Enterprises face more cybersecurity threats than ever before. Verizon’s 2022 Data Breach Investigations Report noted that ransomware attacks increase by 13 percent annually, a rise greater than the previous 5 years combined. Enterprises have leveraged several cybersecurity solutions to create a web of continuous monitoring.
However, attacks continue to slip through the cracks. The reality is that attack surface management is challenging, and many enterprises fail to account for the basics. Here are the 5 most common security threats companies must ensure their attack surface management tools are mitigating.
Despite numerous security training programs and awareness drills, phishing continues to occupy the top spot in the list of the most common attack vectors. One reason is the rising sophistication among phishers. In the past, security admins had to worry about a malware link or Trojan in emails.
These days, phishers have moved on to leveraging concepts like multifactor authentication (MFA) fatigue when targeting employees. For instance, a phisher might unleash a barrage of authentication requests on an unsuspecting employee and message them for authentication credentials to stop the barrage.
The employee willingly hands over credentials since they believe these are being shared with IT security. This scenario played out in the recent Uber data breach, where the attackers announced the hack in an internal Slack channel using stolen credentials.
Security drills must focus on training users to respond to suspicious requests through simulated drills and attacks. Mere awareness doesn’t cut it anymore.
5G Configuration Errors
Enterprises are rapidly upgrading their infrastructure to 5G. The promise of increased bandwidth and support for rich media is a major attraction. However, 5G is still nascent and has several vulnerabilities. More importantly, the switch from legacy networks to 5G is fraught with security risks.
Configuration errors are one of the most common security shortfalls within 5G migration projects. Most enterprises use numerous apps, all of which present unique configuration challenges. The average enterprise’s IT infrastructure is a maze of API calls and microservices. Dissecting each entity’s configuration needs is a considerable task.
The right approach to adopt is to audit each service and app a company uses and migrate them to 5G piecemeal. While urgency and competitive efficiency are critical, enterprises must not pursue these goals at security’s expense.
Secrets management tool usage has increased over the past few years, and with good reason. DevOps pipelines dominate enterprise development schedules. This method focuses on tool usage and automation to quickly release code. However, DevOps does not account for security.
Most enterprise security postures are stuck in legacy waterfall models, with security checking in at pre-planned points. This method serves no one since code changes too fast for security to keep pace. The result is untested code making it into production.
Making matters worse, code often consists of hard-coded credentials that services need to generate output. For instance, developers might hard-code cloud container access credentials to speed processing times. With such practices, one shouldn’t be surprised at the rise in cyberattacks.
Automating credential management helps enterprises install an agile security posture that keeps pace with their DevOps programs. In addition, these tools also eliminate the possibility of cloud infrastructure suffering from a hack since the code will stop referencing authentication credentials.
Companies are generating more data than ever, and IoT devices lie at the heart of this rise. Enterprises leverage IoT data for everything from customer behavior to manufacturing efficiency. These data typically pose storage challenges since they can be either structured or unstructured.
These datasets must also be shared between disparate systems to increase efficiency and drive insights. Transporting data from one system to another is challenging, and this is where malicious actors enter to disrupt networks.
Companies must monitor their IoT framework, both hardware and software. IoT hardware is vulnerable to physical attacks and malfunctions. Most cybersecurity frameworks consider the impact on software and neglect hardware compromise. Enterprises must ensure they avoid this mistake.
AI is increasingly weaponized, and most attack methods use some form of AI. Continuous security monitoring will ensure an enterprise’s systems keep pace with AI evolution. However, a more insidious form of AI cyberattack is deepfake content.
AI these days is smart enough to gather publically available data, process it, and generate the person’s likeness while attributing words they never uttered. Deepfake videos are a serious enough threat to have caught the Pentagon’s eyes. It’s safe to say, enterprises must be concerned as well.
For instance, an attacker might use a deepfake of a company’s senior executive on a call and demand credentials or use these methods to extract sensitive information from colleagues. An attack surface tool must account for the rise of deepfake usage and constantly monitor network activity to ensure nothing abnormal is taking place.
Many Attack Vectors, Many Solutions
While the cybercrime picture might look bleak, companies can leverage several solutions to overcome these challenges. Ensuring the protection of the attack surfaces mentioned in this article goes a long way toward minimizing most security threats.