In terms of pure productivity
Posted: Thu Feb 06, 2025 4:40 am
Towards Flexible Learning in an AI World
08.12.2023
Developer training is becoming increasingly tailored to individual preferences. InformationWeek interviews Peter Danieux, CEO of Secure Code Warrior, about how the field will evolve in the coming year and what role artificial intelligence will play in its evolution.
There has been a lot of enthusiasm lately about using AI for code development. AI can, after all, relieve development teams of the burden of repetitive and tedious tasks. It can suggest code, analyze and review products, and help optimize research initiatives.
, AI cuts the time it takes to create and document code by nearly half, according to McKinsey. According to GitHub, more than 9 in 10 U.S. developers use AI-powered coding tools, citing benefits such as increased efficiency and freeing up more time to focus on more valuable and creative tasks rather than repetitive ones.
But over-reliance on unsupervised coding—or croatia mobile database AI to do all the work—leads to poor-quality code that’s vulnerable to cyberattacks. Beyond code-level vulnerabilities making their way into production, threat actors are taking advantage of AI tools in a variety of ways, from creating malware to engaging in social engineering attacks to exploiting generative AI’s tendency to “hallucinate” incorrect answers.
The latest trick, called “hallucination squatting,” was discovered when a security researcher asked ChatGPT to recommend libraries to perform a certain task, and the bot confidently provided answers. However, none of the libraries it named actually existed. It became clear that an attacker could use their names, create malware disguised as a fake library, and carry out a successful attack.
This is just one example of the attack vectors that are made possible by the abuse of AI. Combined with the fact that AI, unlike humans, is not aware of contextual security when creating code, developers should be able to hone their secure coding skills and increase their security awareness. After all, they are the first line of defense in protecting organizations from introducing code-level security flaws and misconfigurations, especially as AI coding tools become more common.
08.12.2023
Developer training is becoming increasingly tailored to individual preferences. InformationWeek interviews Peter Danieux, CEO of Secure Code Warrior, about how the field will evolve in the coming year and what role artificial intelligence will play in its evolution.
There has been a lot of enthusiasm lately about using AI for code development. AI can, after all, relieve development teams of the burden of repetitive and tedious tasks. It can suggest code, analyze and review products, and help optimize research initiatives.
, AI cuts the time it takes to create and document code by nearly half, according to McKinsey. According to GitHub, more than 9 in 10 U.S. developers use AI-powered coding tools, citing benefits such as increased efficiency and freeing up more time to focus on more valuable and creative tasks rather than repetitive ones.
But over-reliance on unsupervised coding—or croatia mobile database AI to do all the work—leads to poor-quality code that’s vulnerable to cyberattacks. Beyond code-level vulnerabilities making their way into production, threat actors are taking advantage of AI tools in a variety of ways, from creating malware to engaging in social engineering attacks to exploiting generative AI’s tendency to “hallucinate” incorrect answers.
The latest trick, called “hallucination squatting,” was discovered when a security researcher asked ChatGPT to recommend libraries to perform a certain task, and the bot confidently provided answers. However, none of the libraries it named actually existed. It became clear that an attacker could use their names, create malware disguised as a fake library, and carry out a successful attack.
This is just one example of the attack vectors that are made possible by the abuse of AI. Combined with the fact that AI, unlike humans, is not aware of contextual security when creating code, developers should be able to hone their secure coding skills and increase their security awareness. After all, they are the first line of defense in protecting organizations from introducing code-level security flaws and misconfigurations, especially as AI coding tools become more common.