MIT AI Risk Repository · Risk Sub-Category · 63.10.03
Social Engineering at Scale
Category: Multi-Agent Security
Description
"Social Engineering at Scale. Advanced AI agents will be more easily able to interact with large numbers of humans, and vice versa. This provides a wider attack surface for various forms of automated social engineering (Ai et al., 2024). For example, coordinated agents could use advanced surveillance tools and produce personalized phishing or manipulative content at scale, adjusting their tactics based on user feedback (Figueiredo et al., 2024; Hazell, 2023). A large number of subtle interactions with a range of seemingly independent AI agents might be more likely to lead to someone being pers
From Multi-Agent Risks from Advanced AI (Hammond2025), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
- Subdomain
- 7.6 Multi-agent risks
- Causal entity
- AI
- Intent
- Intentional
- Timing
- Post-deployment
Subdomain definition: Risks from multi-agent interactions, due to incentives (which can lead to conflict or collusion) and/or the structure of multi-agent systems, which can create cascading failures, selection pressures, new security vulnerabilities, and a lack of shared information and trust.
How other frameworks describe this risk
- Groups of LLM-Agents May Show Emergent Functionality
- Collusion between LLM-Agents
- Multi-Agent Safety Is Not Assured by Single-Agent Safety
- Foundationality May Cause Correlated Failures
- Financial instability due to model homogeneity
- Impact on Financial Stability
- Multi-agent collaboration capability
- Multi-agent collusion propensity: