Today’s Topics:

• Microsoft Defender False Positive Shows How Certificate Trust Incidents Can Create Operational Confusion
• Vercel Breach Shows How OAuth Abuse and Token Theft Can Turn SaaS Access Into an Internal Security Problem
• How can Netizen help?

Microsoft Defender False Positive Shows How Certificate Trust Incidents Can Create Operational Confusion

Microsoft Defender’s recent false positive involving DigiCert root certificates is a good example of how security tooling can create real operational concern even when the original alert is not tied to an active infection on the affected device. The issue began after a Microsoft Defender signature update flagged legitimate DigiCert root certificate entries as Trojan:Win32/Cerdigent.A!dha, which led to widespread alerts across Windows environments and, in some cases, the removal of certificates from the Windows trust store. For administrators, the immediate problem was not just the alert itself, but the uncertainty it created around whether systems were compromised, misconfigured, or simply affected by a bad detection update.

The certificates reportedly flagged by Defender were DigiCert root certificate entries stored under HKLM\SOFTWARE\Microsoft\SystemCertificates\AuthRoot\Certificates\. On impacted systems, these entries were removed from the AuthRoot store, which raised obvious concerns for users and IT teams that rely on the Windows trust store for certificate validation. Some users reportedly believed their systems had been infected and even reinstalled Windows out of caution, which shows how disruptive false positives can become when they involve trusted system components rather than a suspicious executable or downloaded file.

Microsoft later confirmed that the false positives were connected to detection logic added after reports of compromised certificates tied to a recent DigiCert security incident. The company stated that Defender had added detections to help protect customers, but later determined that false positive alerts were being triggered and updated the alert logic. Microsoft also said customers should update to Security Intelligence version 1.449.430.0 or later and that no extra action was needed for those alerts.

The larger context matters here. DigiCert recently disclosed a security incident where a threat actor targeted a customer support team member and gained access to initialization codes for a limited number of code signing certificates. DigiCert stated that a small number of those certificates were then used to sign malware, and the affected certificates were revoked within 24 hours of discovery. The attacker reportedly used a malicious ZIP file disguised as a screenshot to compromise support staff, then abused access to a support environment that allowed staff to view customer accounts from the customer’s perspective.

That access gave the attacker what they needed to obtain EV code signing certificates across a limited set of approved orders. DigiCert later said it revoked 60 code signing certificates, including 27 connected to a malware campaign referred to as Zhong Stealer. Security researchers had already reported that certificates issued to well-known companies were being abused to sign malware, giving those payloads a greater appearance of legitimacy. This is where the incident becomes more serious from a defender’s perspective: signed malware can bypass user suspicion, complicate triage, and force security teams to treat certificate reputation as part of their threat model rather than a background trust function.

Still, the Defender false positive appears to have flagged DigiCert root certificates in the Windows trust store, not the revoked DigiCert code signing certificates used in the malware campaign. That distinction is important. A compromised or abused code signing certificate is a serious issue, but a root certificate being flagged and removed by endpoint protection introduces a different kind of risk. It can affect trust validation, trigger unnecessary incident response activity, and create confusion across endpoints that may otherwise be healthy.

Vercel Breach Shows How OAuth Abuse and Token Theft Can Turn SaaS Access Into an Internal Security Problem

Vercel’s latest update on its Context.ai-linked breach shows how quickly a compromise in one SaaS environment can become a broader access problem for another organization. The company said it found another small group of customer accounts that showed signs of compromise after it widened its investigation to include more indicators, network request activity, and environment variable read events in its logs. Vercel also found some customer accounts with signs of older compromise that appeared to predate the incident, meaning some of the suspicious access may have come from separate social engineering, malware, or credential theft activity.

The breach originally stemmed from a compromise involving Context.ai, a third-party AI tool that had been used by a Vercel employee. Once the attacker gained control of the employee’s Google Workspace account, they were able to use that access to reach the employee’s Vercel account. From there, the attacker moved into a Vercel environment and enumerated internal systems, including the decryption of non-sensitive environment variables. The detail that stands out here is not just that an account was compromised, but that trust relationships between cloud services helped extend the attacker’s reach.

Hudson Rock’s investigation adds another layer to the incident. According to its findings, a Context.ai employee was infected with Lumma Stealer in February 2026 after searching for Roblox auto-farm scripts and game exploit executors. If that infection was the starting point, then this incident becomes a clear example of how consumer malware, stolen tokens, and SaaS integrations can intersect in enterprise environments. What begins as malware on one employee’s system can become a path into business platforms when session tokens, OAuth grants, API keys, or browser-stored credentials are exposed.

Vercel CEO Guillermo Rauch also stated that threat intelligence points to malware being distributed to computers in search of valuable tokens, including keys tied to Vercel accounts and other providers. That matters for defenders because token theft does not always look like a normal password-based compromise. An attacker may not need to trigger a login failure, bypass MFA in a traditional way, or perform obvious brute-force activity. If they can steal a valid session or abuse an approved integration, they may appear to be operating through legitimate access paths.

This is also why the Context.ai connection raises questions about shadow AI in enterprise environments. It is still unclear whether the Vercel employee’s use of the Context AI Office Suite was formally approved, but the risk is the same either way. AI tools that connect to Google Workspace, Slack, GitHub, development platforms, or other internal services can inherit sensitive permissions from the user. If those tools are compromised, poorly reviewed, or abandoned, they can become another route into business systems. Context.ai has since deprecated the AI Office Suite, but the issue goes beyond one tool.

OAuth integrations are useful because they make SaaS platforms easier to connect and use. That same convenience creates risk when permissions are overly broad, app review is weak, or users authorize tools outside formal security review. An attacker who compromises an approved app or steals tokens tied to that app may avoid some of the controls that would apply to a direct account takeover. For security teams, that means SaaS identity risk needs to include connected applications, OAuth grants, environment variables, API keys, and token activity, not just usernames and passwords.

The Vercel incident also shows why environment variable access deserves more attention. Vercel said the attacker decrypted non-sensitive environment variables, but defenders should still treat environment variable reads as meaningful security events. In many development environments, environment variables can contain service endpoints, feature flags, deployment details, internal references, or sometimes secrets that should have been stored elsewhere. Even when the exposed data is considered non-sensitive, it can help an attacker understand architecture, map services, and plan the next step.

For SOC teams, the operational lesson is that SaaS incidents need fast scoping. Teams should be able to answer which accounts were accessed, which OAuth apps were authorized, which environment variables were read, which tokens were created or used, and whether any unusual API activity occurred after the first compromise. Waiting until after containment to build that picture leaves too much room for an attacker to move through connected systems.

Organizations should also review how they approve and monitor AI-connected SaaS tools. That review should include OAuth scopes, data access, vendor security posture, logging availability, app ownership, deprecation status, and whether the tool is still actively maintained. If employees can connect third-party AI tools to business accounts without review, the organization may not have a reliable inventory of which applications can touch internal data.

How Can Netizen Help?

Founded in 2013, Netizen is an award-winning technology firm that develops and leverages cutting-edge solutions to create a more secure, integrated, and automated digital environment for government, defense, and commercial clients worldwide. Our innovative solutions transform complex cybersecurity and technology challenges into strategic advantages by delivering mission-critical capabilities that safeguard and optimize clients’ digital infrastructure. One example of this is our popular “CISO-as-a-Service” offering that enables organizations of any size to access executive level cybersecurity expertise at a fraction of the cost of hiring internally. 

Netizen also operates a state-of-the-art 24x7x365 Security Operations Center (SOC) that delivers comprehensive cybersecurity monitoring solutions for defense, government, and commercial clients. Our service portfolio includes cybersecurity assessments and advisory, hosted SIEM and EDR/XDR solutions, software assurance, penetration testing, cybersecurity engineering, and compliance audit support. We specialize in serving organizations that operate within some of the world’s most highly sensitive and tightly regulated environments where unwavering security, strict compliance, technical excellence, and operational maturity are non-negotiable requirements. Our proven track record in these domains positions us as the premier trusted partner for organizations where technology reliability and security cannot be compromised.

Netizen holds ISO 27001, ISO 9001, ISO 20000-1, and CMMI Level III SVC registrations demonstrating the maturity of our operations. We are a proud Service-Disabled Veteran-Owned Small Business (SDVOSB) certified by U.S. Small Business Administration (SBA) that has been named multiple times to the Inc. 5000 and Vet 100 lists of the most successful and fastest-growing private companies in the nation. Netizen has also been named a national “Best Workplace” by Inc. Magazine, a multiple awardee of the U.S. Department of Labor HIRE Vets Platinum Medallion for veteran hiring and retention, the Lehigh Valley Business of the Year and Veteran-Owned Business of the Year, and the recipient of dozens of other awards and accolades for innovation, community support, working environment, and growth.

Looking for expert guidance to secure, automate, and streamline your IT infrastructure and operations? Start the conversation today.

Today’s Topics:

• OpenAI Expands Defensive AI Strategy with GPT-5.4-Cyber Release
• Mythos Is Accelerating Vulnerability Discovery, but Most Security Teams Are Not Built to Fix What It Finds
• How can Netizen help?

OpenAI Expands Defensive AI Strategy with GPT-5.4-Cyber Release

OpenAI has introduced GPT-5.4-Cyber, a specialized variant of its GPT-5.4 model built for defensive cybersecurity operations, signaling a continued push to embed AI directly into security workflows. The release arrives within days of Anthropic unveiling its competing frontier model, Mythos, reinforcing the pace at which major AI vendors are positioning models as core components of modern security programs.

GPT-5.4-Cyber is positioned as a tool for security teams responsible for identifying, validating, and remediating vulnerabilities across enterprise environments. The model is optimized for defensive use cases, with an emphasis on accelerating vulnerability discovery and enabling faster remediation across complex software ecosystems. This aligns with a broader industry trend where AI is being integrated earlier in the software development lifecycle, moving security closer to development rather than treating it as a downstream function.

Alongside the model release, OpenAI is expanding its Trusted Access for Cyber (TAC) program, scaling availability to thousands of vetted individual practitioners and hundreds of security teams. The program reflects a controlled distribution model, balancing broader access for defenders with safeguards intended to limit misuse. Access remains gated through authentication and vetting processes, which indicates that OpenAI is attempting to manage the inherent risks associated with deploying high-capability models in sensitive domains.

The dual-use nature of AI remains a central concern. Models designed to identify and fix vulnerabilities can be repurposed by adversaries to discover and exploit those same weaknesses before patches are applied. This inversion risk is not theoretical; it directly affects exposure windows for widely deployed software and increases the pressure on organizations to reduce mean time to remediation. OpenAI’s approach focuses on iterative deployment, where capabilities are released in stages while guardrails are strengthened to mitigate risks such as prompt injection, jailbreak attempts, and model manipulation.

A key component of this ecosystem is Codex Security, OpenAI’s AI-driven application security agent. The platform has already contributed to the remediation of over 3,000 critical and high-severity vulnerabilities, demonstrating how AI can operate as an active participant in secure development pipelines rather than a passive analysis tool. This reflects a shift from periodic security testing toward continuous validation, where vulnerabilities are identified and addressed in near real time as code is written.

Anthropic’s Mythos, introduced under Project Glasswing, represents a parallel effort to deploy AI for large-scale vulnerability discovery. Early results indicate that the model has identified thousands of flaws across operating systems, browsers, and other widely used software, suggesting that both vendors are converging on similar use cases with comparable impact potential. The competitive dynamic between these platforms is likely to accelerate advancements in AI-assisted security tooling, while also increasing scrutiny around governance and safe deployment.

The broader implication is a transition from episodic security assessments to continuous, AI-assisted risk reduction. By embedding models like GPT-5.4-Cyber directly into development and security workflows, organizations gain immediate feedback on vulnerabilities during the build process, reducing reliance on post-deployment audits. This approach compresses the vulnerability lifecycle, limits exposure windows, and aligns security more closely with operational tempo.

For security teams, the value lies in scale and speed. AI models can analyze large codebases, correlate findings, and propose remediation steps far faster than traditional methods. At the same time, the introduction of these tools raises expectations around how quickly organizations can respond to risk. The advantage shifts toward teams that can operationalize these capabilities effectively, integrating them into existing pipelines without introducing new attack surfaces

Mythos Is Accelerating Vulnerability Discovery, but Most Security Teams Are Not Built to Fix What It Finds

Anthropic’s Claude Mythos preview has quickly become a focal point in security discussions due to its ability to identify vulnerabilities at a scale that traditional testing approaches cannot match. Early analysis points to a system capable of scanning large environments and surfacing issues with a level of speed and depth that changes expectations around coverage. The conversation has focused heavily on access, competitive advantage, and adversarial risk, but the more immediate issue is operational, what happens after the findings are generated.

The core problem is the gap between discovery and remediation. Security programs have historically struggled with this even at lower volumes. A penetration test surfaces a handful of critical findings; those findings get distributed across tickets, reports, or spreadsheets; ownership becomes unclear; validation of fixes is inconsistent. That process already breaks down under moderate load. When AI systems like Mythos increase discovery output by an order of magnitude, that same workflow does not scale and instead collapses under backlog pressure.

This is where the impact of Mythos becomes less about detection capability and more about organizational readiness. Faster discovery without parallel improvements in triage, prioritization, and remediation workflows leads to accumulation of unresolved risk. Findings become inventory rather than action. Security teams may have better visibility into weaknesses, but that visibility does not translate into reduced exposure if fixes are delayed, deprioritized, or never validated.

Concerns around false positives compound the issue. Bruce Schneier has pointed out that the reported accuracy rates for Mythos are based on curated outputs rather than full-scale operational runs. In practice, high-performing detection systems tend to generate plausible but incorrect findings alongside valid ones. Each false positive carries a cost; it requires analysis, triage, and dismissal. At scale, that overhead can consume the same engineering bandwidth that would otherwise be used to remediate confirmed vulnerabilities. The net effect is not efficiency, but redistribution of effort.

The organizations best positioned to benefit from this shift already have mature internal infrastructure. They operate centralized systems for managing findings across sources, allowing vulnerability data to exist in a structured, queryable format rather than fragmented across tools. They prioritize based on business context rather than raw severity scores, distinguishing between theoretical risk and actual exposure. Most importantly, they maintain closed-loop remediation processes where findings are tracked from discovery through verified resolution, with re-testing built into the workflow rather than treated as optional.

Without these capabilities, increased discovery velocity becomes a liability. Security teams accumulate large volumes of high-severity findings with no reliable way to determine which ones matter most or whether remediation efforts are effective. The result is a growing backlog of risk that is documented but not reduced. This is the operational reality many teams will face as AI-driven discovery tools become more common.

Access constraints introduce another dimension. Anthropic’s controlled rollout under Project Glasswing concentrates early use among large enterprises with existing resources to act on findings. This creates an uneven distribution of defensive capability, where organizations already equipped to respond gain further advantage. Smaller teams face a different problem; even if access expands, many lack the internal processes required to translate AI-generated findings into completed remediation work. The limitation is not just access to tools, but the ability to operationalize their output.

How Can Netizen Help?

Founded in 2013, Netizen is an award-winning technology firm that develops and leverages cutting-edge solutions to create a more secure, integrated, and automated digital environment for government, defense, and commercial clients worldwide. Our innovative solutions transform complex cybersecurity and technology challenges into strategic advantages by delivering mission-critical capabilities that safeguard and optimize clients’ digital infrastructure. One example of this is our popular “CISO-as-a-Service” offering that enables organizations of any size to access executive level cybersecurity expertise at a fraction of the cost of hiring internally. 

Netizen also operates a state-of-the-art 24x7x365 Security Operations Center (SOC) that delivers comprehensive cybersecurity monitoring solutions for defense, government, and commercial clients. Our service portfolio includes cybersecurity assessments and advisory, hosted SIEM and EDR/XDR solutions, software assurance, penetration testing, cybersecurity engineering, and compliance audit support. We specialize in serving organizations that operate within some of the world’s most highly sensitive and tightly regulated environments where unwavering security, strict compliance, technical excellence, and operational maturity are non-negotiable requirements. Our proven track record in these domains positions us as the premier trusted partner for organizations where technology reliability and security cannot be compromised.

Netizen holds ISO 27001, ISO 9001, ISO 20000-1, and CMMI Level III SVC registrations demonstrating the maturity of our operations. We are a proud Service-Disabled Veteran-Owned Small Business (SDVOSB) certified by U.S. Small Business Administration (SBA) that has been named multiple times to the Inc. 5000 and Vet 100 lists of the most successful and fastest-growing private companies in the nation. Netizen has also been named a national “Best Workplace” by Inc. Magazine, a multiple awardee of the U.S. Department of Labor HIRE Vets Platinum Medallion for veteran hiring and retention, the Lehigh Valley Business of the Year and Veteran-Owned Business of the Year, and the recipient of dozens of other awards and accolades for innovation, community support, working environment, and growth.

Looking for expert guidance to secure, automate, and streamline your IT infrastructure and operations? Start the conversation today.

Today’s Topics:

• Vercel April 2026 Security Incident Exposes OAuth Risk and Developer Supply Chain Concerns
• Anthropic MCP Design Flaw Introduces Systemic RCE Risk Across the AI Supply Chain
• How can Netizen help?

Vercel April 2026 Security Incident Exposes OAuth Risk and Developer Supply Chain Concerns

Vercel disclosed a security incident in April 2026 involving unauthorized access to internal systems, tracing the intrusion back to a compromised third-party AI tool and a single employee account that became an entry point into its environment. The attack chain is direct and uncomfortable; a breach at Context.ai led to the compromise of an OAuth token, which was then used to take over a Vercel employee’s Google Workspace account, ultimately granting access into internal systems and environment variables that were not classified as sensitive.

The scope appears contained for now, with Vercel stating that only a limited subset of customer credentials were impacted and that affected users were contacted directly. The company maintains that environment variables explicitly marked as sensitive were not accessed, due to how those values are stored and protected. What remains unresolved is whether any data was exfiltrated, which Vercel is still investigating with support from incident response firms and law enforcement.

The more important takeaway is how the attacker moved. This was not a noisy intrusion; it relied on legitimate access paths and delegated trust. The OAuth token, granted overly broad permissions, effectively acted as a master key. Once inside the employee’s Google Workspace account, the attacker was able to pivot into Vercel systems and enumerate non-sensitive environment variables. That classification boundary became the difference between protected secrets and exposed operational data, which in practice can still carry meaningful risk depending on how those variables are used.

External reporting adds another layer of concern. Researchers noted that the attacker may have accessed credentials such as GitHub or npm tokens, which introduces the possibility of downstream supply chain abuse if not rotated quickly. The theoretical impact here is significant; access to publishing pipelines for widely used frameworks like Next.js could allow malicious updates to propagate across a large portion of the web ecosystem. There is no evidence that such an outcome occurred, though the scenario underscores how little separation exists between developer tooling and production risk.

The initial access vector also exposes a broader issue with OAuth governance. Context.ai’s compromise did not directly target Vercel, yet a single user granting “Allow All” permissions created a bridge between an external SaaS tool and a high-value internal environment. That pattern is common across modern development stacks, where convenience-driven integrations accumulate privileges over time with minimal review. Once an attacker obtains a token, they inherit those permissions without needing to bypass traditional authentication controls.

Vercel has published a single indicator of compromise tied to the malicious OAuth application and is advising organizations to audit Google Workspace integrations immediately. The guidance itself is standard but necessary; review activity logs, rotate any environment variables that may have been exposed, and reassess which values are classified as sensitive. The incident also prompted recommendations around deployment controls and token rotation, particularly for systems that rely on automated pipelines.

What stands out is not the breach itself, but the path it took. This was not a vulnerability in Vercel’s core infrastructure; it was a failure in trust boundaries between identity, third-party integrations, and internal access controls. The attacker did not need to exploit code; they used permissions exactly as configured. For organizations running similar stacks, that distinction matters. OAuth tokens, CI/CD credentials, and environment variables are increasingly part of the same attack surface, and a weakness in one area can cascade into all three.

Vercel’s services remain operational, and the company continues to monitor for further indicators of compromise. The longer-term impact will depend on how widely exposed credentials were reused across developer environments and whether any downstream abuse emerges. For now, the incident sits in a familiar category; identity-driven access, third-party exposure, and a chain of trust that held until it didn’t.

Anthropic MCP Design Flaw Introduces Systemic RCE Risk Across the AI Supply Chain

A structural weakness in the Model Context Protocol has introduced a remote code execution condition that propagates across a large portion of the AI development stack, affecting thousands of deployments and widely used frameworks. Researchers found that the issue is not an isolated implementation bug but a direct result of how MCP handles configuration and command execution through its STDIO interface, creating a pathway where arbitrary operating system commands can be executed under the right conditions.

The exposure is broad. The flaw exists within the official SDK released by Anthropic and extends across multiple supported languages, including Python, TypeScript, Java, and Rust. That design decision has cascaded into more than 7,000 publicly accessible servers and software packages with over 150 million downloads, embedding the same execution risk into projects that rely on MCP for tool orchestration and agent communication.

At the technical level, the issue stems from how MCP initializes and interacts with STDIO-based services. The protocol was intended to allow a local server process to be spawned and then interfaced with through a controlled input-output channel. In practice, the mechanism does not adequately restrict what can be executed. If a command successfully initializes a server, it returns a valid handle; if not, the command still executes before returning an error. That behavior creates a gap where command execution occurs regardless of whether the operation is considered valid by the protocol, effectively turning configuration input into an execution vector.

This design flaw has already surfaced in multiple downstream implementations. A cluster of CVEs across projects such as LiteLLM, LangChain, Flowise, and others reflects the same root condition; command injection via MCP configuration paths, often without authentication. Attack paths include direct STDIO manipulation, configuration tampering through prompt injection, and exploitation of MCP marketplaces where remote configurations can be introduced without user interaction. In several cases, the attack can be triggered without any explicit user action, relying instead on how LLM-driven workflows process and execute instructions.

The response from Anthropic introduces a separate concern. The behavior has been classified as expected within the protocol design, leaving responsibility with developers to implement safeguards at the application level. Some vendors have issued patches for their own integrations, yet the underlying execution model remains unchanged in the reference implementation. That creates a scenario where fixes are fragmented and inconsistent, and where new projects adopting MCP inherit the same risk profile by default.

What distinguishes this from a typical vulnerability disclosure is its scale and propagation model. This is not a single flaw tied to a specific codebase; it is an architectural condition that has been replicated across ecosystems through SDK adoption. Each integration point compounds the exposure, and each downstream project becomes another potential execution surface. The result is a supply chain issue in the truest sense; a single design decision embedded into the protocol has distributed execution risk across the entire AI tooling ecosystem.

From a defensive standpoint, mitigation is less about patching a single component and more about redefining trust boundaries. Systems running MCP-enabled services need to treat all external configuration as untrusted input, restrict network exposure, and isolate execution environments through sandboxing or containerization. Monitoring becomes equally important, particularly around MCP tool invocation patterns and unexpected process execution. Controls that would normally be applied to traditional command execution interfaces now need to be extended into AI orchestration layers.

This incident reinforces a pattern already emerging in AI security. As orchestration frameworks and agent-based systems become more common, the boundary between configuration and execution continues to blur. MCP collapses that boundary entirely in certain cases, allowing inputs that appear declarative to produce direct system-level effects. Once that model is adopted at scale, a single oversight in protocol design can move far beyond one vendor or one product and become embedded across an entire supply chain.

How Can Netizen Help?

Founded in 2013, Netizen is an award-winning technology firm that develops and leverages cutting-edge solutions to create a more secure, integrated, and automated digital environment for government, defense, and commercial clients worldwide. Our innovative solutions transform complex cybersecurity and technology challenges into strategic advantages by delivering mission-critical capabilities that safeguard and optimize clients’ digital infrastructure. One example of this is our popular “CISO-as-a-Service” offering that enables organizations of any size to access executive level cybersecurity expertise at a fraction of the cost of hiring internally. 

Netizen also operates a state-of-the-art 24x7x365 Security Operations Center (SOC) that delivers comprehensive cybersecurity monitoring solutions for defense, government, and commercial clients. Our service portfolio includes cybersecurity assessments and advisory, hosted SIEM and EDR/XDR solutions, software assurance, penetration testing, cybersecurity engineering, and compliance audit support. We specialize in serving organizations that operate within some of the world’s most highly sensitive and tightly regulated environments where unwavering security, strict compliance, technical excellence, and operational maturity are non-negotiable requirements. Our proven track record in these domains positions us as the premier trusted partner for organizations where technology reliability and security cannot be compromised.

Netizen holds ISO 27001, ISO 9001, ISO 20000-1, and CMMI Level III SVC registrations demonstrating the maturity of our operations. We are a proud Service-Disabled Veteran-Owned Small Business (SDVOSB) certified by U.S. Small Business Administration (SBA) that has been named multiple times to the Inc. 5000 and Vet 100 lists of the most successful and fastest-growing private companies in the nation. Netizen has also been named a national “Best Workplace” by Inc. Magazine, a multiple awardee of the U.S. Department of Labor HIRE Vets Platinum Medallion for veteran hiring and retention, the Lehigh Valley Business of the Year and Veteran-Owned Business of the Year, and the recipient of dozens of other awards and accolades for innovation, community support, working environment, and growth.

Looking for expert guidance to secure, automate, and streamline your IT infrastructure and operations? Start the conversation today.