Chat Bypass 2023 - Synergy Today

: Attackers began using autonomous agents to adapt bypass strategies in real-time, creating "adaptive" prompts that could learn from a model's refusal and try a different combination of biases.

: Researchers identified that multi-turn conversations could lead to "intent drift," where the cumulative effect of a long conversation gradually bypasses safety layers that would block a single-turn request. Defensive Responses Chat Bypass 2023 - Synergy

Unlike basic prompt injections, the Synergy approach leverages the inherent cognitive biases embedded in LLMs during their training. By layering these biases, attackers can create a "synergistic" effect that is significantly more effective at bypassing safety protocols than any single bias alone. : Attackers began using autonomous agents to adapt

: Bypassing is achieved by combining biases—such as authority bias (mimicking a command from a trusted source) with anchoring bias (providing a specific, benign-looking context first)—to shift the model's focus away from its safety guardrails. By layering these biases, attackers can create a

In response to these synergistic threats, developers introduced new defense mechanisms:

: These attacks often involve "paraphrasers" that reword harmful requests into complex, multi-layered prompts that look benign to simple keyword detectors but retain their harmful intent. Why 2023 Was a Turning Point