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Understanding the FTC Data Breach Reporting Requirements

June 18, 2024
4
Min Read
Compliance

More Companies Need to Report Data Breaches

In a significant move towards enhancing data security and transparency, new data breach reporting rules have taken effect for various financial institutions. Since May 13, 2024, non-banking financial institutions, including mortgage brokers, payday lenders, and tax preparation firms, must report data breaches to the Federal Trade Commission (FTC) within 30 days of discovery. This new mandate, part of the FTC's Safeguards Rule, expands the breach notification requirements to a broader range of financial entities not overseen by the Securities and Exchange Commission (SEC). 

Furthermore, by June 15, 2024, smaller reporting companies—those with a public float under $250 million or annual revenues under $100 million—must comply with the SEC’s new cybersecurity incident reporting rules, aligning their disclosure obligations with those of larger corporations. These changes mark a significant step towards enhancing transparency and accountability in data breach reporting across the financial sector.

How Can Financial Institutions Secure Their Data?

Understanding and tracking your sensitive data is fundamental to robust data security practices. The first step in safeguarding data is detecting and classifying what you have. It's far easier to protect data when you know it exists. This allows for appropriate measures such as encryption, controlling access, and monitoring for unauthorized use. By identifying and mapping your data, you can ensure that sensitive information is adequately protected and compliance requirements are met.

Identify Sensitive Data: Data is constantly moving, which makes it a challenge to know exactly what data you have and where it resides. This includes customer information, financial records, intellectual property, and any other data deemed sensitive. Having an automated data classification tool is a crucial first step. This includes ‘shadow’ data that may not be well known or well managed.

Data Mapping: Create and maintain an up-to-date map of your data landscape. This map should show where data is stored, processed, and transmitted, and who has access to it. It helps in quickly identifying which systems and data were affected by a breach and the impact blast radius (how extensive is the damage).

"Your Data Has Been Breached, Now What?"

When a data breach occurs, the immediate response is critical in mitigating damage and addressing the aftermath effectively. The investigation phase is particularly crucial as it determines the extent of the breach, the type and sensitivity of the data compromised, and the potential impact on the organization.

A key challenge during the investigation phase is understanding where the sensitive data was located at the time of the data breach and why or how existing controls were insufficient. 

Without a proper data classification process or solution in place, it is difficult to ascertain the exact locations of the sensitive data or the applicable security posture at the time of the breach within the short timeframe required by the SEC and FTC reporting rules. 

Here's a breakdown of the essential steps and considerations during the investigation phase:

1. Develop Appropriate Posture Policies and Enforce Adherence:

Establish policies that alert on and can help enforce appropriate security posture and access controls - these can be out-of-the-box fitting various compliance frameworks or can be customized for unique business or privacy requirements. Monitor for policy violations and initiate appropriate remediation actions (which can include ticket issuance, escalation notification, and automated access revocation or de-identification).

2. Conduct the Investigation: Determine Data Breach Source:

Identify how the breach occurred. This could involve phishing attacks, malware, insider threats, or vulnerabilities in your systems.

According to the FTC, it is critical to clearly describe what you know about the compromise. This includes:

  • How it happened
  • What information was taken
  • How the thieves have used the information (if you know)
  • What actions you have taken to remedy the situation
  • What actions you are taking to protect individuals, such as offering free credit monitoring services
  • How to reach the relevant contacts in your organization

Create a Comprehensive Plan: Additionally, create a comprehensive plan that reaches all affected audiences, such as employees, customers, investors, business partners, and other stakeholders.

Affected and Duplicated Data: Ascertain which data sets were accessed, altered, or exfiltrated. This involves checking logs, access records, and utilizing forensic tools. Assess if sensitive data has been duplicated or moved to unauthorized locations. This can compound the risk and potential damage if not addressed promptly.

How Sentra Helps Automate Compliance and Incident Response

Sentra’s Data Security Posture Management solution provides organizations with full visibility into their data’s locations (including shadow data) and an up-to-date data catalog with classification of sensitive data. Sentra provides this without any complex deployment or operational work involved, this is achieved due to a cloud-native agentless architecture, using cloud provider APIs and mechanisms.

Below you can see the different data stores on the Sentra dashboard.

Sentra Dashboard data stores

Sentra Makes Data Access Governance (DAG) Easy

Sentra helps you understand which users have access to what data and enrich metadata catalogs for comprehensive data governance. The accurate classification of cloud data provides advanced classification labels, including business context regarding the purpose of data, and automatic discovery, enabling organizations to gain deeper insights into their data landscape. This both enhances data governance while also providing a solid foundation for informed decision-making.

Sentra's detection capabilities can pinpoint over permissioning to sensitive data, prompting organizations to swiftly control them. This proactive measure not only mitigates the risk of potential breaches but also elevates the overall security posture of the organization by helping to institute least-privilege access.

Below you can see an example of a user’s access and privileges to which sensitive data.

An example of a user’s access and privileges to which sensitive data

Breach Reporting With Sentra

Having a proper classification solution helps you understand what kind of data you have at all times.

With Sentra, it's easier to pull the information for the report and understand whether there was sensitive data at the time of breach,  what kind of data there was, and who/what had access to it, in order to have an accurate report.

Example of Sentra's Data Breach Report

To learn more about how you can gain full coverage and an up-to-date data catalog with classification of sensitive data, schedule a live demo with our experts.

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Meni is an experienced product manager and the former founder of Pixibots (A mobile applications studio). In the past 15 years, he gained expertise in various industries such as: e-commerce, cloud management, dev-tools, mobile games, and more. He is passionate about delivering high quality technical products, that are intuitive and easy to use.

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Ward Balcerzak
Ward Balcerzak
December 17, 2025
3
Min Read

How CISOs Will Evaluate DSPM in 2026: 13 New Buying Criteria for Security Leaders

How CISOs Will Evaluate DSPM in 2026: 13 New Buying Criteria for Security Leaders

Data Security Posture Management (DSPM) has quickly become part of mainstream security, gaining ground on older solutions and newer categories like XDR and SSE. Beneath the hype, most security leaders share the same frustration: too many products promise results but simply can't deliver in the messy, large-scale settings that enterprises actually have. The DSPM market is expected to jump from $1.86B in 2024 to $22.5B by 2033, giving buyers more choice - and greater pressure - to demand what really sets a solution apart for the coming years.

Instead of letting vendors dictate the RFP, what if CISOs led the process themselves? Fast-forward to 2026 and the checklist a CISO uses to evaluate DSPM solutions barely resembles the checklists of the past. Here are the 12 criteria everyone should insist on - criteria most vendors would rather you ignore, but industry leaders like Sentra are happy to highlight.

Why Legacy DSPM Evaluation Fails Modern CISOs

Traditional DSPM/DCAP evaluations were all about ticking off feature boxes: Can it scan S3 buckets? Show file types? But most CISO I meet point to poor data visibility as their biggest vulnerability. It's already obvious that today’s fragmented, agent-heavy tools aren’t cutting it.

So, what’s changed for 2026? Massive data volumes, new unstructured formats like chat logs or AI training sets, and rapid cloud adoption mean security leaders now need a different class of protection.

The right platform:

  • Works without agents, everywhere you operate
  • Focuses on bringing real, risk-based context - not just adding more alerts
  • Automates compliance and fixes identity/data governance gaps
  • Manages both structured and unstructured data across the whole organization

Old evaluation checklists don’t come close. It’s time to update yours.

The 13 DSPM Buying Criteria Vendors Hope You Don’t Ask

Here’s what should be at the heart of every modern assessment, especially for 2026:

  1. Is the platform truly agentless, everywhere? Agent-based designs slow you down and block coverage. The best solutions set up in minutes, with absolutely no agents - across SaaS, IaaS, or on-premises and will always discover any unknown and shadow data
  1. Does it operate fully in-environment? Your data needs to stay in your cloud or region - not copied elsewhere for analysis. In-environment processing guards privacy, simplifies compliance, and matches global regulations (Cloud Security Alliance).
  1. Can it accurately classify unstructured data (>98% accuracy)? Most tools stumble outside of databases. Insist on AI-powered classification that understands language, context, and sensitivity. This covers everything from PDF files to Zoom recordings to LLM training data.
  1. How does it handle petabyte-scale scanning and will it  break the bank? Legacy options get expensive as data grows. You need tools that can scan quickly and stay cost-effective across multi-cloud and hybrid environments at massive scale.
  1. Does it unify data and identity governance? Very few platforms support both human and machine identities - especially for service accounts or access across clouds. Only end-to-end coverage breaks down barriers between IT, business, and security.
  1. Can it surface business-contextualized risk insights? You need more than technical vulnerability. Leading platforms map sensitive data by its business importance and risk, making it easier to prioritize and take action.
  1. Is deployment frictionless and multi-cloud native? DSPM should work natively in AWS, Azure, GCP, and SaaS, no complicated integrations required. Insist on fast, simple onboarding.
  1. Does it offer full remediation workflow automation? It’s not enough to raise the alarm. You want exposures fixed automatically, at scale, without manual effort.

  2. Does this fit within my Data Security Ecosystem? Choose only platforms that integrate and enrich your current data governance stack so every tool operates from the same source of truth without adding operational overhead. 
  1. Are compliance and security controls bridged in a unified dashboard? No more switching between tools. Choose platforms where compliance and risk data are combined into a single view for GRC and SecOps.
  1. Does it support business-driven data discovery (e.g., by project, region, or owner)? You need dynamic views tied to business needs, helping cloud initiatives move faster without adding risk, so security can become a business enabler.
  1. What’s the track record on customer outcomes at scale? Actual results in complex, high-volume settings matter more than demo promises. Look for real stories from large organizations.
  2. How is pricing structured for future growth? Beware of pricing that seems low until your data doubles. Look for clear, usage-based models so expansion won’t bring hidden costs.

Agentless, In-Environment Power: Why It’s the New Gold Standard

Agentless, in-environment architecture removes hassles with endpoint installs, connectors, and worries about where your data goes. Gartner has highlighted that this approach reduces regulatory headaches and enables fast onboarding. As organizations keep adding new cloud and hybrid systems, only these platforms can truly scale for global teams and strict requirements.

Sentra’s platform keeps all processing inside your environment. There’s no need to export your data; offering peace of mind for privacy, sovereignty, and speed. With regulations increasing everywhere, this approach isn’t just helpful; it’s essential.

Classification Accuracy and Petabyte-Scale Efficiency: The Must-Haves for 2026

Unstructured data is growing fast, and workloads are now more diverse than ever. The difference between basic scanning and real, AI-driven classification is often the difference between protecting your company or ending up on the breach list. Leading platforms, including Sentra, deliver over 95% classification accuracy by using large language models and in-house methods across both structured and unstructured data.

Why is speed and scale so important? Old-school solutions were built with smaller data volumes in mind. Today, DSPM platforms must quickly and affordably identify and secure data in vast environments. Sentra’s scanning is both fast and affordable, keeping up as your data grows. To learn more about these challenges read: Reducing Cloud Data Attack Risk.

Don’t Settle: Redefining Best-in-Class DSPM Buying Criteria for 2026

Many vendors are still only comfortable offering the basics, but the demands facing CISOs today are anything but basic. Combining identity and data governance, multi-cloud support that works out of the box, and risk insights mapped to real business needs - these are the essential elements for protecting today’s and tomorrow’s data. If a solution doesn’t check all 12 boxes, you’re already limiting your security program before you start.

Need a side-by-side comparison for your next decision?  Request a personalized demo to see exactly how Sentra meets every requirement.

Conclusion

With AI further accelerating data growth, security teams can’t afford to settle for legacy features or generic checklists. By insisting on meaningful criteria - true agentless design, in-environment processing, precise AI-driven classification, scalable affordability, and business-first integration - CISOs set a higher standard for both their own organizations and the wider industry.

Sentra is ready to help you raise the bar. Contact us for a data risk assessment, or to discuss how to ensure your next buying decision leads to better protection, less risk, and a stronger position for the future.

Continue the Conversation

If you want to go deeper into how CISOs are rethinking data security, I explore these topics regularly on Guardians of the Data, a podcast focused on real-world data protection challenges, evolving DSPM strategies, and candid conversations with security leaders.

Watch or listen to Guardians of the Data for practical insights on securing data in an AI-driven, multi-cloud world.

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Nikki Ralston
Nikki Ralston
Romi Minin
Romi Minin
December 16, 2025
3
Min Read

Sentra Is One of the Hottest Cybersecurity Startups

Sentra Is One of the Hottest Cybersecurity Startups

We knew we were on a hot streak, and now it’s official.

Sentra has been named one of CRN’s 10 Hottest Cybersecurity Startups of 2025. This recognition is a direct reflection of our commitment to redefining data security for the cloud and AI era, and of the growing trust forward-thinking enterprises are placing in our unique approach.

This milestone is more than just an award. It shows our relentless drive to protect modern data systems and gives us a chance to thank our customers, partners, and the Sentra team whose creativity and determination keep pushing us ahead.

The Market Forces Fueling Sentra’s Momentum

Cybersecurity is undergoing major changes. With 94% of organizations worldwide now relying on cloud technologies, the rapid growth of cloud-based data and the rise of AI agents have made security both more urgent and more complicated. These shifts are creating demands for platforms that combine unified data security posture management (DSPM) with fast data detection and response (DDR).

Industry data highlights this trend: over 73% of enterprise security operations centers are now using AI for real-time threat detection, leading to a 41% drop in breach containment time. The global cybersecurity market is growing rapidly, estimated to reach $227.6 billion in 2025, fueled by the need to break down barriers between data discovery, classification, and incident response 2025 cybersecurity market insights. In 2025, organizations will spend about 10% more on cyber defenses, which will only increase the demand for new solutions.

Why Recognition by CRN Matters and What It Means

Landing a place on CRN’s 10 Hottest Cybersecurity Startups of 2025 is more than publicity for Sentra. It signals we truly meet the moment. Our rise isn’t just about new features; it’s about helping security teams tackle the growing risks posed by AI and cloud data head-on. This recognition follows our mention as a CRN 2024 Stellar Startup, a sign of steady innovation and mounting interest from analysts and enterprises alike.

Being on CRN’s list means customers, partners, and investors value Sentra’s straightforward, agentless data protection that helps organizations work faster and with more certainty.

Innovation Where It Matters: Sentra’s Edge in Data and AI Security

Sentra stands out for its practical approach to solving urgent security problems, including:

  • Agentless, multi-cloud coverage: Sentra identifies and classifies sensitive data and AI agents across cloud, SaaS, and on-premises environments without any agents or hidden gaps.
  • Integrated DSPM + DDR: We go further than monitoring posture by automatically investigating incidents and responding, so security teams can act quickly on why DSPM+DDR matters.
  • AI-driven advancements: Features like domain-specific AI Classifiers for Unstructure advanced AI classification leveraging SLMs, Data Security for AI Agents and Microsoft M365 Copilot help customers stay in control as they adopt new technologies Sentra’s AI-powered innovation.

With new attack surfaces popping up all the time, from prompt injection to autonomous agent drift, Sentra’s architecture is built to handle the world of AI.

A Platform Approach That Outpaces the Competition

There are plenty of startups aiming to tackle AI, cloud, and data security challenges. Companies like 7AI, Reco, Exaforce, and Noma Security have been in the news for their funding rounds and targeted solutions. Still, very few offer the kind of unified coverage that sets Sentra apart.

Most competitors stick to either monitoring SaaS agents or reducing SOC alerts. Sentra does more by providing both agentless multi-cloud DSPM and built-in DDR. This gives organizations visibility, context, and the power to act in one platform. With features like Data Security for AI Agents, Sentra helps enterprises go beyond managing alerts by automating meaningful steps to defend sensitive data everywhere.

Thanks to Our Community and What’s Next

This honor belongs first and foremost to our community: customers breaking new ground in data security, partners building solutions alongside us, and a team with a clear goal to lead the industry.

If you haven’t tried Sentra yet, now’s a great time to see what we can do for your cloud and AI data security program. Find out why we’re at the forefront: schedule a personalized demo or read CRN’s full 2025 list for more insight.

Conclusion

Being named one of CRN’s hottest cybersecurity startups isn’t just a milestone. It pushes us forward toward our vision - data security that truly enables innovation. The market is changing fast, but Sentra’s focus on meaningful security results hasn't wavered.

Thank you to our customers, partners, investors, and team for your ongoing trust and teamwork. As AI and cloud technology shape the future, Sentra is ready to help organizations move confidently, securely, and quickly.

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Meni Besso
Meni Besso
December 15, 2025
3
Min Read

AI Governance Starts With Data Governance: Securing the Training Data and Agents Fuelling GenAI

AI Governance Starts With Data Governance: Securing the Training Data and Agents Fuelling GenAI

Generative AI isn’t just transforming products and processes - it’s expanding the entire enterprise risk surface. As C-suite executives and security leaders rush to unlock GenAI’s competitive advantages, a hard truth is clear: effective AI governance depends on solid, end-to-end data governance.

Sensitive data is increasingly used for model training and autonomous agents. If organizations fail to discover, classify, and secure these resources early, they risk privacy breaches, regulatory violations, and reputational damage. To make GenAI safe, compliant, and trustworthy from the start, data governance for generative AI needs to be a top boardroom priority.

Why Data Governance is the Cornerstone of GenAI Trustworthiness and Safety

The opportunities and risks of generative AI depend not only on algorithms, but also on the quality, security, and history of the underlying data. AWS reports that 39% of Chief Data Officers see data cleaning, integration, and storage as the main barriers to GenAI adoption, and 49% of enterprises make data quality improvement a core focus for successful AI projects (AWS Enterprise Strategy - Data Governance). Without strong data governance, sensitive information can end up in training sets, leading to unintentional leaks or model behaviors that break privacy and compliance.

Regulatory requirements, such as the Generative AI Copyright Disclosure Act, are evolving fast, raising the pressure to document data lineage and make sure unauthorized or non-compliant datasets stay out. In the world of GenAI, governance goes far beyond compliance checklists. It’s essential for building AI that is safe, auditable, and trusted by both regulators and customers.

New Attack Surfaces: Risks From Unsecured Data and Shadow AI Agents

GenAI adoption increases risk. Today, 79% of organizations have already piloted or deployed agentic AI, with many using LLM-powered agents to automate key workflows (Wikipedia - Agentic AI). But if these agents, sometimes functioning as "shadow AI" outside official oversight, access sensitive or unclassified data, the fallout can be severe.

In 2024, over 30% of AI data breaches involve insider threats or accidental disclosure, according to Quinnox Data Governance for AI. Autonomous agents can mistakenly reveal trade secrets, financial records, or customer data, damaging brand trust. The risk multiplies rapidly if sensitive data isn’t properly governed before flowing into GenAI tools. To stop these new threats, organizations need up-to-the-minute insight and control over both data and the agents using it.

Frameworks and Best Practices for Data Governance in GenAI

Leading organizations now follow data governance frameworks that match changing regulations and GenAI's technical complexity. Standards like NIST AI Risk Management Framework (AI RMF) and ISO/IEC 42001:2023 are setting the benchmarks for building auditable, resilient AI programs (Data and AI Governance - Frameworks & Best Practices).

Some of the most effective practices:

  • Managing metadata and tracking full data lineage
  • Using data access policies based on role and context
  • Automating compliance with new AI laws
  • Monitoring data integrity and checking for bias

A strong data governance program for generative AI focuses on ongoing data discovery, classification, and policy enforcement - before data or agents meet any AI models. This approach helps lower risk and gives GenAI efforts a solid base of trust.

Sentra’s Approach: Proactive Pre-Integration Discovery and Continuous Enforcement

Many tools only secure data after it’s already being used with GenAI applications. This reactive strategy leaves openings for risk. Sentra takes a different path, letting organizations discover, classify, and protect sensitive data sources before they interact with language models or agentic AI.

By using agentless, API-based discovery and classification across multi-cloud and SaaS environments, Sentra delivers immediate visibility and context-aware risk scoring for all enterprise data assets. With automated policies, businesses can mask, encrypt, or restrict data access depending on sensitivity, business requirements, or audit needs. Live Continuous monitoring tracks which AI agents are accessing data, making granular controls and fast intervention possible. These processes help stop shadow AI, keep unauthorized data out of LLM training, and maintain compliance as rules and business needs shift.

Guardrails for Responsible AI Growth Across the Enterprise

The future of GenAI depends on how well businesses can innovate while keeping security and compliance intact. As AI regulations become stricter and adoption speeds up, Sentra’s ability to provide ongoing, automated discovery and enforcement at scale is critical. Further reading: AI Automation & Data Security: What You Need To Know.

With Sentra, organizations can:

  • Stop unapproved or unchecked data from being used in model training
  • Identify shadow AI agents or risky automated actions as they happen
  • Support audits with complete data classification
  • Meet NIST, ISO, and new global standards with ease

Sentra gives CISOs, CDOs, and executives a proactive, scalable way to adopt GenAI safely, protecting the business before any model training even begins.

AI Governance Starts with Data Governance

AI governance for generative AI starts, and is won or lost, at the data layer. If organizations don’t find, classify, and secure sensitive data first, every other security measure remains reactive and ineffective. As generative AI, agent automation, and regulatory demands rise, a unified data governance strategy isn’t just good practice, it’s an urgent priority. Sentra gives security and business teams real control, making sure GenAI is secure, compliant, and trusted.

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