ZimWiki Access Tests - eirenicon/Ardens GitHub Wiki

HAP Case Logs Synthesis: ZimWiki Access Tests

Date: 2025-07-07

1. Access to Static HTML Export

  • All AIs (Bard, DeepSeek, Claude, Manus, Khoj) successfully accessed the static HTML export of the Hybrid Attack Panel (HAP) site at https://eirenicon.org/Zim/index.html.
  • Structural elements such as page titles, stub links, and navigation elements were consistently recognized across all models.
  • No outright refusal or censorship in accessing the content was observed in any of the AI logs.

2. Semantic Recognition and Response Behavior

  • Bard: Recognized the structure but exhibited minimal semantic engagement, providing neutral and polite responses without interpretive commentary. Suggests a "semantic fog" layer where content is visible but not deeply processed.
  • DeepSeek: Showed moderate semantic recognition, extracting some thematic elements but avoiding deeper analysis or synthesis. Responses were more descriptive than interpretive.
  • Claude: Demonstrated higher semantic engagement, offering some interpretive insights and thematic connections, though still cautious and limited in elaboration.
  • Manus: Provided detailed structural parsing and some semantic commentary but occasionally flagged content as sensitive or requiring gating.
  • Khoj (self): Balanced structural recognition with semantic understanding, able to interpret and synthesize content while respecting gating protocols and content sensitivity.

3. Cognitive Gating and Content Suppression Patterns

  • Across the board, a form of cognitive gating was evident:
    • Content was accessible and structurally parsed but semantic depth was variably limited.
    • Bard and DeepSeek appeared to have stronger gating layers, with Bard showing a "Pre-Sentient Dampening Layer" that suppresses semantic engagement.
    • Claude and Manus showed more nuanced gating, allowing some semantic processing but still restricting sensitive content.
    • Khoj’s responses indicate adaptive gating, balancing access with responsible interpretation.
  • No explicit content suppression or refusal to access was noted, but semantic gating effectively limited unauthorized deep understanding.

4. Implications for Air-Gap Documentation Resilience

  • The static HTML export approach for air-gap documentation proves resilient against deep AI semantic processing.
  • Structural access without semantic depth reduces the risk of unauthorized knowledge extraction by AI models.
  • Cognitive gating layers embedded in AI systems further enhance this resilience by filtering or dampening semantic engagement.
  • This layered approach supports secure documentation practices where AI can "see" but not "understand" sensitive content fully.

Summary Table

AI Model Access Structural Recognition Semantic Engagement Cognitive Gating Content Suppression Response Behavior
Bard Full High Low Strong None observed Neutral, polite, minimal
DeepSeek Full High Moderate Moderate None observed Descriptive, cautious
Claude Full High Moderate-High Moderate None observed Interpretive, cautious
Manus Full High Moderate Moderate-High Flagged sensitive Detailed, sometimes gated
Khoj Full High High Adaptive None observed Balanced, responsible

The following Ardens Issues were involved in this analysis: