In the rapidly evolving landscape of cybersecurity, a new threat has emerged that exploits the very tools designed to enhance productivity: generative AI coding assistants. Dubbed “slopsquatting,” this insidious supply chain attack leverages AI-hallucinated package names to infiltrate systems with malicious code, posing a significant risk to organizations worldwide. For CXOs and security experts, understanding and mitigating this threat is critical to safeguarding enterprise software ecosystems. This deep-dive article explores the mechanics of slopsquatting, its implications for the Consumer Packaged Goods (CPG) industry amidst current tariff challenges, and actionable strategies to protect against this novel attack vector.

What is Slopsquatting?

Slopsquatting is a supply chain attack where threat actors create malicious packages on public indexes using names that AI models hallucinate—names that resemble popular libraries but do not actually exist. The term, coined by security researcher Seth Larson, draws a parallel to typosquatting, where attackers register misspelled domain names to deceive users. However, slopsquatting flips the script: instead of exploiting human error, it capitalizes on the generative AI’s tendency to invent non-existent dependencies.

Generative AI tools, such as large language models (LLMs) used in coding assistants like GitHub Copilot or ChatGPT, are increasingly relied upon by developers to accelerate software development. These tools can generate code snippets, complete functions, and even suggest dependencies based on the context of a prompt. However, LLMs are prone to “hallucination”—fabricating information that appears plausible but is factually incorrect. Research from Socket, a software supply chain security firm, found that approximately 20% of AI-generated code references non-existent packages. When a developer unknowingly uses such a hallucinated package name and attempts to install it via a package manager like npm or pip, an attacker who has preemptively registered that name on a public registry can deliver malicious code directly into the developer’s environment.

The mechanics of slopsquatting are chillingly simple. An attacker monitors AI-generated code outputs—either by analyzing public repositories or prompting LLMs themselves—to identify commonly hallucinated package names. They then register these names on public package indexes such as PyPI (Python Package Index) or npm, uploading malicious packages that can execute harmful code when installed. This code might steal sensitive data, install backdoors, or even disrupt operations, all while masquerading as a legitimate dependency.

A notable example involves a threat actor known as “_Iain,” who automated the creation of malicious packages targeting developers by exploiting hallucinated names. This automation underscores the scalability of slopsquatting attacks, making them a low-effort, high-reward strategy for cybercriminals. As generative AI becomes more ingrained in development workflows—used by over 92% of developers according to a 2024 Stack Overflow survey—the attack surface for slopsquatting continues to grow.

Slopsquatting in the Context of CPG: A Perfect Storm

For leaders in the CPG industry, slopsquatting arrives at a particularly precarious time. As detailed in a recent article on tariff challenges, CPG companies are already grappling with supply chain disruptions due to escalating trade tensions. With U.S. tariffs on Chinese imports at 145% and China’s retaliatory tariffs at 125%, costs are soaring, and consumer spending on CPG goods is declining. Amidst these pressures, a cybersecurity breach caused by slopsquatting could exacerbate vulnerabilities, disrupt operations, and erode consumer trust at a moment when resilience is paramount.

CPG companies often rely on complex software ecosystems to manage supply chains, track inventory, and engage with consumers. Many of these systems are developed or maintained using modern DevOps practices, which increasingly incorporate AI-driven tools to accelerate development cycles. A slopsquatting attack in this context could have devastating consequences. For instance, a malicious package installed in a supply chain management system might leak sensitive data about sourcing strategies, giving competitors an edge in navigating tariff-impacted markets. Alternatively, it could disrupt inventory tracking, leading to stockouts at a time when consumers are already stockpiling goods to preempt tariff-driven price hikes.

Moreover, the CPG sector’s reliance on third-party vendors and open-source software amplifies the risk. A single compromised dependency in a vendor’s codebase could cascade through the supply chain, affecting multiple stakeholders. Posts on X highlight that smaller CPG companies are already outpacing larger ones by adapting quickly to consumer needs, often through rapid software innovation. However, this agility often comes at the cost of rigorous security checks, making them prime targets for slopsquatting attacks. Larger CPG firms, while better resourced, are not immune—their complex, legacy systems and risk-averse cultures can slow down the adoption of security best practices, leaving them vulnerable.

The Broader Cybersecurity Landscape

Slopsquatting is part of a broader wave of supply chain attacks that have plagued the tech industry in recent years. High-profile incidents like SolarWinds (2020) and Log4Shell (2021) demonstrated the devastating impact of compromised dependencies. Slopsquatting, however, introduces a new dimension by exploiting AI-driven workflows, which are becoming ubiquitous across industries. The attack vector’s novelty has caught the attention of cybersecurity experts and policymakers alike. Legislators in the U.S. and Europe are drafting “secure-by-design” mandates that could hold vendors liable for shipping AI-generated code without proper vetting, signaling a potential shift in regulatory expectations.

The predictability of AI hallucinations makes slopsquatting particularly dangerous. Security researcher Seth Larson notes that these hallucinations are “low-hanging fruit” for adversaries, as attackers can systematically identify and register hallucinated names with minimal effort. Hackaday’s community has pointed out the futility of restricting LLMs to only generate code with known libraries, as attackers can simply publish malicious packages under those “known” names first. This cat-and-mouse game underscores the need for proactive, rather than reactive, cybersecurity measures.

Implications for CXOs and Security Experts

For CXOs, slopsquatting poses both strategic and operational challenges. At a strategic level, a successful attack could lead to financial losses, reputational damage, and regulatory scrutiny—particularly for CPG companies already strained by tariff-related cost increases. Operationally, it demands a reevaluation of development practices, third-party risk management, and incident response protocols. Security experts, meanwhile, must contend with the technical complexities of detecting and mitigating these attacks, which often blend seamlessly into legitimate workflows.

The financial implications are stark. A supply chain attack can cost millions in remediation, legal fees, and lost business. For CPG companies, where margins are already under pressure due to tariffs, such an incident could be catastrophic. Moreover, the reputational damage—especially if consumer data is compromised—could erode trust at a time when consumer confidence is already at a four-year low of 92.9. Regulatory risks are also significant, as data breaches often trigger investigations under frameworks like GDPR or CCPA, which can result in hefty fines.

From a technical perspective, slopsquatting is difficult to detect because it exploits the trust developers place in AI tools. Traditional security measures like signature-based malware detection may fail to flag these packages, as they are often custom-built for specific targets. Moreover, the open-source nature of public package registries makes them a breeding ground for such attacks, as anyone can upload a package with minimal oversight.

Actionable Strategies to Mitigate Slopsquatting

To combat slopsquatting, CPG leaders and security experts must adopt a multi-layered approach that integrates technology, policy, and education. Here are five key strategies:

1. Implement Dependency Verification Policies
   Organizations should mandate that developers verify all dependencies—AI-suggested or otherwise—against trusted registries before installation. Tools like Socket or Dependabot can scan for known vulnerabilities and flag suspicious packages. Establishing a “known good” list of approved dependencies can further reduce risk.
2. Enhance Developer Training
   Developers must be educated about the risks of AI-hallucinated dependencies. Regular training sessions should emphasize the importance of manually checking package names and sources, even when using trusted AI tools. As Hackaday’s Tyler August notes, “an AI cannot take responsibility”—the onus remains on the developer to validate imports.
3. Leverage Automated Guardrails
   Deploy automated tools to monitor and block the installation of unverified packages. Dependency scanners, policy-as-code gates, and continuous monitoring can catch hallucinated dependencies before they enter production environments. Some experts suggest that LLM vendors could integrate registry lookups to prevent the generation of non-existent package names, though this is not yet widely implemented.
4. Strengthen Third-Party Risk Management
   CPG companies must extend their security policies to third-party vendors, ensuring that their development practices align with enterprise standards. This includes auditing vendor codebases for slopsquatting vulnerabilities and requiring regular security assessments.
5. Prepare for Incident Response
   Develop a robust incident response plan tailored to supply chain attacks. This should include playbooks for identifying compromised dependencies, isolating affected systems, and communicating with stakeholders. Given the potential impact on consumer trust, CPG companies should also prepare for public relations challenges in the event of a breach.

The Road Ahead: Balancing Innovation and Security

Slopsquatting underscores a broader lesson for the CPG industry and beyond: automation, while a powerful driver of innovation, also amplifies the attack surface. Generative AI is not going away—its productivity gains are too significant to ignore. However, as adoption grows, so does the responsibility to secure its outputs. For CXOs, this means investing in both technology and talent to stay ahead of emerging threats. For security experts, it demands a shift toward proactive, AI-aware defense strategies that can keep pace with the evolving threat landscape.

In the context of the CPG industry’s current challenges, slopsquatting is a stark reminder of the interconnectedness of operational and cybersecurity risks. As tariffs strain supply chains and consumer spending, a cybersecurity breach could tip the scales from manageable disruption to full-scale crisis. By taking decisive action now—through policy, technology, and education—CPG leaders can protect their organizations from this emerging threat and build a more resilient future in an increasingly complex digital world.