AI-enabled attacks present unique risks primarily due to the speed and scale at which they occur, making standard countermeasures difficult to implement within typical timelines. These attacks are distinct because of the ease with which adversaries can deploy them and the dynamic, optimized nature of the artificial intelligence (AI) driving them. AI can enhance adversary capabilities across the cybersecurity landscape, including the discovery of vulnerabilities, the acceleration of attack paths, and the uplifting of previously unsophisticated bad actors.
Social Engineering and Personnel Targeting Attacks targeting personnel are a leading method for AI-enabled intrusions. AI capabilities introduce several unique threats in this domain:
- Hyper-realistic Content: Adversaries can use Generative AI (GenAI) to create hyper-realistic malicious websites and links for phishing campaigns.
- DeepFakes: AI-enabled spear-phishing can exploit users through realistic audio and video manipulation, known as DeepFakes.
- Personalization: Attackers can leverage AI to process personal data distributed online to build personalized profiles and trust-building narratives for intended targets with very little effort.
Malware and Evasion AI enables adversaries to obfuscate their intentions and bypass traditional defenses:
- Evasion of Detection: AI is used to generate new forms of malware designed to make current signature-based detections and anti-virus systems fail.
- Obfuscation Techniques: Examples include malware executed from computer memory rather than hardware and the use of seemingly benign file types to hide planted malware instructions.
Autonomous Operations AI agents introduce the risk of autonomous attack orchestration:
- Attack Phases: AI agents are increasingly capable of autonomously managing various phases of a cyber attack, including reconnaissance, attack surface mapping, vulnerability exploitation, credential harvesting, lateral movement, and data collection.
- Tool Usage: These agents can autonomously operate common cybersecurity utilities, such as password crackers, network scanners, binary analysis suites, and exploitation frameworks.
Operational and Strategic Risks The broader implications of AI-enabled attacks include:
- lowered Barrier to Entry: AI-enabled attacks lower the barrier of entry for gaining access to identities, credentials, services, and hardware.
- Supply Chain Vulnerability: Suppliers and third parties with access to internal data and systems may become specific targets of AI-enabled attacks.
- Resource Intensity: The scale and speed of these attacks may increase the resources required to properly detect if and when an attack has occurred.
