A Resource For Thinking About The Various Attack Surfaces Related To Ai

A Resource For Thinking About The Various Attack Surfaces Related To AI

A Resource For Thinking About The Various Attack Surfaces Related To AI The purpose of the this resource is to give the general public, and offensive security practitioners specifically, a way to think about the various attack surfaces within an ai system. The agentic threats navigator is a guide that outlines key attack surfaces in agentic ai systems, including reasoning, memory, tools, identity, human oversight, and multi agent interactions. it provides threats and examples to help security teams understand and assess risks in agentic ai systems.

AI System Security: Understanding Expanded Attack Surfaces

AI System Security: Understanding Expanded Attack Surfaces Agentic ai promises autonomous threat detection and process automation at machine speed — but introduces new security risks, unseen attack surfaces, and governance challenges that cisos must address. From prompt injection to model inversion, attackers are already targeting ai systems to exfiltrate data, manipulate outcomes, or bypass controls. ai has become a new attack surface and must be secured as such, with the same urgency applied to your cloud, network, or endpoints. Stride is a threat modeling framework that supports a proactive approach to improving security by identifying, understanding, and addressing threats before systems are implemented. stride stands for spoofing, tampering, repudiation, information disclosure, denial of service, and elevation of privilege. Download our whitepaper to learn more about expanded attack surfaces and protecting your organisation from digital threats in the age of ai.

AI-generated Attack Vectors Cybersecurity Should Watch For

AI-generated Attack Vectors Cybersecurity Should Watch For Stride is a threat modeling framework that supports a proactive approach to improving security by identifying, understanding, and addressing threats before systems are implemented. stride stands for spoofing, tampering, repudiation, information disclosure, denial of service, and elevation of privilege. Download our whitepaper to learn more about expanded attack surfaces and protecting your organisation from digital threats in the age of ai. As of may 2023, the release of advanced artificial intelligence (ai) models like gpt 4 and chatgpt, combined with integration technologies such as langchain, has ushered in a new era of ai technology rapid evolution and its integration into various aspects of society. In 2024, 87% of global organizations faced an ai powered cyberattack, a number that is only expected to increase. this is also reflected in our open source intelligence research, where we are regularly coming across instances of ai powered cyberattacks. In 2025, researchers proposed the first end to end threat taxonomy for llm agent ecosystems, with four primary domains: 1. input manipulation. 2. model compromise. 3. system & privacy attacks. 4. protocol exploits. a real ai attack surface review must track data flow and privilege boundaries across six layers: 1. data inputs. Embedded into information systems, artificial intelligence (ai) faces security threats that exploit ai specific vulnerabilities. this paper provides an accessible overview of adversarial attacks unique to predictive and generative ai systems.

Attack Surface Of AI. | Download Scientific Diagram

Attack Surface Of AI. | Download Scientific Diagram As of may 2023, the release of advanced artificial intelligence (ai) models like gpt 4 and chatgpt, combined with integration technologies such as langchain, has ushered in a new era of ai technology rapid evolution and its integration into various aspects of society. In 2024, 87% of global organizations faced an ai powered cyberattack, a number that is only expected to increase. this is also reflected in our open source intelligence research, where we are regularly coming across instances of ai powered cyberattacks. In 2025, researchers proposed the first end to end threat taxonomy for llm agent ecosystems, with four primary domains: 1. input manipulation. 2. model compromise. 3. system & privacy attacks. 4. protocol exploits. a real ai attack surface review must track data flow and privilege boundaries across six layers: 1. data inputs. Embedded into information systems, artificial intelligence (ai) faces security threats that exploit ai specific vulnerabilities. this paper provides an accessible overview of adversarial attacks unique to predictive and generative ai systems.

Artificial Intelligence: The new attack surface