yogsoth-ai Adversarial Roleplay Tactic
Deploy constructed hostile personas to attack the artifact from distinct motivational frames.
Orchestration
- persona-construction builds detailed adversary profile:
- Background and expertise domain
- Motivation for attacking (career incentive, resource competition, ideological)
- Known blind spots and biases of this persona type
- Preferred attack patterns
- attack-vector-generation generates vectors specific to persona's expertise and motivation
- probe-execution executes attacks while maintaining persona consistency
- Successful attack paths recorded with persona attribution
- Process repeats for each persona (budget-limited)
- finding-aggregation cross-references findings across personas for convergent vulnerabilities
Subagents Dispatched
- persona-construction (1 call per persona)
- attack-vector-generation (1 call per persona)
- probe-execution (N calls per persona, budget-limited)
- finding-aggregation (1 call at end, cross-persona)
Termination Conditions
- All budgeted personas deployed and exhausted
- Convergent vulnerability found by 2+ personas (high-confidence finding)
- Single persona finds critical vulnerability (early report)
- Budget exhausted (report per-persona findings separately)
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| attack-vector-generation | Generate specific attack strategies for a given threat surface, producing concrete probes that can be executed. |
| finding-aggregation | Aggregate, deduplicate, and classify findings from multiple probes into a coherent vulnerability report. |
| persona-construction | Build a detailed adversarial persona with background, motivation, expertise, blind spots, and preferred attack patterns. |
| probe-execution | Execute a single attack probe against an artifact, record the result with evidence and severity classification. |