zero ops overhead with serverless architecture
  • 400+ built-in detections for popular SaaS and on-prem apps
  • Detection-as-code in Python with CI/CD workflow
  • 12-month minimum data retention
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