Federal Tech Podcast: for innovators, entrepreneurs, and CEOs who want to increase reach and improve brand awareness

The discussion explained how Fivecast uses open-source intelligence to support investigations, emphasizing targeted collection, privacy safeguards, and human analysis.

Our guest is Tony D'Angelo from Fivecast. He begins the interview by noting that today we are bombarded with data. Finally, AI tools can develop those relationships and connect the dots.

That can be impressive for a federal agency, but it takes a human to connect the dots and summarize what those relationships mean.

D'Angelo goes on to show that there is a difference between monitoring an early warning. Some systems observe a situation and store it. Innovative companies can take a more subtle approach, look for nuances, and filter through weak signals to establish an early warning.

The discussion explained how Fivecast applies open-source intelligence to support investigations while emphasizing targeted collection, privacy safeguards, and human analysis.

If you would like more information, Fivecast is hosting an event in Washington, DC, on February 18, 2027, called Illuminate. You can meet subject matter experts to discuss your unique challenges in applying AI to investigations.

The discussion presented Symmatrics' one-time-pad symmetric-key approach as a proposed response to AI-driven credential attacks and future quantum threats.

During the interview, Drew Davis from Symmantrics puts this discussion into perspective. In the early days of the Internet, a mathematician named Shannon proved mathematically that the one-time pad achieves "perfect secrecy." One weakness of this method is that it can't scale for the rapidly growing Internet.

Recently, Symmatrics has developed an innovative approach to applying this one-time pad encryption to today's Internet. Rather than dive into mathematical details, Davis says this approach can resist newer cryptologic threats like AI and quantum computing.

The company claims its protocol can securely distribute up to 8 million keys per second and support applications, APIs, devices, and quantum-secure VPN deployments.

Unlike modern public-key systems like RSA, which rely on math problems that quantum computers can solve, their system relies on random bits, making it immune to quantum attacks.

The federal government has legacy systems that house large amounts of data that must be secured. Symmantrics' solution can help agencies maintain continuity and security while modernizing.

We recently sat down with leaders from Elastic and Google Cloud to discuss how their joint capabilities empower organizations to run high-assurance cybersecurity, local AI operations, and resilient workloads within sovereign, air-gapped environments.

Air-gapping is one of the strongest security measures an organization can put in place. But as Sean MacKirdy from Elastic points out, running an isolated system comes with a unique practical challenge. Systems that are completely cut off from the public internet can't rely on traditional cloud tools for live updates, threat feeds, or automatic patches. At the same time, threats don't stop at the perimeter and risks like software supply chains, data transfers, and USB drives still need to be caught and managed on-site. When organizations need the highest level of protection possible, both types of risk need to be mitigated.

That's where the partnership between Elastic and Google Distributed Cloud comes in.

Data transfers, cross-domain guards, patching cycles, supply chains, USB devices, and insiders remain potential entry points. Google Cloud's TJ Banasik highlights why a meaningful solution to addressing these threat vectors is to consolidate tools. Elastic Security now has a deep integration with Google Distributed Cloud air-gapped, providing a hardened architecture for organizations handling highly sensitive, regulated workloads to use Elastic's agentic security operations platform. This joint solution delivers:

● Complete Visibility on One Platform: It unifies endpoint detection (EDR/XDR), user behavior analytics, and vulnerability tracking in one place so teams aren't juggling multiple disconnected consoles.

● Built-in Automation and AI: Teams get automated alert triage and detection that run entirely locally, speeding up response times and cutting down on alert fatigue without any data ever leaving the facility.

● Less Overhead for Analysts: By handling heavy lifting on-site, it helps smaller security teams run a fast, modern SOC without needing constant internet reach-back.

This interview provides an overview of the concepts discussed. For more details, please attend the Google Public Sector Summit on October 20, 2026, at the Reagan Center in Washington, D.C. You'll see how Elastic and Google Distributed Cloud work together, with subject matter experts in the room with you.

Federal agencies must consider how to protect air-gapped networks amid regulatory authorization, data sovereignty, and operational risk. That is why it is important to meet face-to-face with developers from Elastic and Google Cloud to determine the optimized solution for your agency. The Google Public Sector Summit presents the perfect opportunity to accomplish that task.

Learn more about Elastic Security for Google Distributed Cloud air-gapped: https://www.elastic.co/blog/google-distributed-cloud-air-gapped-environments

Register for the Google Public Sector Summit on October 20: https://events.govexec.com/google-public-sector-summit/

Looking back over decades of defending against cyberattacks, we see initial attempts at moats and protective walls being demolished by malicious actors. The next trend is the promise of Zero Trust. One could assume that AI-driven attacks will be able to overcome this verification system.

Today, we look at a new approach to protecting federal data: risk reframing. In our discussion with Beth Miller from Mimecast, she highlights the importance of visibility, including broad coverage, and establishing behavioral baselines.

One mistake Miller sees is organizations diving into adherence and detection before making sure they have a complete view of the system. This includes basic inventory before considering OMB's mandating governance.

Because identities are easy to steal, even a strong Zero Trust environment can still pose risks. Miller argues that understanding behavior patterns is essential to protecting data. Once a baseline is established, behavioral signals can flag suspicious activity.

Instead of being dazzled by agents, Miller suggests a more sober approach. Apply identity and access to agents as you would to humans. Today, we see agents that are not systematically governed.

Miller recommends a newer response approach. Risk responses may include transferring, exploiting, accepting, avoiding, or mitigating risk rather than defaulting only to mitigation.

Listen to the podcast to better understand how federal agencies can manage human risk, shadow AI, behavioral drift, and data loss through better visibility.

SAS has led data management for the federal government for over fifty years. We face a new technology that tightly integrates data and AI.

Today, we sit down with Reggie Townsend to get his ideas on human involvement in AI and review a new report, the 2026 Data and AI Impact Report.

AS's 2026 Data and AI Impact Report, based on IDC research, finds that trustworthy AI is strongly associated with better business results. Organizations with strong governance, data quality, auditability, and explainability practices were 15 times more likely to report strong AI ROI.

Nearly all users—97.2%—override AI recommendations at least occasionally, with lack of explanation the leading reason. Trust also declines as AI becomes more autonomous. Only 17.5% of enterprises have data infrastructure mature enough for agentic AI.

The study, covering 2,699 decision-makers across 28 countries, concludes that strong data foundations and trustworthy AI practices are essential for successfully scaling AI.

During the interview, Townsend tempers this information with comments about a human component, typically called getting the human in the loop. He begins by noting that humans are part of the solution, then comments on federal involvement.

Townsend thinks government involvement in evaluating AI capabilities may be warranted to protect citizens.

Malicious cyber-attacks are increasingly driven by AI and identity vulnerabilities. Today, we sat down with Adam Meyers from CrowdStrike to detail this acceleration and offer some solutions.

Attack Acceleration

Meyers highlights a significant decrease in breakout time, which is the duration between initial access and lateral movement.

• In 2024, the average breakout time was 48 minutes.
• By 2025, this decreased to an average of 29 minutes, with the fastest recorded at 27 seconds.

One reason for these attacks is strategic. Current defenses often focus heavily on endpoints while neglecting identity and cloud control planes. Specifically, organizations must monitor many issues.

For example, unauthorized users provisioning new multi-factor authentication (MFA) devices. Also, impossible travel scenarios where logins occur from disparate geographic locations in impossible timeframes.

During the interview, Meyers expands on the concept of "cross-domain hunting." They must constantly switch between roles—such as threat hunting and incident response—across various tools and screens, contributing to burnout rates comparable to air traffic controllers or EMTs.

Emerging Trends

AI is driving a massive increase in vulnerability discovery; CVE publications in June 2026 were up 96% compared to June 2025. Additionally, machines now generate two and a half times as many detections as humans.

The conclusion is that AI will be able to fight AI in cybersecurity. It may be a rocky road, but it will balance the threat in the end.

Years ago, the phrase "big data" entered the vocabulary of federal technology leaders. Please note, it was not "accurate" data; it was not "significant" data, just big.

Today, we sat down with Monty Montgomery from Island to get some insight into best practices for protecting data in modern federal systems. He expands on concepts like data valuation, zero trust implementation, and AI integration.

Data.

Monty begins by stating the obvious: not all data is equal; protecting low-value information like hobbies is inefficient compared to protecting high-value assets like Social Security numbers or banking details. Further, agencies often struggle with "data buckets" that treat all information as having uniform value, which leads to misallocated labor hours.

Zero Trust Implementation

The conversation highlights a shift from traditional perimeter security to a more granular, user-centric Zero Trust Architecture. Monty notes that monolithic, multi-billion-dollar network stacks often fail because they are too rigid; instead, agencies should adopt tools that move closer to the user and allow for rapid iteration.

AI Integration

The emergence of generative AI introduces new paradigms for both data protection and potential vulnerabilities. Best practice is for agencies to run experiments to "fail fast," allowing them to learn from unsuccessful attempts rather than committing to inflexible, large-scale failures.

Listen to the interview to gain insight into protecting data at rest, data in transit, and data in use.

When most federal technology leaders look at preventing cybersecurity attacks, they rarely go beyond the network. Today we are looking at a new breach vector: the resume.

Patricia Titus from Abnormal AI begins the interview with a shocking story about a recently discovered exploit. In the summer of 2026, the FBI confirmed that a North Korean operative spent months working inside a federal agency as an authorized employee.

Because of this incident, Titus makes the case for why the security perimeter must extend upstream to the resume.

During the interview, she details how VOIP numbers are used to mask origins. Beyond that, advances in voice duplication (vishing) allow HR personnel to be duped. Not only that, but today's AI technology allows a single actor to manage several accounts.

In other words, today we have a scenario playing out where a naïve hiring manager can have several fake resumes from the same individual competing for the same position. Once a system is compromised, lateral movements are enabled to gain access to sensitive areas of the network.

There are attempts to block this system, commonly called Application Tracking Systems (ATS). Gaps in the ability of this system can be addressed by establishing a formal partnership between the cybersecurity team and the HR department. From there, behavioral patterns can be used to detect abnormal patterns.

The conclusion is obvious; can public sector leaders effectively validate identity without relying solely on automated systems that may be deceived by high-quality synthetic data?

Today, we sat down with leaders from Elastic and Google Distributed Cloud to discuss how their unique combination of skills can address cybersecurity, AI operations, and resilience in sovereign air-gapped environments.

Most listeners hear the phrase "air-gapped" and think absolute safety. Sean MacKirdy from Elastic offers insight into air-gapped environments. He reminds the audience that, by definition, an air-gapped system cannot get updates from the Internet. That means they are vulnerable to attacks.

Further, data transfers, cross-domain guards, patching cycles, supply chains, USB devices, and insiders remain potential entry points.

Google's TJ Banasik's solution is to consolidate tools. For example, common tools include capabilities like endpoint detection, user behavior analytics, and vulnerability management. Elastic Security can be combined with Google Distributed Cloud.

For example, Elastic uses specialized, self-managed platforms to provide unified security for air-gapped environments. This automation reduces fatigue, staffing requirements, response time, and integration complexity in a SOC.

This interview provides a brief overview of the concepts discussed. For more details, please attend the Google Public Sector Summit on October 20, 2026, at the Reagan Center in Washington, DC. You'll see how Elastic and Google Distributed Cloud work together, with subject matter experts in the room with you.

Federal agencies must consider how to protect air-gapped networks amid regulatory authorization, data sovereignty, and operational risk. That is why it is important to meet face-to-face with developers from Elastic and Google to determine the optimized solution for your agency. The Google Public Sector Summit presents the perfect opportunity to accomplish that task.

Michael Crossland, Solutions Engineer for National Security Programs at DTEX Systems, discussed the evolution and importance of insider threat protection in the federal government.

DTEX, with over 20 years of experience, focuses on data capture and telemetry to enhance risk and behavioral awareness. Crossland makes the argument that behavior is key to reducing the cybersecurity risk.

Crossland emphasized the challenges of managing remote workforces post-2020 and the role of AI in both productivity and security risks. Because of the DTEX experience, they can draw from a wide background to be able to move from reacting to an attack to being able to have proactive insider-risk detection.

He highlighted the significance of metadata in understanding user behavior and the need for privacy-first approaches.

Crossland also touched on the future of cybersecurity, predicting a continued focus on AI and behavioral analytics to stay ahead of threats.