The recent hijacking of the Axios package highlights the escalating threat of supply chain attacks in software development. An attacker compromised a maintainer's account, added a malicious dependency called plain-crypto-js, and published an update. This dependency executed a remote access trojan on any machine that ran npm install, then deleted itself, making it nearly undetectable. With Axios being downloaded over 100 million times a week, the potential for widespread impact was significant. Traditional security measures, which focus on known vulnerabilities, failed to catch this threat since the backdoor didn’t have a CVE. Two key developments have worsened the situation. First, AI-driven coding tools have accelerated development, allowing for rapid dependency management with little human oversight. Second, attackers are now capable of exploiting this speed, targeting entire ecosystems rather than just individual packages. An example is the TeamPCP campaign that exploited a vulnerability in the Trivy scanner. It stole an access token, inserted malicious code across nearly all version tags, and propagated a worm that spread through 66 npm packages within days. This shift from surgical and targeted attacks to automated, ecosystem-wide exploits presents a new danger. AI tools are not only enhancing developer productivity but also increasing supply chain vulnerabilities. A study revealed that AI agents are 50% more likely to select known-vulnerable dependency versions compared to humans. Furthermore, they often generate fake package names, a tactic known as "slopsquatting," where attackers create malicious packages based on these hallucinated names. Autonomous coding agents are now capable of installing dependencies and executing builds without human intervention, compressing security review windows to nearly zero. Socket, a company focused on supply chain security, detected the malicious Axios dependency just six minutes after publication, a stark contrast to the industry average of 267 days for detecting such breaches. Socket's approach analyzes the behavior of code rather than relying on a vulnerability database, which allowed it to identify the threat before the compromised version of Axios was even released. This highlights the urgent need for more effective security measures in software development to keep pace with evolving threats.