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Raw AI Threats Observations
Date: 2025-04-23
Research Context
This document represents the raw output of the observe primitive applied to collect intelligence on emerging cybersecurity threats related to AI systems. No filtering or analysis has been applied at this stage.
Logic Primitive: observe | Task ID: observe_001
Objective
Collect raw intelligence and signals about emerging cybersecurity threats related to AI systems without filtering or analysis.
Collection Parameters
- • Context ID: ai_cyber_report_2025
- • Observation Period: [Current - 6 months]
- • Logic Primitive: observe
- • Process Combination: Initial Curiosity (Observe)
Raw Observations
- • AI-driven cyber attacks can exploit vulnerabilities and masquerade as trusted system attributes.
- • Generative AI enhances defense mechanisms but also provides new tools for threat actors.
- • Adversarial machine learning threats involve manipulating the behavior of AI systems.
- • Prompt injection is a significant exploited LLM attack vector, allowing attackers to override model behavior, leak data, or execute malicious instructions.
- • AI-powered deception and fraud are emerging threats.
- • Weaponized AI is being used for automated attack technique code generation.
- • Midnight Blizzard is identified as a threat actor using compromised Microsoft 365 tenants for social engineering attacks.
- • Emerging threats and vulnerabilities for 2025 include zero-day exploits and 5G network vulnerabilities.
- • AI is transforming threat intelligence, increasing the sophistication and frequency of cyber threats.
- • Emerging attack vectors include advanced phishing, ransomware, AI-powered threats, IoT vulnerabilities, and cloud security risks.
- • The intersection of AI and cybersecurity presents both defenses and dangers, with potential unforeseen implications of AI-generated cyber attacks.
- • The question of whether GenAI threats are truly novel or iterations of existing challenges is being explored.
- • AI-powered cyberattacks leverage AI/ML to automate, accelerate, or enhance attack phases.
- • Leaders anticipate an increasingly complex threat landscape in 2025.
Observation Sources
- • tandfonline.com - 2022.2037254
- • perception-point.io - Generative AI in Cybersecurity
- • researchgate.net - The Emerging Threat of AI-driven Cyber Attacks
- • csoonline.com - Emerging Cyber Threats in 2023
- • geeksforgeeks.org - Emerging Attack Vectors in Cyber Security
- • darkreading.com - Emerging Threats Vulnerabilities Prepare 2025
- • gapii.xyz - How AI is Transforming Threat Intelligence
- • nist.gov - Types of Cyberattacks Manipulate Behavior of AI Systems
- • sciencedirect.com - S2214212620308620
- • researchgate.net - Comprehensive Analysis of New Attack Vectors
- • neuraltrust.ai - AI Security Risks 2025
- • deepmind.google - Evaluating Potential Cybersecurity Threats of Advanced AI
- • right-hand.ai - Impact of AI on Cyber Threat
- • microsoft.com - Cyber Signals Issue 9: AI-powered Deception
- • picussecurity.com - Top Threat Actors, Malware Vulnerabilities and Exploits
- • sciencedirect.com - S0167404824003821
- • arcticwolf.com - Top Five Cyberattack Vectors
- • eviden.com - AI Cybersecurity Threats and Defense
- • balbix.com - Attack Vectors and Breach Methods
- • arxiv.org - 2408.12806
- • knostic.ai - AI Attacks: Novel Risks or Simply Iterations of Existing Challenges
- • crowdstrike.com - AI-powered Cyberattacks
- • weforum.org - Biggest Cybersecurity Threats 2025
- • hiof.brage.unit.no - Misra The Emerging Threat 2022
Potential SCM Triggers
[This section will note any anomalies or patterns that might warrant Strategic Curiosity Mode investigation]
Next Actions
- Forward to
distinguish_critical_events
task - Tag observations for cross-referencing
- Update observation matrix