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John Heasman, senior director of software security at DocuSign where the tool was trialed, lauded its effectiveness saying, “It’s rare that these solutions have such a low rate of false positives,” which traditionally pose a huge problem, taking so long to investigate that security experts risk missing the real bugs as they sort through false ones. The Microsoft Security Risk Detection tool, formerly Project Springfield, is an advanced, cloud-based fuzzing program that uses AI to root out risks before a program is generally available. In 2017 Microsoft announced the roll out of a new error and virus detection tool designed to meet the requirements of the current threat landscape. Using polymorphism and obfuscation, targeted attacks evading overloaded security teams and automation-to-scale, attackers are making it nigh on impossible for traditional solutions to keep pace.
With a 2017 Enterprise Risk Index report claiming that only 50% of file-based attacks were submitted to malware repositories, it is clear that the hackers have the upperhand. Despite the enormous commitment to preventing, detecting, and triaging faulty code, errors still account for 9 out of every 10 instances of cybercrime.
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It’s still common for developers to review each other’s code and run tests before launching new programs. It is estimated that 50–75% of development time is spent testing, with many errors detected due to firewalls, assertions, code reviews, IDE warnings, varying compilers for different OSes, working on different hardware, and so on. Traditional and legacy antivirus solutions simply cannot compete with advanced threats, such as the recent WannaCry ransomware virus. Security researchers regularly discover new malware as well as advanced malware variants, such as Mylobot. In an era where even the simplest of programming errors can throw open the doors to malicious intrusion, it is not surprising that many businesses are looking closely at the role artificial intelligence (AI) and machine learning (ML) could play in reinforcing cyber defenses. Program manager at US military Defence Advanced Research Projects Agency (DARPA), Sandeep Neema, says “What’s concerning and challenging is that the bugs in software are not decreasing,” which is why DARPA spends millions of dollars funding the development of Artificial Intelligence (AI) systems that can detect software flaws.
With billions of lines of code written every year it is currently impossible to ensure complete infallibility of code - while developers are, by nature a highly focused and meticulous bunch, to err is human and they are still just humans!
There is an ever-increasing onus on developers to ensure that they create robust programs that can withstand the advancing threat. Security vulnerabilities are growing in lockstep with accelerated software development and application complexity. While this synergy is driving innovation and advancement in almost every facet of our lives, it exposes us to new and challenging vulnerabilities that must be met by new and fulsome countermeasures. The Internet of Things is rapidly creating a global ecosystem of computer-human interdependence. Can AI detect bugs and errors, and prevent security breaches? Shields down