While AI or Artificial intelligence is a rapidly growing technology with its vast conveniences, it can also bring disaster in the form of AI-based phishing attacks. Therefore, robust AI-based anti-phishing solutions that can help predict the attacks can be the only way to secure your enterprise networks.
Artificial intelligence (AI) and machine learning (ML) is transforming the way we live and work, with a wide range of tools and applications now commonplace in our daily lives. However, as most are beginning to see, with the rise of AI comes new challenges, particularly in the realm of cybersecurity. Criminals can now leverage the power of AI to launch increasingly sophisticated and convincing phishing attacks with little effort and by volumes that were not previously achievable. Therefore, to prevent AI-based cyberattacks and malware that infect networks, using efficient and more clever AI-based anti-phishing solutions is vital. It means using AI to combat AI and acting before you get phished. This article touches into this grey area and offers solutions to protect your organization and preserve its critical data assets’ confidentiality, integrity, and availability.
Statistics: AI-Based Phishing
Today, a significant part of phishing attacks are AI-generated. One can get an idea of the phishing scenario by the following statistics:
- According to an APWG report, the Q1 of 2022 saw 1,025,968 phishing attacks.
- The 2022 SlashNext State of Phishing Report says that phishing attacks in 2022 increased by 61% over 2021.
- A Swiss Cyber Institute report says that 65% of malicious actors leverage spear phishing emails as the primary attack vector.
- Verizon reports say that 94% of malware is delivered through email.
Emerging Risks and Challenges Due to AI-Based Phishing
Ransomware comes in different types; however, the two most common categories are crypto-ransomware and locker ransomware.
AI has been proving itself to be a double-edged sword. On the one hand, it has simplified people’s lives significantly, while on the other hand, AI-Based phishing is changing the cyber world by introducing ways never seen before to infiltrate enterprise networks. Below are some emerging risks and challenges associated with AI-based phishing.
Increased Attack Surface
The attack surface is expanding. AI can exploit vulnerabilities like default OS settings, poorly maintained (unpatched) software, weak passwords, or exposed APIs, considerably increasing the cyberattack surface.
Speed and Scale of Attack
AI bots can enhance the scale of attack to hitherto unheard levels. For instance, AI can perform reconnaissance, such as analyzing millions of social media interactions to identify relevant high-profile targets.
The Inability of Older Anti-Phishing and Anti-malware Solutions to Adapt to New Threats
The existing cybersecurity software solutions can prove inadequate to upscale and adapt to advanced persistent threats, especially with AI-based cyberattacks.
Easy Malware Implants
AI can quickly analyze and predict user behavior, making it convenient for AI-based phishing attacks to implant malware into enterprise network systems.
Dangerous Things in Store
Deepfake scams (Deepfakes are fake videos created using software that can combine various images and create new videos by leveraging AI-ML-based face swapping. ) are nearly impossible to detect. The use of AI in cybercrime can lead to more undesirable outcomes.
Malicious actors can use AI to manipulate machine algorithms and trick cybersecurity systems into classifying malicious attacks as benign. If the dataset poisoning continues undetected for extended durations, it can lead to severe repercussions for the organization.
Activating AI-powered Malware
AI-based phishing allows threat actors to activate AI-powered malware that can analyze the enterprise network system’s defense mechanisms and mimic system communications to evade detection.
Steps Organizations Can Take to Prevent Malware from Getting into Enterprise Networks
How can organizations counter AI-based cyber threats? When enterprise networks encounter threats generated by capabilities beyond humans, AI is the only way to handle them. AI can help cybersecurity strategists hone threat intelligence, detect zero-day threats, eliminate false positives, and manage security alerts efficiently and effectively. Organizations can take the following steps and leverage AI to prevent malware from entering their enterprise networks.
Leveraging AI-Based Anti-Phishing Solutions
AI has been revolutionary in proving that fighting fire by fire is the best counterattack strategy. As phishing attacks have evolved much beyond emails and graduated to social media, leveraging AI-based anti-phishing solutions becomes crucial to prevent phishing attacks.
Organizations must use cutting-edge AI to detect a phishing attempt at the source and thwart it before the user becomes a victim. In addition, AI enables cybersecurity strategies to maintain a depository of known threats, allowing enterprise networks to improve anti-phishing protection technologies.
Effective Identity Automation:
Ascertaining user identity is critical because malicious actors use AI to impersonate other users and move laterally through the system network to infiltrate and compromise information assets. Therefore, it becomes crucial for enterprise networks to maintain an effective identity and access management (IAM) system that allows access to the right people to carry out their specific tasks whenever required.
Automated lifecycle management ensures removing the identities of employees who have left the organization from the database. Threat actors use AI to access networks. A single sign-on (SSO) process ensures users do not have multiple logins. IAM also secures access through various devices.
Taking Steps to Prevent Polymorphic Malware
Malicious actors have developed innovative techniques to launch their vicious attacks. For example, polymorphic malware cannot be detected using traditional signature-based methods. Instead, they use new decryption routines to mutate their appearance or signature files.
The only way to detect such malware is by using AI-based anti-malware solutions. An AI-based anti-phishing solution can detect phishing attempts and alert users before the malware strikes the network, enabling cybersecurity teams to initiate prompt corrective action and eliminate the threat before it accomplishes its task.
Early Prediction, Detection, and Mitigation Capabilities:
One of the significant advantages of using AI-based anti-malware solutions is that they can detect the threat early, enabling easy identification and prompt mitigation before it becomes a significant cyber incident.
AI allows for maintaining an elaborate database of identified threats. Consequently, it becomes convenient for organizations to predict cybersecurity threat trends and have proper corrective measures to mitigate new and advanced threats.
Real-Time Credential Phishing Prevention
AI-based cybersecurity solutions prove more versatile than conventional ones because cutting-edge computer vision analyzes webpages as they download. As a result, it helps identify phishing attacks in real time and stop them from compromising your information assets.
The solution detects credential phishing attacks and alerts users to discontinue the ongoing operation. Therefore, it prevents them from becoming victims and ensures no account takeover.
Choosing a Vendor or Solution Provider You Can Rely On
Your security posture depends on choosing the right AI-based solution that meets your organization’s cybersecurity requirements. The right anti-phishing tool can detect phishing and credential theft attacks in real-time and warn users to prevent them from becoming victims.
Choosing the right vendor entails taking proactive measures to stop threat actors in their tracks instead of reacting to cyberattacks after they take place. Another crucial point to note is the upscaling of the AI-based solution to counter advanced threats effectively.
Cyberattacks have evolved considerably, with malicious actors using innovative tactics, including AI, to target vulnerable enterprise networks globally. The use of AI has given attackers a new tool to craft more sophisticated and convincing phishing messages that are difficult to detect.
The ideal strategy to deal with such AI-based phishing attacks is to deploy AI-based cybersecurity solutions that can identify and block threats in real-time, enabling organizations to beat the malicious actors in their own game. By incorporating machine learning and other advanced techniques, these AI-powered anti-phishing solutions can rapidly analyze vast amounts of data to detect patterns and anomalies, allowing security teams to respond quickly and accurately to potential threats.
Examples of Ransomware-as-a-Service
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- (2022, October 4). Conti ransomware: The history behind one of the world’s most aggressive RaaS groups. (2022, October 4). Retrieved January 2, 2023, from Flashpoint website: https://flashpoint.io/blog/history-of-conti-ransomware/
- United States Department of State. (2021, November 4). DarkSide Ransomware as a Service (RaaS). (2021, November 4). Retrieved January 2, 2023, from United States Department of State website: https://www.state.gov/darkside-ransomware-as-a-service-raas/
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- Scroxton, A. (2022, February 9). Ransomware ever more sophisticated and impactful, warns NCSC. Retrieved January 2, 2023, from Computerweekly.com website: https://www.computerweekly.com/news/252513166/Ransomware-more-sophisticated-and-impactful-warns-NCSC
- Kost, E. (2022, September 9). What is ransomware as a service (RaaS)? The dangerous threat to world security. (n.d.). Retrieved January 2, 2023, from Upguard.com website: https://www.upguard.com/blog/what-is-ransomware-as-a-service
- X-Ops, S. (n.d.). Maturing criminal marketplaces present new challenges to defenders. Retrieved January 5, 2023, from Sophos.com website: https://assets.sophos.com/X24WTUEQ/at/b5n9ntjqmbkb8fg5rn25g4fc/sophos-2023-threat-report.pdf
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