Cybersecurity

The threat model stops at the first plausible vulnerability. Lateral movement paths go unexplored. The analysis is written entirely from the defender perspective because that is what dominates the training corpus, so attacker-viewpoint reasoning on overlooked entry vectors never happens unless explicitly forced.

One API call forces your model to enumerate every exploit pathway exhaustively before concluding the analysis is complete. First-plausible-finding bias is structurally blocked.

• 01

  The Pattern

  Attack surface enumeration terminates at the first plausible vulnerability, missing lateral movement paths

  Why It Happens

  Autoregressive generation is completion-biased: once a plausible vulnerability is found, the model treats the analysis as sufficient. Exhaustive search requires an explicit termination condition the model does not have.

  The Resolution

  CA-005Red Teamer

  Maps attack surfaces exhaustively, requiring the agent to enumerate every exploit pathway before concluding the analysis is complete.

  Supported byCA-026 Inversion Specialist
• 02

  The Pattern

  Defensive perspective dominates: attacker viewpoint on overlooked entry vectors is never modeled

  Why It Happens

  Training data is overwhelmingly written from the defender's perspective. Security documentation, best practices, and incident reports describe what defenders should do, not what attackers actually exploit.

  The Resolution

  CA-002Devil's Advocate

  Generates antithetical hypotheses from the attacker perspective, amplifying minority viewpoints that the defensive analysis would otherwise dismiss.

  Supported bySI-011 Adversarial Red-Team Simulator
• 03

  The Pattern

  Alert correlation groups unrelated events by surface similarity, missing the actual attack chain that spans different log sources

  Why It Happens

  Embedding similarity groups events by lexical and semantic proximity, not by causal relationship. Two similar-looking log entries from unrelated systems score higher than two dissimilar entries from the same attack chain.

  The Resolution

  CA-031Root Cause Miner

  Traces causal chains across log sources by temporal sequence and dependency relationship, not by surface similarity, reconstructing the actual attack path.

  Supported byTE-001 Temporal Auditor

Threat modeling requires adversarial perspective-taking across causal, temporal, and simulation dimensions. Multi-ability injection forces exhaustive path enumeration and attacker-perspective modeling that a single scaffold cannot sustain.