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A critical cybersecurity lapse at Home Depot allowed access to internal systems for roughly a year, after an employee mistakenly published a private GitHub access token online. Security researcher Ben Zimmermann discovered the exposure in early November 2025 and attempted to alert Home Depot privately, but the company initially did not respond.

The token, which had been exposed since early 2024, granted access to hundreds of private Home Depot repositories hosted on GitHub. According to Zimmermann, it provided full access to the company’s cloud infrastructure, including order fulfillment, inventory management, and code development pipelines.

Zimmermann noted that he reached out multiple times via email and even LinkedIn to Home Depot’s Chief Information Security Officer, Chris Lanzilotta, but received no response. The lack of a formal vulnerability disclosure or bug bounty program at Home Depot left the researcher with no official reporting channel. Ultimately, TechCrunch’s outreach prompted Home Depot to revoke the token and secure the exposed systems.

“Home Depot is the only company that ignored me,” Zimmermann told TechCrunch, contrasting the response from other firms who have thanked him for similar disclosures. The company has not commented on whether any unauthorized parties accessed internal systems during the exposure.

The incident highlights a growing issue in corporate cybersecurity: organizations increasingly rely on cloud-hosted development infrastructure, but many lack formal mechanisms to identify and remediate leaked credentials. Access tokens, if publicly available, can allow attackers to modify code, compromise operational systems, or disrupt critical workflows.

As companies continue to digitize operations and rely on GitHub and other developer platforms, establishing clear vulnerability reporting channels and proactive monitoring becomes essential. Home Depot’s delayed response underscores the risk when such protocols are absent.

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The cybersecurity world just got another wake-up call. Deepwatch, a security company known for its AI-powered detection and response platform, has laid off roughly 80 employees out of its 250-person team. The company says the move is about “accelerating investments in AI and automation.”

For many in the field, it’s a sign of a bigger shift happening across the cybersecurity industry — one where traditional analyst-heavy teams are giving way to AI-driven platforms that promise faster detection and fewer human bottlenecks.

The story behind the layoffs

In an email to TechCrunch, Deepwatch CEO John DiLullo explained that the company is “aligning our organization to accelerate our significant investments in AI and automation.”

Employees inside the company painted a more complicated picture. One current staffer told TechCrunch that the layoffs “feel like an AI reshuffle more than a clear product plan.” The move comes as Deepwatch develops new “agentic AI” features that supposedly make its security platform more autonomous though insiders say details are still unclear.

Eight former employees have already announced their departures on LinkedIn. The total reduction, between 60 and 80 workers, represents a major downsizing for a company that had been growing steadily over the last few years.

A broader cybersecurity reset

Deepwatch isn’t alone. 2025 has seen a string of cybersecurity layoffs, even as demand for threat defense keeps rising.

Earlier this year, CrowdStrike cut about 5% of its workforce, despite posting record revenue and cash flow. Other firms, including Deep Instinct, Otorio, ActiveFence, SkyBox Security, and Sophos, have also reduced headcount.

At first glance, that might sound like an industry contraction. But the deeper story is a realignment. Security platforms are increasingly being rebuilt with AI automation at the core, aiming to do what used to require entire SOC teams.

The pitch is simple: AI models can flag anomalies faster, handle repetitive triage work, and even automate response playbooks. That means fewer humans, more software, and a new kind of efficiency that’s starting to define the next phase of cybersecurity.

What it means for the future of cybersecurity work

The shift comes with big questions for cybersecurity professionals. What happens when AI becomes the analyst?

For now, most companies still rely on human oversight, but the ratio is changing. Fewer people are being hired to monitor dashboards. More are being asked to train AI models, review outputs, and handle only the complex or ambiguous cases.

In the near future, the cybersecurity job market may look less like traditional operations centers and more like data science and model management teams. The people who stay will be those who understand both domains: security and machine learning.

This mirrors what’s happening in other tech sectors, where AI adoption doesn’t eliminate roles immediately it reshapes them.

The bigger picture

If this sounds familiar, it’s because this same pattern has played out before, when cloud automation replaced on-prem infrastructure jobs, and when DevOps merged development and operations.

The cybersecurity industry is now undergoing its own version of that shift. Deepwatch’s layoffs aren’t an isolated event; they’re a preview of what happens when security meets automation at scale.

Over the next few years, expect more platforms that market themselves as “AI-native,” fewer manual SOC workflows, and a growing divide between traditional analysts and the next generation of cyber-AI engineers.