Weaponizing Generative AI: Emerging TTPs in Adversarial Operations

By: Rick Froggatt - July 2025
CIO ToriiGate Security Consulting, LLC

Introduction

The proliferation of generative AI tools has opened new avenues for threat actors to scale malicious operations, automate reconnaissance, and subvert traditional defenses. As enterprise adoption grows, adversaries are rapidly adapting, exploiting vulnerabilities that are unique to large language models (LLMs) and other AI-driven platforms. This article explores the most recent tactics, techniques, and procedures being used by malicious actors, along with the strategic implications for defenders.

Key Exploitation Techniques

Threat actors are actively deploying prompt injection attacks by embedding adversarial instructions into user-generated content or backend data. This allows them to manipulate AI behavior, cause data leakage, and override safety systems. Data poisoning has also emerged as a viable tactic, wherein attackers feed corrupted data into training sets or context inputs. This can degrade model performance, inject bias, or introduce misinformation into AI outputs.

Jailbreak prompts continue to evolve, offering attackers pathways to bypass content moderation and generate prohibited outputs such as exploit code or phishing kits. Models like FraudGPT are being marketed within dark web communities to generate malware, RATs, and keyloggers with little technical overhead. Meanwhile, LLMs are increasingly used for automated reconnaissance—mining open-source intelligence and crafting highly tailored social engineering payloads at scale.

Defensive Countermeasures

To mitigate these emerging risks, organizations are investing in adaptive multi-factor authentication and behavioral analytics to detect anomalous patterns resulting from AI-enabled attacks. Red team simulations now incorporate generative AI scenarios to prepare defenders for novel threat vectors. Monitoring dark web channels for AI-related developments is also essential, as new tools and exploit kits emerge with alarming frequency. On the technical front, input sanitization strategies must be redefined to account for context-aware attacks, especially those aimed at prompt injection vulnerabilities.

Strategic Implications

The rise of generative AI in cyber operations marks a pivotal shift—from skill-centric exploitation to scalable, automated tooling. Nation-states and cybercrime syndicates are probing AI systems for capabilities that extend beyond traditional attack vectors. While these TTPs often resemble conventional methods, the velocity and reach enabled by generative AI are unprecedented.

Security teams must evolve by integrating AI threat models into tabletop exercises, refining detection logic to capture AI-generated artifacts, and establishing governance frameworks around model inputs and outputs. The threat landscape has changed, and with it, so must our defenses.

Contact us: ToriiGate Security Consulting, LLC