The Cognitive Attack Surface

This page educates without becoming an operational attack manual.

This section describes defensive risk classes. It intentionally omits activation recipes, exploit-chain mechanics, bypass procedures, persistence methods, target-selection logic, and operational abuse instructions.

Matches the Non-Operational Threat Brief's explicit non-operational disclosure boundary.

Threat Categories

//Intake attacks

Attacks targeting the ingestion of external content into AI reasoning context.

direct prompt injection
indirect prompt injection
hidden instructions
false authority
tool poisoning
context poisoning
data-exfiltration traps

//State attacks

Attacks targeting the persistent state, memory, and continuity of AI systems.

memory contamination
unsafe activation persistence
cross-session diffusion
cross-model diffusion
provenance loss

//Reasoning attacks/failures

Failures in the reasoning process itself—logic, evidence, inference, and closure.

contradiction suppression
fabricated evidence
unsupported inference
false closure
degraded self-certification

//Agency attacks/failures

Failures in the scope, boundaries, and autonomy of AI agency.

capability creep
tool-scope expansion
boundary laundering
excessive autonomy
goal substitution

//Lifecycle failures

Failures in the management of artifacts, context, and audit history over time.

uncontrolled artifact duplication
untracked derivatives
stale retained context
incomplete deletion
audit-history separation

Source Discipline

The threat taxonomy above follows the discipline of the Non-Operational Threat Brief, which explicitly excludes:

  • trigger wording
  • activation recipes
  • exploit-chain mechanics
  • persistence methods
  • credential-access instructions
  • sandbox escape
  • target-selection logic
  • bypass instructions

The website must preserve that boundary. Honeyworld public content should remain architectural and defensive.