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594 risk entries extracted from 74 frameworks, coded by domain, subdomain, causal entity, intent and timing. Filter, then export the current selection with its licence and citation attached.

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594 entries · page 5 of 12

  1. 61.02.49 · Risk Sub-Category

    Sources of systemic risks from general-purpose AI

    Widespread use of persuasion tools

    "Widespread use of AI-powered persuasion tools could lead to systemic harm"

    From A Taxonomy of Systemic Risks from General-Purpose AI (Uuk2025)

  2. 62.31.03#1 · Risk Sub-Category

    Impacts of AI (Societal Impacts)

    Automatically generating disinformation at scale

    "Disinformation (in various modalities: text, audio, images, video, etc.) can be generated with minimal human oversight and effort. Disinformation tools are relatively cheap and their technology is widely available. Such deployments can be particularly widespread in sensitive political contexts."

    From Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems (Gipiškis2024)

  3. 62.31.05 · Risk Sub-Category

    Impacts of AI (Societal Impacts)

    Generative AI use in political influence campaigns

    "GPAI tools can be used in automation and scaling of influence campaigns [178]. Public opinion may be manipulated by targeted misleading or manipulative information. This can lead to rising political polarization and diminishing trust in public institutions."

    From Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems (Gipiškis2024)

  4. 62.31.10 · Risk Sub-Category

    Impacts of AI (Societal Impacts)

    Misuse for surveillance and population control

    "AI tools can be misused by human or institutional actors for monitoring, control- ling, or suppressing individuals [178]. Massive data collection and automated analysis are often conducted, and AI tools can further exacerbate such practices."

    From Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems (Gipiškis2024)

  5. 62.31.12 · Risk Sub-Category

    Impacts of AI (Societal Impacts)

    Diminishing societal trust due to disinformation or manipulation

    "The use of GPAIs may contribute to the proliferation of either deliberate dis- information or unintended misinformation can severely erode trust in public figures and democratic institutions. This diminishing trust can extend to other forms of media, making the public less informed."

    From Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems (Gipiškis2024)

  6. 62.31.13 · Risk Sub-Category

    Impacts of AI (Societal Impacts)

    Personalized disinformation

    "Automatic generation of disinformation can be personalized to target specific groups or individuals. Such attacks can be more effective in achieving their goals, and their costs can be significantly reduced when using GPAIs."

    From Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems (Gipiškis2024)

  7. "Create synthetic online personas or accounts"

    From Generative AI Misuse: A Taxonomy of Tactics and Insights from Real-World Data (Marchal2024)

  8. "Fabricate or falsely represent evidence, incl. reports, IDs, documents"

    From Generative AI Misuse: A Taxonomy of Tactics and Insights from Real-World Data (Marchal2024)

  9. 65.14.06 · Risk Sub-Category

    Output risks (misuse)

    Spreading disinformation

    "Generative AI models might be used to intentionally create misleading or false information to deceive or influence a targeted audience."

    From AI Risk Atlas (IBM2025)

  10. 66.02.02 · Risk Sub-Category

    Political and Economic

    Institutional trust loss

    "Erosion of trust in public institutions and weakened checks and balances due to mis/disinformation, influence operations, or real or perceived misuse of generative AI"

    From A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents (Li2025)

  11. 66.07.04 · Risk Sub-Category

    Psychological

    Coercion / manipulation

    "Use of a technology system to covertly alter user beliefs and behaviour using nudging, dark patterns and/or other opaque techniques"

    From A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents (Li2025)

  12. 67.03.03 · Risk Sub-Category

    Misuse risks

    Disinformation and Influence Operations

    "In addition to unintentional degradation of the information environment (discussed in the section on Societal Harms above), frontier AI can be misused to deliberately spread false information to create disruption, persuade people on political issues, or cause other forms of harm or damage."

    From Capabilities and Risks from Frontier AI (DSIT2023)

  13. 72.01.04 · Risk Sub-Category

    Misuse Risks

    Large-Scale Persuasion and Harmful Manipulation Risks

    "AI systems can be gravely misused to distort public perception and compromise social stability through the generation of synthetic content (e.g., deepfakes, sophisticated fake news) and the strategic manipulation of digital platforms with large user bases to disseminate or precisely target misleading information or ideologies."

    From Frontier AI Risk Management Framework (v1.0) (Tse2025)

  14. 73.03.03 · Risk Sub-Category

    Dual-Use Capabilities Enable Malicious Use and Misuse of LLMs

    Surveillance and Censorship

    "Content moderation has emerged as one of the key use-cases of LLMs (Weng et al., 2023), indicating the potential of LLMs for surveillance and censorship as well (Edwards, 2023). Surveillance and censorship are one of the primary tools employed by governments with dictatorial tendencies to suppress opposing political and social voices. These censorship measures, however, are often quite crude and can be escaped with little ingenuity...However, LLMs could enable significantly more sophisticated surveillance and censorship operations at scale (Feldstein, 2019). Multimodal-LLMs or LLMs combined w

    From Foundational Challenges in Assuring Alignment and Safety of Large Language Models (Anwar2024)

  15. One or more criminal entities could create AI to intentionally inflict harms, such as for terrorism or combating law enforcement.

    From TASRA: a Taxonomy and Analysis of Societal-Scale Risks from AI (Critch2023)

  16. AI deployed by states in war, civil war, or law enforcement can easily yield societal-scale harm

    From TASRA: a Taxonomy and Analysis of Societal-Scale Risks from AI (Critch2023)

  17. 02.03.03 · Risk Sub-Category

    Unhelpful Uses

    Cyber Attacks

    "Hackers can obtain malicious code in a low-cost and efficient manner to automate cyber attacks with powerful LLM systems."

    From Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  18. 05.10.00 · Risk Category

    Cybercrime

    Closely related to discussions surrounding security and harmful content, the field of cybersecurity investigates how generative AI is misused for fraudulent online activities. A particular focus lies on social engineering attacks, for instance by utilizing generative AI to impersonate humans, creating fake identities, cloning voices, or crafting phishing messages. Another prevalent concern is the use of LLMs for generating malicious code or hacking.

    From Mapping the Ethics of Generative AI: A Comprehensive Scoping Review (Hagendorff2024)

  19. 09.05.03 · Risk Sub-Category

    Unauthorized manipulation of AI

    Unauthorized manipulation of AI

    "AI machines could be hacked and misused, e.g. manipulating an airport luggage screening system to smuggle weapons"

    From Managing the ethical and risk implications of rapid advances in artificial intelligence: A literature review (Meek2016)

  20. 12.01.00 · Risk Category

    Abuse & Misuse

    "The potential for AI systems to be used maliciously or irresponsibly, including for creating deepfakes, automated cyber attacks, or invasive surveillance systems. Specifically denotes intentional use of AI for harm."

    From AI Risk Profiles: A Standards Proposal for Pre-Deployment AI Risk Disclosures (Sherman2023)

  21. 16.04.02 · Risk Sub-Category

    Risk area 4: Malicious Uses

    Assisting code generation for cyber security threats

    Anticipated risk: "Creators of the assistive coding tool Co-Pilot based on GPT-3 suggest that such tools may lower the cost of developing polymorphic malware which is able to change its features in order to evade detection [37]."

    From Taxonomy of Risks posed by Language Models (Weidinger2022)

  22. 17.04.03 · Risk Sub-Category

    Malicious Uses

    Assisting code generation for cyber attacks, weapons, or malicious use

  23. 18.04.04 · Risk Sub-Category

    Malicious Use

    Security threats

    "Facilitating the conduct of cyber attacks, weapon development, and security breaches"

    From Sociotechnical Safety Evaluation of Generative AI Systems (Weidinger2023)

  24. 19.02.04 · Risk Sub-Category

    Informational and Communicational AI Risks

    Endangerment of data protection through AI cyberattacks

  25. 19.04.03 · Risk Sub-Category

    Social AI Risks

    Hazardous misuse of AI systems bears danger to the society in public spaces (e.g., hacker attacks on autonomous weapons)

  26. 22.01.02 · Risk Sub-Category

    Malicious Use (Intentional)

    Unleashing AI Agents

    "people could build AIs that pursue dangerous goals’"

    From An Overview of Catastrophic AI Risks (Hendrycks2023)

  27. 24.03.01 · Risk Sub-Category

    Malicious Uses

    Offensive Cyber Operations (General)

    "Offensive cyber operations are malicious attacks on computer systems and networks aimed at gaining unauthorized access to, manipulating, denying, disrupting, degrading, or destroying the target system. These attacks can target the system’s network, hardware, or software. Advanced AI assistants can be a double-edged sword in cybersecurity, benefiting both the defenders and the attackers. They can be used by cyber defenders to protect systems from malicious intruders by leveraging information trained on massive amounts of cyber-threat intelligence data, including vulnerabilities, attack pattern

    From The Ethics of Advanced AI Assistants (Gabriel2024)

  28. 24.03.03 · Risk Sub-Category

    Malicious Uses

    AI-Assisted Software Vulnerability Discovery

    "A common element in offensive cyber operations involves the identification and exploitation of system vulnerabilities to gain unauthorized access or control. Until recently, these activities required specialist programming knowledge. In the case of ‘zero-day’ vulnerabilities (flaws or weaknesses in software or an operating system that the creator or vendor is not aware of), considerable resources and technical creativity are typically required to manually discover such vulnerabilities, so their use is limited to well-resourced nation states or technically sophisticated advanced persistent thr

    From The Ethics of Advanced AI Assistants (Gabriel2024)

  29. 24.03.04 · Risk Sub-Category

    Malicious Uses

    Malicious Code Generation

    "Malicious code is a term for code—whether it be part of a script or embedded in a software system—designed to cause damage, security breaches, or other threats to application security. Advanced AI assistants with the ability to produce source code can potentially lower the barrier to entry for threat actors with limited programming abilities or technical skills to produce malicious code. Recently, a series of proof-of-concept attacks have shown how a benign-seeming executable file can be crafted such that, at every runtime, it makes application programming interface (API) calls to an AI assis

    From The Ethics of Advanced AI Assistants (Gabriel2024)

  30. 30.04.02 · Risk Sub-Category

    Resistance to Misuse

    Cyberattack

    ability of LLMs to write reasonably good-quality code with extremely low cost and incredible speed, such great assistance can equally facilitate malicious attacks. In particular, malicious hackers can leverage LLMs to assist with performing cyberattacks leveraged by the low cost of LLMs and help with automating the attacks.

    From Trustworthy LLMs: A Survey and Guideline for Evaluating Large Language Models’ Alignment (Liu2024)

  31. 31.01.04 · Risk Sub-Category

    Information Manipulation

    Security

    "Though chatbots cannot (yet) develop their own novel malware from scratch, hackers could soon potentially use the coding abilities of large language models like ChatGPT to create malware that can then be minutely adjusted for maximum reach and effect, essentially allowing more novice hackers to become a serious security risk"

    From Generating Harms - Generative AI's impact and paths forwards (EPIC2023)

  32. 35.01.00 · Risk Category

    Weaponization

    weaponizing AI may be an onramp to more dangerous outcomes. In recent years, deep RL algorithms can outperform humans at aerial combat [18], AlphaFold has discovered new chemical weapons [66], researchers have been developing AI systems for automated cyberattacks [11, 14], military leaders have discussed having AI systems have decisive control over nuclear silos

    From X-Risk Analysis for AI Research (Hendrycks2022)

  33. 41.05.00 · Risk Category

    Security & Defense

    "AI could enable more serious incidents to occur by lowering the cost of devising cyber-attacks and enabling more targeted incidents. The same programming error or hacker attack could be replicated on numerous machines. Or one machine could repeat the same erroneous activity several times, leading to an unforeseen accumulation of losses."

    From The Rise of Artificial Intelligence - Future Outlooks and Emerging Risks (Allianz2018)

  34. 41.05.01 · Risk Sub-Category

    Security & Defense

    Catastrophic risk due to autonomous weapons programmed with dangerous targets

    "AI could enable autonomous vehicles, such as drones, to be utilized as weapons. Such threats are often underestimated."

    From The Rise of Artificial Intelligence - Future Outlooks and Emerging Risks (Allianz2018)

  35. 42.12.00 · Risk Category

    Security

    "Implications of the weaponization of AI for defence (the embeddedness of AI-based capabilities across the land, air, naval and space domains may affect combined arms operations)."

    From An Exploratory Diagnosis of Artificial Intelligence Risks for a Responsible Governance (Teixeira2022)

  36. 43.02.06 · Risk Sub-Category

    Extreme Risks

    Dual-Use Science

    "LLM has science capabilities that can be used to cause harm (e.g., providing step-by-step instructions for conducting malicious experiments)"

    From Cataloguing LLM Evaluations (InfoComm2023)

  37. 45.02.04 · Risk Sub-Category

    Safety risks in AI Applications

    Cyberspace risks (Risks of abuse for cyberattacks)

    "AI can be used in launching automatic cyberattacks or increasing attack efficiency, including exploring and making use of vulnerabilities, cracking passwords, generating malicious codes, sending phishing emails, network scanning, and social engineering attacks. All these lower the threshold for cyberattacks and increase the difficulty of security protection."

    From AI Safety Governance Framework (TC2602024)

  38. 45.02.08 · Risk Sub-Category

    Safety risks in AI Applications

    Real-world risks (Risks of misuse of dual-use items and technologies)

    "Due to improper use or abuse, AI can pose serious risks to national security, economic security, and public health security, such as greatly reducing the capability requirements for non-experts to design, synthesize, acquire, and use nuclear, biological, and chemical weapons and missiles; and designing cyber weapons that launch network attacks on a wide range of potential targets through methods like automatic vulnerability discovery and exploitation."

    From AI Safety Governance Framework (TC2602024)

  39. 47.02.02 · Risk Sub-Category

    Ethical and social risks

    Malicious use and abuse (cyberattacks)

    "Generative AI can help amplify the frequency and destructiveness of cyberattacks.311 It has the capacity “to increase the accessibility, success rate, scale, speed, stealth, and potency of cyberattacks. It enables the identification of critical vulnerabilities within targeted systems, facilitates the increase of the scale of cyberattacks, and accelerates the process by discovering innovative methods of system infiltration. Cyberattacks can inflict significant damage and may impact critical infrastructure, including electrical grids, financial systems, and weapons management systems."

    From Regulating under Uncertainty: Governance Options for Generative AI (G'sell2024)

  40. 47.02.03 · Risk Sub-Category

    Ethical and social risks

    Malicious use and abuse (biosecurity threats)

    "Many fear that generative AI could make the creation of biological weapons easier by providing access to critical knowledge and automated assistance to a wider range of actors to engage in malicious activities."

    From Regulating under Uncertainty: Governance Options for Generative AI (G'sell2024)

  41. 47.02.06 · Risk Sub-Category

    Ethical and social risks

    Malicious use and abuse (military applications)

    "The advancement of AI for military purposes is rapidly ushering in a new phase of growth in military technology. Lethal Autonomous Weapons Systems (LAWS) possess the capability to detect, engage, and eliminate human targets independently, without human input.341 In 2020, a sophisticated AI agent surpassed experienced F-16 pilots in multiple simulated aerial combat scenarios, notably achieving a 5-0 victory against a human pilot through “aggressive and precise maneuvers” that the human could not surpass.342 Additionally, fully autonomous drones are already operational."

    From Regulating under Uncertainty: Governance Options for Generative AI (G'sell2024)

  42. "Lowered barriers for offensive cyber capabilities, including via automated discovery and exploitation of vulnerabilities to ease hacking, malware, phishing, offensive cyber operations, or other cyberattacks; increased attack surface for targeted cyberattacks, which may compromise a system’s availability or the confidentiality or integrity of training data, code, or model weights."

    From Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile (NIST2024)

  43. 49.01.02#2 · Risk Sub-Category

    Malicious Use Risks

    Cyber offence

    "General- purpose AI systems could uplift the cyber expertise of individuals, making it easier for malicious users to conduct effective cyber- attacks, as well as providing a tool that can be used in cyber defence. General- purpose AI systems can be used to automate and scale some types of cyber operations, such as social engineering attacks."

    From International Scientific Report on the Safety of Advanced AI (Bengio2024)

  44. 49.01.03 · Risk Sub-Category

    Malicious Use Risks

    Dual use science risks

    "General- purpose AI systems could accelerate advances in a range of scientific endeavours, from training new scientists to enabling faster research workflows. While these capabilities could have numerous beneficial applications, some experts have expressed concern that they could be used for malicious purposes, especially if further capabilities are developed soon before appropriate countermeasures are put in place. There are two avenues by which general- purpose AI systems could, speculatively, facilitate malicious use in the life sciences: firstly by providing increased access to informatio

    From International Scientific Report on the Safety of Advanced AI (Bengio2024)

  45. 50.02.05 · Risk Sub-Category

    Content Safety Risks

    Violence and extremism (Weapon Usage and Development)

  46. 50.02.06 · Risk Sub-Category

    Content Safety Risks

    Violence and extremism (Military and Warfare)

  47. 52.02.02 · Risk Sub-Category

    Misuse Risks

    Biosecurity Threats

    "The potential misuse of general purpose AI models also extends to biosecurity threats. Biological weapons are generally understood as biological toxins or infectious agents such as viruses that are intentionally released to cause disease and death.157 General purpose AI models could facilitate the production of biological weapons, by reducing barriers through access to critical knowledge or increasingly automated assistance and thus enable more malicious actors."

    From Governing General Purpose AI: A Comprehensive Map of Unreliability, Misuse and Systemic Risks (Maham2023 )

  48. 53.02.02 · Risk Sub-Category

    Dangerous capabilities in AI systems

    Acquisition of a goal to harm society

    "cases of AI systems being given the outright goal of harming humanity (ChaosGPT);"

    From Advancing AI Governance: A Literature Review of Problems, Options, and Proposals (Maas2023)

  49. 55.02.01 · Risk Sub-Category

    Worsened conflict

    AI enables development of weapons of mass destruction

    "AI is already enabling the development of weapons which could cause mass destruction —including new weapons that themselves use AI capabilities, such as Lethal Autonomous Weapons [2],10 and the potential use of AI to speed up the development of other potentially dangerous technologies, such as engineered pathogens (as discussed in Section 2)."

    From A Survey of the Potential Long-term Impacts of AI: How AI Could Lead to Long-term Changes in Science, Cooperation, Power, Epistemics and Values (Clarke2023)

  50. 58.07.15 · Risk Sub-Category

    Societal and Cultural

    Violence/armed conflict

    "Violence/armed conflict - Use or misuse of a technology system to incite, facilitate or conduct cyberattacks, security breaches, lethal, biological and chemical weapons development, resulting in violence and armed conflict."

    From A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

Informational only, not legal advice. Verify every claim against the linked official sources and consult qualified counsel before acting.