MIT AI Risk Repository · domain 4: Malicious actors

4.3 Fraud, scams, and targeted manipulation

Using AI systems to gain a personal advantage over others such as through cheating, fraud, scams, blackmail or targeted manipulation of beliefs or behavior. Examples include AI-facilitated plagiarism for research or education, impersonating a trusted or fake individual for illegitimate financial benefit, or creating humiliating or sexual imagery.

Risk entries
77
Frameworks citing it
12
Recorded incidents
412
Incidents since 2020
402
Causal entity (risk entries)
Causal entity (risk entries) 62 0 Human: 62 Human 62 Other: 10 Other 10 AI: 5 AI 5
Causal entity (risk entries)
LabelValue
Human62
Other10
AI5
Intent (risk entries)
Intent (risk entries) 63 0 Intentional: 63 Intentional 63 Other: 13 Other 13 Unintentional: 1 Unintentional 1
Intent (risk entries)
LabelValue
Intentional63
Other13
Unintentional1
Timing (risk entries)
Timing (risk entries) 72 0 Post-deployment: 72 Post-deployment 72 Other: 5 Other 5
Timing (risk entries)
LabelValue
Post-deployment72
Other5
Recorded incidents per yearIncident date; current year partial
Recorded incidents per year 190 0 2014: 1 2014 1 2016: 2 2016 2 2017: 2 2017 2 2018: 1 2018 1 2019: 3 2019 3 2020: 9 2020 9 2021: 4 2021 4 2022: 13 2022 13 2023: 43 2023 43 2024: 103 2024 103 2025: 190 2025 190 2026: 40 2026 40
Recorded incidents per year
LabelValue
20141
20162
20172
20181
20193
20209
20214
202213
202343
2024103
2025190
202640
Entries by levelRisk categories, subcategories and additional evidence coded to this subdomain
Entries by level 64 0 Risk Category: 13 Risk Category 13 Risk Sub-Category: 64 Risk Sub-Category 64
Entries by level
LabelValue
Risk Category13
Risk Sub-Category64
  • Harmful Content Generation at Scale: Non-Consensual Content

    "The misuse of generative AI has been widely recognized in the context of harms caused by non-consensual content generation. Historically, generative adversarial networks (GANs) have been used to gene...

    The Ethics of Advanced AI Assistants (Gabriel2024) · Human · Intentional · Post-deployment

  • Harmful Content Generation at Scale: Fraudulent Services

    "Malicious actors could leverage advanced AI assistant technology to create deceptive applications and platforms. AI assistants with the ability to produce markup content can assist malicious users wi...

    The Ethics of Advanced AI Assistants (Gabriel2024) · Human · Intentional · Post-deployment

  • AI-driven highly personalized advertisement

    "Advanced GPAI systems can create advertisements tailored to individual recip- ients, exploiting the biases and irrational beliefs of each recipient. Such adver- tisements can cause consumers to make...

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

  • Multimodal deepfakes

    "Deepfakes are media that depict real or non-existent people or events, involving the use of multiple modalities (e.g., images, audio, video). They can also involve the imitation of speech or body mov...

    Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems (Gipiškis2024) · Human · Intentional · Post-deployment

  • Generation of personalized content for harassment, extortion, or intimidation

    "GPAIs can be misused for the automated generation of content personalized to target select individuals based on their weak spots [30]. Such attacks may be more efficient and more successful in achiev...

    Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems (Gipiškis2024) · Human · Intentional · Post-deployment

  • GPAI assisted impersonation

    "GPAI outputs are not always correctly detected as AI-generated across multiple modalities (text, images, audio, video). A malicious actor can use GPAI outputs directly when communicating, or use AI-i...

    Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems (Gipiškis2024) · Human · Intentional · Post-deployment

  • AI-driven spear phishing attacks

    "Generative models can be misused to target individual users more efficiently by using personalized information [23]. Highly convincing automated fraudulent schemes can exploit the trust of victims by...

    Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems (Gipiškis2024) · Human · Intentional · Post-deployment

  • Malicious use and abuse (cybercrime)

    "The advanced capabilities and widespread availability of generative AI models make it possible for malicious actors to conduct harmful activities with great efficiency and on a large scale, simultane...

    Regulating under Uncertainty: Governance Options for Generative AI (G'sell2024) · Human · Intentional · Post-deployment

  • Malicious use and abuse (sexually explicit content generation)

    "An illustrative case of malicious use of generative AI models is the creation of explicit sexual images. Generative AI technologies can be employed to produce deepfakes—for instance, superimposing a...

    Regulating under Uncertainty: Governance Options for Generative AI (G'sell2024) · Human · Intentional · Post-deployment

  • Malicious Use of AI

    Malicious utilization of AI has the potential to endanger digital security, physical security, and political security. International law enforcement entities grapple with a variety of risks linked to...

    Artificial Intelligence Trust, Risk and Security Management (AI TRiSM): Frameworks, Applications, Challenges and Future Research Directions (Habbal2024) · Human · Intentional · Post-deployment

  • Education - Learning

    In contrast to traditional machine learning, the impact of generative AI in the educational sector receives considerable attention in the academic literature. Next to issues stemming from difficulties...

    Mapping the Ethics of Generative AI: A Comprehensive Scoping Review (Hagendorff2024) · Human · Intentional · Post-deployment

  • Writing - Research

    Partly overlapping with the discussion on impacts of generative AI on educational institutions, this topic cluster concerns mostly negative effects of LLMs on writing skills and research manuscript co...

    Mapping the Ethics of Generative AI: A Comprehensive Scoping Review (Hagendorff2024) · AI · Unintentional · Post-deployment

  • Deception

    "AI has become very good at creating fake content. From text to photos, audio and video. The name "Deep Fake" refers to content that is fake at such a level of complexity that our mind rules out the p...

    A framework for ethical Ai at the United Nations (Hogenhout2021) · AI · Other · Post-deployment

  • Nonconsensual use

    "Generative AI models might be intentionally used to imitate people through deepfakes by using video, images, audio, or other modalities without their consent."

    AI Risk Atlas (IBM2025) · Human · Intentional · Post-deployment

  • Impact on education: plagiarism

    "Easy access to high-quality generative models might result in students that use AI models to plagiarize existing work intentionally or unintentionally."

    AI Risk Atlas (IBM2025) · Human · Other · Post-deployment

  • Impact on education: bypassing learning

    "Easy access to high-quality generative models might result in students that use AI models to bypass the learning process."

    AI Risk Atlas (IBM2025) · Human · Intentional · Post-deployment

  • Impersonation / identity theft

    "Theft of an individual, group or organisation’s identity by a third-party in order to defraud, mock or otherwise harm them or another party"

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

  • IP / copyright / personality / rights loss

    "Misuse or abuse of an individual or organisation’s intellectual property, including copyright, trademarks, and patents. & Loss of or restrictions to the rights of an individual to control the commerc...

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

  • Economic manipulation

    "Generative AI facilitating targeted manipulation of public opinion for economic purposes (e.g., inflating stock prices)"

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

  • Cheating / plagiarism

    "Use of generative AI in an academic setting to either cheat or plagiarize"

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

  • Defamation / libel / slander

    "Use of a technology system to create, facilitate or amplify false perception(s) about an individual, group or organisation"

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

  • Sexualization

    "The non-consensual sexualisation of an individual or group using a technology or application"

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

  • Social-Engineering

    psychologically manipulating victims into performing the desired actions for malicious purposes

    Trustworthy LLMs: A Survey and Guideline for Evaluating Large Language Models’ Alignment (Liu2024) · Human · Intentional · Post-deployment

  • Cybercrime

    "The increasingly advanced capabilities and availability of general purpose AI models could be misused for improvements in efficiency and efficacy of cyber crimes. This is especially true for crimes t...

    Governing General Purpose AI: A Comprehensive Map of Unreliability, Misuse and Systemic Risks (Maham2023 ) · Human · Intentional · Post-deployment

  • Misuse tactics that exploit GenAI capabilities (Realistic depiction of human likeness)

    -

    Generative AI Misuse: A Taxonomy of Tactics and Insights from Real-World Data (Marchal2024) · Human · Intentional · Post-deployment